Chapter 19 Scale-up of high-shear binder-agglomeration processes

C H A P T E R 19

Scale-Up of High-Shear BinderAgglomeration Processes Paul Mort* Procter & Gamble Co., ITC, 5299 Spring Grove Ave., Cincinnati, OH 45217, USA Contents

1. Introduction 1.1. Product design 1.2. Transformations 1.3. Process equipment/systems 1.4. Scale of scrutiny 1.5. Economy of scale 2. Product attributes - the micro-scale approach 2.1. Dispersion, wetting, and binder coverage 2.2. Interfacial reaction and drying 2.3. Granule structure - saturation 2.4. Nucleation 2.5. Granule growth - stokes criterion for viscous dissipation 2.6. Granule growth - coalescence 2.7. Growth limitation 2.8. Granule consolidation 2.9. Attrition, breakage 3. Scale up of process equipment- the macro-approach 3.1. Power-draw, torque 3.2. Specific energy (E/M) 3.3. Swept volume 3.4. Stress and flow fields 3.4.1. Granulation under gravitational flow 3.4.2. Granulation with centripetal flows 3.5. Delivery number 3.6. Spray flux 3.7. Process ancillaries 4. Multi-scale approach -linking micro- and macro-scale approaches 5. Summary and forward look 5.1. Flow patterns in mixers 5.2. Binder spray flux 5.3. Linkage of process parameters with material properties 5.4. Batch and continuous systems

*Corresponding author. E-mail: [email protected]

Granulation Edited by A.D. Salman, M.J. Hounslow and J. P. K. Seville

~{~ 2007 Elsevier B.V. All rights reserved

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854 5.5. Productive use of recycle 5.6. Models 6. Conclusion Acknowledgments References

P. Mort 892 892 893 894 894

1. INTRODUCTION This chapter describes scale-up of batch and continuous granulation processes where a liquid binder is added to fine powder in order to form a granular product. The technical goal of scale-up is to maintain similarity of critical product attributes as the production scale and/or throughput of a manufacturing process is increased. This chapter provides a framework for scaling-up that considers critical process transformations in relation to the desired product attributes. A similar approach can be taken in developing process control strategies. In any agglomeration process, transformations can be used to describe how raw materials (typically fine powders and liquid binders) are converted into a granular product. While critical product attributes may be characterized on the scale of individual granules (e.g., size, shape, porosity, mechanical strength, etc.), industrial scaleup requires predictive relations for the sizing, design and operation of larger-scale process equipment. Considering scale-up on the basis of transformations is one way to link the macro-scale equipment decisions with micro-scale product attributes. This approach can be applied to the scale-up of batch and/or continuous granulation processes as well as transitioning from small batch prototypes to continuous production circuits While much of the content of this chapter is taken from a recent review article [1], new material is also presented, mainly in the form of a proposed framework for the description and analysis of continuum flow and stress fields in mixergranulators (Section 3.4). The implications of flow and stress fields for scale-up of granulation processes are discussed throughout. The earlier review [1] was published as part of a topical issue of Powder Technology on Scale-up of Industrial Processes. This issue includes a collection of papers that were initially given as invited presentations at the 2002 Annual Meeting of the Particle Technology Forum (PTF) / AIChE, including coating, heat transfer, crystallization, fluidization, etc.

1.1. Product design A current trend in the design of granular products is the move toward "engineered particles". Agglomerates are no longer simply random aggregates of powder and binder materials; rather, granular structures are being designed to perform

Scale-Up of High-Shear Binder-Agglomeration Processes

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specific product functions. Examples of designed structure include surface characteristics (e.g., via coatings), porosity and other composite structural features. To improve product performance, it is first necessary to make the link between the desired performance of the product and the specific granular attributes that are associated with the performance benefit. Identifying the relationships between product performance and the physical-chemical attributes of the agglomerates is not necessarily an obvious step. Further, once the key attributes have been identified, the agglomeration process needs to maintain the desired attributes on scale-up to full production. Often, key attributes depend on microscale structural features. Process scale-up may depend on linking this microscale understanding to bulk production on a macro-level. With powders, it is rarely obvious how to bridge these scales. The scope of agglomeration processing includes many different materials over wide scales of production, from specialty materials and pharmaceuticals made in kg/day batches to continuous processes for detergents and fertilizers measured in tons/hour. Agglomeration adds value to the product, for example, by producing free-flowing, dust-free particles that are optimized for uses, such as tabletting, dispersion/dissolution and compact delivery (i.e., to increase the bulk density). There are a number of key physical attributes of agglomerates that are essential for product performance, such as granule size, size distribution, density, flowability, mechanical integrity, compressibility and dispersion. An optimal agglomeration process will, in a controlled and reproducible way, produce granules with design attributes that are relevant to the desired product performance. Characterization of the important attributes may require investigation on several different scales of scrutiny. While specific single-particle attributes may require micro-scale scrutiny (e.g., particle size, intra-granular porosity), bulk or meso-scale characterization is more appropriate for inter-particle characteristics, such as flow, compressibility, packing and bulk dispersion. Modeling and simulation tools are becoming more and more important in this scheme of product evolution, both from a product design and process perspective. It is often easier and much more cost efficient to conduct experiments on a small scale, and then use models and/or simulation tools to scale up to larger production facilities. In terms of product engineering, modeling and simulation tools can be very useful in making functional linkages between material properties and product performance across various scales of scrutiny.

1.2. Transformations Transformations describe the many ways in which the raw materials are changed by the process to form the product [2,3]. Agglomeration includes a complicated collection of transformations, typically including the mixing of powder feeds,

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Agglomeration Transformations =f(Material Properties, Process Parameters) ;~..'..~.:~:.~.:.~::. "'1111._._..~ ~ ;~':~:.~:"~:'~"..':.? -I- U Material Properties Powders: Binder: 9particle size 9viscosity, &distribution, 9 9shape, 9yield 9surface area, stress, 9 roughness, 9surface porosity, tension 9surface Vapor: chemistry... 9humidity

Process parameters: 9applied forces, 9 rate of impact or shear, 9residence time, Granular Product 9energy, 9fluidization, O O @O 9temperature... @ @@ @ I

~

I

@@

~

ProductAttributes: I 9particle size and Transformations: distribution, 9atomization, 9shape, 9 dispersion, 9 porosity & density 9 (bulk, particle), 9 mixing, 9compositional 9r e a c t i o n , homogeneity, 9particle growth, 9 yield stress, 9densification, 9fracture toughness, 9drying, 9flowability, 9 attrition... 9tabletability...

Fig. 1. Linkage between material properties, process parameters, transformations and product attributes in a binder agglomeration process. binder atomization, dispersion of binder in powders, wetting and spreading of binder on particle surfaces, chemical reactions between binder and powder (and sometimes vapor phase), particle growth by coalescence, consolidation, attrition and drying. This chapter reviews the recent agglomeration literature with the aim of summarizing transformations that typically have an important role in agglomeration processes. It also describes sets of process parameters and material properties that are critical to scale-up and process control (Fig. 1). In considering how to link the scale-up of agglomeration equipment with the need to maintain specific product attributes, one may find it helpful to separate the actions of the equipment (i.e., the process parameters) from the properties of the materials being processed. In a binder agglomeration process, both the solids and liquid binder properties are relevant, as are their interactions. Note that material properties may be especially relevant in intermediate states (i.e., a wet-mass) where the constitutive relations may change dramatically as a function of both composition (wet and dry) and consolidation. In addition, the properties of the gas phase can be very important to consider in scale-up, especially the moisture balance between the wet-mass product and the headspace or air-stream in the process. In identifying the key transformations, linkages between process parameters and the material properties are reconciled in the form of controlling groups. Wherever possible, it is recommended to separate (either temporally or spatially) the key transformations in a process. This is especially relevant in agglomeration processes where a large number of potentially conflicting transformations may be

Scale-Up of High-Shear Binder-Agglomeration Processes

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occurring simultaneously (e.g., wetting-drying, growth-breakage, mixing-segregation, etc.) Additionally, the separation of critical transformations can be very useful in moving toward single-variable process control strategies [4].

1.3. Process equipment/systems This chapter is not intended to give a comprehensive review of agglomeration process equipment. For more discussion on agglomeration unit operations, there are several excellent references that are readily available [5,6]. The current discussion considers process equipment in terms of process parameters. There are various classes of agglomeration processes. For example, high-shear agglomerators typically operate with mechanical impellers at speeds sufficient to impose high impact and/or shear stresses on the wet mass. Roller compactors are also capable of high mechanical energy transfer from the process to the product. On the other hand, fluid-bed agglomerators are lower-shear devices with lower transfer of mechanical energy to the product. These various types of agglomeration processes can be distinguished according to their process parameters (Fig. 1) and relative interaction between these parameters and the product (i.e., transformations). Many agglomeration devices have been developed as "black boxes" and do not allow the user to visually inspect the transformations as they occur. Exceptions include lab-scale equipment made with glass or transparent polymer vessels (e.g., a fluid-bed agglomerator with a glass riser), or in some cases, pan agglomerators. The "black-box" unit operation has reinforced the view of agglomeration as an "art" rather than a "science". As a step toward a more scientific approach, transformations (i.e., transforming from raw materials into a product) are used to describe and quantify the changes that occur in materials as they are processed. In the case of binder agglomeration, we start with powders and binders that have a variety of distinct material properties, and these materials are transformed in a variety of ways to produce a product. The transformations are typically controlled by the process parameters and material properties. In regards to the equipment scope, engineers consider the overall plant system involved with the agglomeration process. There is often considerable complexity in ancillary equipment (e.g., hoppers, feeders, transport, recycle loops, grinding, classification, etc.) beyond the unit operations that are most directly associated with agglomeration (e.g., mixer-agglomerators, drums, fluid beds, etc.). In many cases, these ancillary devices are tightly connected to the agglomeration process and have significant effects (both good and bad) on product quality as well as overall system reliability. It is necessary to consider these ancillary operations in a successful scale-up strategy, especially given that process rate bottlenecks often occur in ancillary solids handling operations (hoppers, chutes, conveying lines, bucket elevators, etc.). Wherever possible, it is preferred to simplify the

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overall plant operation by reducing the number of steps in the process and especially to reduce or eliminate non-productive handling and transformations.

1.4. Scale of scrutiny Overall, the goal of scale-up is to maintain identical product attributes (micro-scale) across production scales (macro-scale). A successful scale-up depends on considering both scales of scrutiny. In an industrial scenario, a project team may include members whose specific focus and area of expertise is on one scale or the other. The success of the team depends on coordination of both levels of expertise. A typical macro-scale approach determines desired operating conditions over a range of dimensionally similar unit operations using dimensionless groups, such as Froude Number, Stokes Number, Reynolds Number, and Power Number. The concepts of dimensional similarity and controlling groups are discussed in more detail in the section on Scale-up of Process Equipment. According to the macroscale approach, a measurable process parameter, such as power draw in a vertical granulator, is used to determine the desired process residence time (e.g., endpoint in a batch mixer or fill level in a continuous mixer). This provides guidelines for scale-up of the equipment operation. Empirical adjustment of parameters is still required to achieve the desired product attributes. On the other hand, a micro-scale analysis is useful in characterizing important transformations and defining mechanistic linkages between transformations and desired product attributes on a particle scale. The challenge is to maintain the similarity of each transformation during scale-up. This approach helps in predicting the feasibility of scale-up around specific attributes, and also helps to guide empirical adjustment of process parameters needed to achieve the desired results.

1.5. Economy of scale In the industrial production of a commercial product, an implicit goal of scale-up is to improve the economy of production. This economic analysis (e.g., a cost/value function) is critical to industrial applications, especially when considering tradeoffs in a scale-up execution. While this chapter includes some practical suggestions for scaleup efficiency, a detailed economic analysis is beyond the scope of the current work.

2. PRODUCT ATTRIBUTES - THE MICRO-SCALE APPROACH The micro-scale approach to scale-up is based on defining the key transformations in an agglomeration process on the scale of individual granules. Earlier

Scale-Up of High-Shear Binder-Agglomeration Processes

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descriptions of granulation on the micro-scale involve complex collections of mechanisms using a population balance modeling approach [7]; while these mechanisms provide a useful micro-scale view, the complexity of the approach has proven to be excessive for practical scale-up applications. On the other hand, a more recent view has been to define granulation in terms of three sets of rate phenomena: nucleation: growth; and breakage [8]. The current review follows an intermediate approach, where the mechanisms are described in terms of key transformations (e.g., binder distribution, nucleation, growth, consolidation, and breakage), and selected based on their relevance to the desired product attributes (e.g., chemical homogeneity, granular size, size distribution, and granule density). The challenge is then to maintain the similarity of each transformation during scale-up. This approach helps in scale-up of specific product attributes, and helps in the adjustment of parameters needed to achieve the desired results. Transformations describe the many ways in which the raw materials are changed by the process to form the product (Fig. 1). For example, atomization and binder droplet size can be a key to granule nucleation and growth. Dispersion of binder in the powder is often correlated to the breadth of distributed properties. Wetting refers to the micro-scale spreading of binder on powder surfaces. Reactions may occur between binder and powders. Particle growth is generally regarded as the primary transformation in the agglomeration process; however, it is very much affected by many of the other transformations. Granule consolidation is often coupled with growth and coalescence. Moisture removal may be required to form a dry, flowable product from an aqueous binder system and drying has a very strong effect on other transformations if it is done concurrently in the process. Attrition, or particle breakage, is often regarded as a negative transformation; however, it can also be used advantageously in limiting the breadth of particle size distributions and in improving the chemical homogeneity of the product. Key powder properties include particle size, size distribution, shape, surface area, surface roughness, porosity and surface chemistry. Some of these, such as size distribution and surface area, can be characterized by fairly direct measurements. Others, such as shape and roughness are more qualitative measurements. Surface chemistry is a very important and often difficult area to characterize. Subtle changes in surface chemistry can have significant effects on the agglomeration process. Binder properties are most commonly characterized in terms of viscosity, although viscoelasticity and yield stress may also be relevant, especially in melt granulation and/or with binders that are used to deliver an active ingredient to the formulation. There are a variety of adjustable process parameters covering the combined collection of agglomeration unit operations. Here, these have been compressed into a short list of key parameter groups. Certainly, fluidization is a key to systems using binder sprays; shear rate is a key to binder dispersion and agglomerate consolidation; and impact velocity affects consolidation and breakage. Material

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properties, such as binder rheology, solubility of solids in the binder, reaction rates, and drying are sensitive to temperature. In the following discussion, interactions between material properties and process parameters are illustrated on a series of simple transformation maps.

2.1. Dispersion, wetting, and binder coverage For high-shear mixers, the dispersion of a binder in a powder depends both on the binder viscosity and the applied shear rate of the process [9]. A combination of high shear and low viscosity will disperse the binder evenly throughout the powder mass while a viscous binder with insufficient shear results in a heterogeneous mixture of over-wet globules and dry powder (Fig. 2a). In top-spray fluid-bed agglomeration, the dispersion of the binder depends on the spray coverage relative to the mass in mixer, as well as the turnover of the powder mass (i.e., fluidization). Here, the best dispersion is achieved with a large area of spray coverage and aggressive fluidization (Fig. 2b). The effect of binder spray flux on dispersion (Fig. 2b) is well illustrated in the series of papers by Watano et al. [10]. Wetting coverage refers to the local distribution of the binder on the particle surface. This depends on both the bulk dispersion of binder in the powder and the wetting chemistry between the binder and powder surface. Maximum binder coverage requires both good bulk dispersion and low binder-powder contact angle (Fig. 2c). The effect of heterogeneous binder distribution is often seen in the compositional assay of granules classified into a series of size cuts, i.e., a sieve-assay. Given that the binder loading contributes to growth, it is understandable that, within a granule size distribution, the finer particles are often found to have lower binder content [11].

2.2. Interracial reaction and drying Some granulation systems involve reactions between a binder and a powder. For instance, an aqueous binder will hydrate starch excipients in a pharmaceutical a) Dispersion-mechanicalmixing

~'.-

.___o .(3 ~ 9

poor dispersion

~

uniform dispersion iv

shear rate

b) Dispersion -fluid bed spray . uniform =_olidispersion '

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poor coverage

OC~

poor

o

"-

dispersion --

Iv

binder sprayflux

(D

~

23

good coverage o

iv

dispersion

Fig. 2. Dispersion and wetting transformation maps for binder dispersion: (a) in a mechanical mixer; (b) spray-on in a fluid-bed granulator; (c) coverage of binder on the particle surfaces.

Scale-Up of High-Shear Binder-Agglomeration Processes

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Surface Reaction, Drying slow, incomplete reaction

fast, complete reaction

wetting coverage Fig. 3. Chemical reactions between the binder and the solid powders depend on dispersion and wetting coverage at the solid-liquid interface. In drying, the rate also depends on the liquid coverage over the solid surface; a higher coverage area provides more liquidvapor interface for drying.

granulation. In another example, granular detergents are made by an acid-base reaction between binder and powder. In such cases, reactions occur at the surface interface between the binder and powder; thus, the extent and rate of the reaction depends on the wetting coverage. Drying is somewhat analogous to this, except that the drying rate increases with increasing liquid-gas surface area. This occurs when the binder is thinly distributed over a large powder surface area. Both reaction rate and drying are very important transformations because they can significantly affect binder properties (e.g., viscosity, yield stress) and the effective binder loading (i.e., liquid saturation), which are key to the transformations of granule growth and consolidation (Fig. 3).

2.3. Granule s t r u c t u r e - saturation The primary factor controlling agglomerate growth is the relative binder loading level and degree of saturation in the granule structure (Fig. 4). The filling of the binder in the granule pores is expressed as the saturation ratio, relating the binder volume bridging between particles within the agglomerate to the total available pore and void space between particles [12-14]. The saturation ratio is increased by adding more binder and/or by consolidating agglomerates to reduce their internal porosity. The growth process depends on the success of particles sticking together upon collision. More growth occurs with increasing binder saturation, especially as the saturation approaches 100%. In the (fully-saturated) capillary state, rapid growth occurs by coalescence. Beyond 100% saturation, the particles are suspended in a continuous liquid phase and a paste or over-wet mass results.

2.4. Nucleation The nucleation stage of an agglomeration process is the initial phase where small agglomerates (nuclei) are formed. Two basic mechanisms can be considered

862

P. Mort Relative binder loading in liquid bridge structures a) Filling pores by binder addition: b) Pore space reduction by consolidation: pendular

funicular capillary

droplet

I

saturation

100%

Fig. 4. The structure of granules evolves with increasing binder saturation. Saturation increases by: (a) additional binder loading and/or (b) granular consolidation. a) Distribution Mechanism ~j~ ~ ~

~t dispersio2n 0 0

solid particles

binder

O

agglomerate growth~

wetted particles

agglomerate, size and size distribution controlled by growth mechanism

b) ImmersionMechanism @ |

@ solid particles

immersion~

~ ~

+ binder

agglomerate, size controlled size of binder "template"

Fig. 5. Agglomeration nucleation mechanisms" (a) distribution; (b) immersion. Granule properties typically depend on the mode of nucleation and growth. [15]. The distribution case assumes that the binder disperses as a film on the particle surfaces; nuclei are formed by successful collision and bridging of the particles (Fig. 5a). The immersion case considers a binder droplet or other binder mass as the core of the agglomerate, to which finer solid particles are attached and embedded (Fig. 5b). The results of the agglomeration, especially the size distribution of the agglomerates, can be related to the prevailing mechanism. The immersion mechanism is attractive because the binder droplet size can be used as a control parameter for the product agglomerate size [16]. Immersion is also very useful as a way to encapsulate a sticky binder in a dry shell. An example of experimental work on agglomerate nucleation by droplet immersion shows the effect of binder viscosity and powder-fluid interactions [17]. In this case, binder viscosity is a function of the solution concentration of

Scale-Up of High-Shear Binder-Agglomeration Processes

(a)

(b)

863

(c)

Fig. 6. Binder droplet nucleation experiments from Hapgood [17] using an initial binder droplet diameter of--~2 mm in lactose powder: (a) dyed water, d = 6.5mm; (b) dyed solution of 3.5 wt% HPC, viscosity = 17 cP, d = 3.5 mm; (c) dyed solution of 7 wt% HPC, viscosity = 105 cP, d = 3.0 mm.

hydroxypropyl cellulose (HPC). Relatively large (~2 mm) individual binder droplets with a dye tracer are contacted with a static bed of fine powder. The binder wets into the powder forming nuclei, which are recovered, dried and analyzed (Fig. 6). The lower viscosity binder (water) wets the hydrophilic excipient (lactose) and spreads out from the core (dyed center, capillary structure) to form a looser network of extended pendular hydrate bonds. On the other hand, the water in the more viscous HPC solution is less available to spread and chemically interact with the lactose and the agglomerate retains only a dense capillary core nucleus. This work shows the net effects of initial dispersion of binder in the powder (i.e., as discrete droplets), wetting-spreading interactions between the binder and the powder and chemical interactions between the binder and powder substrate. Schaafsma et al. [18] proposed a quantitative nucleation ratio based on the volume ratio of the agglomerate nucleus relative to the binder droplet. It is instructive to notice that while the absolute size of nuclei formed using the simple single-droplet nucleation experiment (as shown in Fig. 6) can be an order of magnitude larger than nuclei formed in an actual granulation process with a spray atomizer, the nucleation ratio is reasonably consistent across scales. For example, structural differentiation of lactose nuclei made with different binders (water vs. HPC solution) has been shown to be consistent for a wide range of droplet sizes [17] (Fig. 7). This suggests that the simple single-droplet experiment is a useful first step to investigate binder-powder interactions and their effects on the formation of nuclei structures [19].

2.5. Granule growth- stokes criterion for viscous dissipation Growth processes can be modeled using a force or energy balance that relates forces applied in the process to material properties. The relevant material properties depend on the growth mechanism (Fig. 8). In terms of process control

864

P. Mort 4, ~" 40._o '~ ~' ,- 30 ............... '~I~ .................

~, water

4, I " 7% HPC soln. ..........................................................................................

o, sola!:;: r!

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-,~ 20 ......................................................................................... 0

z

o,0 . . . . . . . . .

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1000 Nucleus size (urn)

10000

Fig. 7. Nucleation ratio (K) for agglomerates formed with lactose powder and a binder (either water or an aqueous HPC solution), using both single droplet experiments with a syringe (as per Fig. 6) and nucleation experiments with a spray atomizer.

Agqlomerate Growth: a) Viscous Stokes: -~ o

._~

large

~

MPS

small .-

b) Yield-coalescence:

MPS impact velocity

~

c) Yield-breakage case:

small

~

large

MPS

~ ~

MPS

large

9

MPS

-~

~- impact stress

small MPS impact stress

Fig. 8. Growth transformations analyzed in terms of force balances, where the extent of size growth is given by the mean particle size (MPS) of the granular distribution: (a) viscous Stokes case describes growth limited by viscous dissipation in binder layer; it assumes good binder coverage and the formation of liquid bridges on contact. (b) In the yield-coalescence case, plastic deformation and binder flow must be activated to form bridges between particles and/or embed particles into a binder droplet. To activate binder flow, the stress at impact must exceed the yield stress of the material (either binder or granular composite). In this case, it is assumed that the energy dissipation in plastic deformation of the material is large compared to the impact energy; therefore, no rebound occurs. (c) The yield-deformation-breakage case describes an upper limit to growth based on granular breakage, where the shear stress increases with increasing granule size.

parameters and material properties, the Stokes criteria (Fig. 8a) and the elastic-plastic transformation maps for coalescence (Fig. 8b) appear to be in contradiction. Obviously, it is of critical importance for scale-up and process control that the mechanism of growth is understood. The viscous Stokes criterion for granulation considers the force balance between colliding particles according to the dispersion mechanism (Fig. 5a) [20]. In this case, good binder coverage is assumed, and the success of collisions in

Scale-Up of High-Shear Binder-Agglomeration Processes

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producing larger agglomerates depends on whether the collision energy is sufficiently dissipated by the viscous binder to prevent the elastic rebound from breaking the binder bridge between the particles. Further, it is assumed that the binder rheology and surface tension permit the spontaneously formation of a liquid bridge on contact. The limitation to growth occurs when the viscous dissipation in the binder is not sufficient to absorb the elastic rebound energy of the collision, as with a low binder viscosity or high collision velocity (Fig. 8a). The Stokes criterion is expressed in the form of a viscous Stokes number (Stv), given as the ratio of the collision energy to the energy of viscous dissipation equation (1), where _~ is the harmonic mean particle size in a collision of two particles equation (2), U the collision velocity, pp the particle density and ~/ the binder viscosity. The critical Stokes number (S~) accounts for binder loading in a system equation (3) where it is assumed that particles possess a solid core. Here, e is the particle coefficient of restitution, h is the binder thickness at the collision surface and ha a characteristic length scale of surface asperities. For conditions in which Stv is less than the critical value, SPv, collisions are successful and growth occurs. For Stv>S_Pv, viscous dissipation is insufficient and rebound occurs (Fig. 9). While it is difficult to measure the parameters in the critical Stokes number, it can be convenient, in practice, to correlate the ratio h/ha to the degree of binder dispersion. For example, a poorly dispersed binder will result in some areas with thick binder coverage and others with little to no binder. The result is a distribution

1) Particles on

~)..

U~

collision c o u r s e al

a2

2) on Liquid contact bridge forms

3) Elastic collision of core particles, then rebound 4) Is viscous dissipation > inertia?

rebound Stv > St*

~,~S agglomeration Stv < St*

Fig. 9. Agglomeration sequence described by Stokes criteria.

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P. Mort

of critical Stokes numbers or even a bimodal distribution, leading to heterogeneous growth.

Stv- 8,opUa -

av =

SPv=

9~/

2xal

xa2

al --I- a2

1+

In

(1)

(2)

(3)

Binder rheology is not necessarily confined to Newtonian fluids. In fact, many binder systems exhibit yield-stress behavior. Examples include binder solutions containing longer-chain polymers, especially when the local activity of the polymer on the particle surface changes due to water evaporation, hydration and/or partial dissolution of the particulate solid. In such cases, small collision velocities and/or short collision times may be insufficient to allow for substantial binder flow and liquid bridge formation and more energetic particle collisions may be required to induce agglomerate growth. The combination of a high binder yield stress and a low collision velocity results in low growth while a low yield stress and higher collision velocity results in more growth (Fig. 8b), as long as the dissipation is sufficient to prevent rebound. Energy dissipation can be quantified in terms of viscosity or loss modulus. It is important to note that binder rheology at the time of collision is relevant to this analysis; this is not necessarily the same as the rheology of the starting binder material, measured before addition to the agglomeration process. One must consider other transformations that may alter the binder rheology after it is added to the granulation, such as thermal effects, drying and hydration. Kinetics of these transformations must be considered in processes where binder rheology changes simultaneously with agglomerate growth and consolidation. Other examples of yield-stress binder rheology are found in melt agglomeration. Here, the binder is added as a powder or flake solid, mixed with the other powders, and then transformed into a binder by heating the entire mixture. In its transformation from solid to liquid the binder typically passes through a critical semi-solid or glassy state where the yield-stress drops into the range of shear stress in the process, and growth occurs. Thermo-mechanical analysis can be used to quantify this growth onset [21]. In cases where the binder solids are larger in size than the other powders, melt-agglomeration may proceed according to an immersion mechanism, where the finer solids are embedded into the semi-solid binder particle.

Scale-Up of High-Shear Binder-Agglomeration Processes

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2.6. Granule g r o w t h - coalescence Granular deformation leading to coalescence is a well-documented growth mechanism [22-24]. In coalescence, colliding granules stick together if the collision force is sufficient to plastically deform the granules, increasing the zone of contact, and consolidate the granular microstructures to the extent that enough binder is expressed into the contact zone (Fig. 9). Iveson and Litster proposed a granular growth regime map that shows increasingly rapid growth with increasing deformation at relatively high binder loading [25]. Assuming that there is enough fluid binder within the granular microstructure to hold the deformed parts together and prevent fracture, then growth will occur. Although rebound will occur if the collision is not of sufficient energy to induce elastic to plastic deformation, once the plastic yield stress is exceeded, the energy absorbed is typically quite high compared to the collision energy, minimizing the chance of an elastic rebound to break the formed bridge. Thus, the key transformation is the deformation of the granular microstructure and the flow of capillary binder to the contact zone, where the coalescence bridge is formed. Iveson and Litster describe this deformation propensity in terms of a deformation number (De), where Yg is the granule dynamic yield stress, pp the granule density and U a characteristic collision velocity for the granulator De - ppU2

yg

(41

The key material parameters relate to the deformation of the composite granular microstructure; typically, this is measured as an apparent plastic yield stress of the granular material (Fig. 8b). Note that the yield stress of the wet mass may depend on the deformation rate, which depends on the time scale of collisions and shear-induced consolidation associated with a given agglomeration process [26]. Figure 10 Returning to the apparent contradiction in the transformation maps for the Stokes' criterion vs. plastic coalescence (Fig. 8a and b), on closer analysis, the micro-scale models are not necessarily contradictory. In the case of elastic-plastic collisions leading to coalescence, consider that the critical Stokes number (S~) equation (3) accounts for binder loading in terms of the binder thickness at the zone of contact. During plastic deformation and microstructure consolidation, the binder thickness in the contact zone, h, may increase substantially as binder is expressed from the pore structure into the contact zone, thereby increasing the instantaneous value of S~ at the relevant interface. Further, the value of S~ increases with a decrease in the coefficient of restitution (e), as in the transformation from elastic to plastic deformation. Thus, the forcebalance analyses remain consistent when one treats S~ as a variable that can

868

P. Mort collision of agglomerates

/.,',, --aj

Q o"i > O'y

elastic rebound

plastic deformation of granules, flow of binder into contact zone, coalescence

Fig. 10. Agglomerate growth by plastic deformation and coalescence. Plastic deformation occurs when the collision impact stress (r exceeds the plastic deformation yield stress of the composite granular material (r Plastic deformation of the granules increases the contact zone area. If sufficient binder flows into the contact zone, coalescence occurs. undergo instantaneous change during collisions involving micro-structural redistribution of binder and/or change in restitution due to elastic-plastic transition. 2.7.

Growth

limitation

The yield-deformation-breakage case (Fig. 8c) considers the upper limit of growth in the process, beyond which breakage becomes dominant. The yield limit is expressed as a "Deformation-breakage Stokes number", Stdef [27]. This is the ratio between the kinetic energy of a collision to the energy required for breakage (equation (5)), where Tb is the shear stress required to deform and break the granule. Assuming that the local collision velocity is proportional to the shear rate and the particle size (equation (6)), and that the granule's yield strength is approximated by a power-law rheology model (equation (7)), a power-law relationship is predicted between the limiting size, a*, and the shear rate in the mixer (equation (8)). This approach has been used to analyze the scale-up of agitated fluid-bed granulators [2,10,27]. Stdef = pp U2

(5)

U~ ~x a

(6)

"T,b --

k'~ n

a* = .~((n/2)-1) -I- c

(7) (8)

Scale-Up of High-Shear Binder-Agglomeration Processes

869

Growth is limited by the balance of the collision stress applied to the granule relative to the inherent fracture stress of the granular material. In theory, agglomerate strength can be considered on the basis of binder-bridge strength between particles [28]. In practice, it is observed that large agglomerates are more prone to fracture than smaller ones for two reasons: (1) for a given impact force, the larger the size of the agglomerate, the greater the moment and the larger the stress that will be exerted on a weak point in the microstructure; and (2) as a composite material, larger agglomerates are more likely to contain a larger number of flaws through which cracks can propagate and cause fracture. While the approach described above provides reasonable correlation with experimental data, it should be noted that it relies heavily on the approximate relationship given in equation (8), where the shear rate is related to the impeller tip speed and a characteristic particle size. In actuality, the material will see a distribution of shear and impact stresses which could lead to breakage, and the distribution will typically depend on the pattern of flow in a mixer-granulator. Another approach is to experimentally measure the critical stress directly using a set of tracer particles [29]. Tracers with known yield stress and breakage behavior are added to the mixer; examination of their remains provides an experimental basis for the in situ stress state in the mixer. Breakage of agglomerates also affects the homogeneity of the product [30]. The dynamic situation of granule growth and breakage leads to a continuous exchange of particles, which improves the homogeneity of the granules. When granule breakage is absent, any heterogeneity due to the nonuniform distribution of the binder in the nucleation stage tends to remain in the final product. In terms of process control parameters and material properties, the elasticplastic transformation map for coalescence (Fig. 8b) and the yield-breakage map (Fig. 8c) appear to be in opposition. In the plastic coalescence case, more growth occurs with increased process energy. In the yield-breakage case, an increase in process energy causes more breakage, lowering the stable size limit. Although both cases are driven by mechanical interaction between the process and the granular materials, the product result is very different, in the elastic-plastic deformation case, the granule is able to absorb all of the impact energy and dissipate it through plastic deformation and heat, resulting in coalescence. On the other hand, the material undergoing yield-breakage cannot absorb all the energy; it reaches a fracture point that limits its growth. The transition between plastic to breakage behavior can be strongly influenced by material properties such as moisture content and temperature [31]. Thus, the relevant transformation map may change during a typical agglomeration process, e.g., progression in temperature and moisture level in a fluid-bed dryer-agglomerator may move the process from case 8b-c or vice versa.

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2.8. Granule consolidation Agglomerate consolidation requires the deformation of a granular structure into a dense-packed structure. Plastic deformation occurs when the localized impact force exceeds the composite yield stress of the granule (Fig. 11). Consolidation can increase the binder saturation ratio by reducing the intragranule void volume and can trigger coalescence when the saturation ratio reaches a critical point. Thus, the consolidation transformation is integral to the mechanism of growth coalescence by plastic deformation. If the yield stress occurs between an elastic and plastic regime, consolidation will occur. Below critical saturation, the granular strength tends to increase with consolidation, typically with an increase in restitution coefficient and/or yield stress. The linkage of consolidation and growth implies two potential feedback loops: (1) a negative feedback to offset growth - as growth proceeds by coalescence, granular densification may cause an increase in the apparent yield stress, thereby limiting further coalescence; and (2) positive feedback which can potentially lead to runaway growth if consolidation increases binder saturation beyond a critical point (e.g., from capillary to droplet structure in Fig. 4b) or if the yield stress is reduced as the result of the internal heat produced by the work of plastic deformation. The dominant scenario is reflected in the value of the exponent "n" in equations (7) and (8). When n > 1, we see a consolidation strengthening effect where the yield stress of the granule increases with consolidation. On the other hand, a value of n < 1 implies a softening of the material with increasing consolidation, which can lead to runaway growth. Obviously, the negative feedback scenario is preferred from the perspective of process control.

2.9. Attrition, breakage As discussed earlier in the discussion of growth limitation, agglomerate breakage is a dynamic part of the process. It is essential to limit growth and to help improve Agglomerate Consolidation

low

density - ~ . m

high e

m c~

density b.. impact stress

Fig. 11. Consolidation of granular microstructure and the elimination of intra-granular porosity.

Scale-Up of High-Shear Binder-Agglomeration Processes

871

the compositional homogeneity of the product. Beyond this, the details of granule attrition and breakage are quite complex. There are different mechanisms for surface breakage (i.e., erosion, abrasion) and particle breakage (fracture, shattering). These depend on material properties including elastic modulus, hardness and fracture toughness (i.e., the resistance to crack propagation), particle shape and impact conditions. In this illustration (Fig. 12), a tough particle may survive a high level of impacts before it finally shatters, while a particle with a lower toughness and/or more irregular shape may progressively break into smaller fragments with increasing impact stress and/or increasing number of impact events. Generally, one of the prime reasons for doing agglomeration is to avoid problems that are encountered with fine particles, e.g., hygiene, dust explosively, or other product performance issues correlated with fines. Obviously, once having made the investment to make the agglomerates, it is paramount to avoid their attrition or abrasion in subsequent handling and conveying operations. Here, there is a balance in approach toward specifying more gentle handling operations vs. the design and production of the agglomerates with increased resistance to attrition. There are a number of criteria for particle breakage, depending on the particle characteristics, material properties and the details of stress loading (compression, shear, stress rate, number of impacts, fatigue, etc.)[32,33].

Agglomerate Attrition a) Impactbreakage iL D shat~ie~~ 9"-'~ c-

O|

OO00 O

b) Compression/ shear

-

~ ~" breakage/ oE

breakage impact stress

o ~ ~ , oo

abrasion

r

IL

shear stress

r

Fig. 12. Attrition of granules as a function applied stress and material properties (composite material toughness, flaw distribution, shape, etc.): (a) single particle impact mode tends to cause intermediate breakage and/or shattering depending on material properties and impact stress; (b)in multi-particle interactions (e.g., shear and compression in bulk handling operations), abrasion can be a problem along with breakage. A more detailed discussion of breakage mechanisms and material property relations are cited in the literature.

872

P. Mort

3. SCALE UP OF PROCESS EQUIPMENT- THE MACRO-APPROACH Scale-up of agglomeration processes based on equipment parameters is referred to herein as the macro-scale approach. Typically, the macro-scale approach determines desired operating conditions over a size range of unit operations using dimensionless groups, such as Froude number, Reynolds number, Power number, swept volume, delivery number and spray flux. While the actual unit operations may or may not be geometrically similar, it is generally sought to maintain the similarity of stress and powder flow fields across a set scales, especially for mixer granulators where the applied stress is critical to the micro-scale transformations. In order to control the stress and flow fields of the powder and granular materials, several other dimensioned parameters or parameter groups that are often used including mixer impeller tip speed, power draw and power draw derivatives. The effect of process time can be combined with power draw in a mixer to be expressed as the cumulative or specific energy dissipation. These operating parameters may typically affect multiple product transformations. It is a challenge to scale up equipment in a way that maintains key product attributes while also achieving an economical and industrially efficient operation. For example, impeller speed and/or the Froude number in a vertical granulator affect binder dispersion, consolidation, coalescence and breakage. Herein is a classic challenge for scale-up: one cannot increase the mixer diameter and keep both Froude number and tip speed constant. The suggested approach identifies the critical transformations based on product attributes and the selects appropriate scale-up criteria. If it is not possible to resolve the key transformations simultaneously, it is then advisable to separate the transformations, either temporally or spatially. For example, by staged processing in a batch unit or adding additional unit operations in a continuous process.

3.1. Power-draw, torque A measurable process parameter, such as power draw in a high-shear vertical granulator, is often used to determine the desired process residence time (e.g., endpoint in a batch mixer or fill level in a continuous mixer). In the pharmaceutical and powder technology literature, there are numerous references on the use of power draw, torque or other similar indicator for endpoint control and scale-up of batch granulation processes [34-39]. While these provide guidelines for scale-up of the equipment operation, empirical adjustment of parameters may still be required to achieve the desired granular product attributes, such as granule size, size distribution and particle density. In a classical scale-up approach [40], dimensionless groups relating process parameters and wet-mass material properties are applied over a series of vertical

Scale-Up of High-Shear Binder-Agglomeration Processes

873

mixer-granulators. The power number (Np) relates the net power draw (AP) to mixer size (D), rotational speed of the agitator (N) and the instantaneous product bulk density (p) (equation (9)). A pseudo-Reynolds number (Re*) describes the kinematic flow in the mixer in terms of product bulk density (p), agitator tip speed (ND), characteristic shear dimension (D) and a pseudo-viscosity (~/*) (equation (10)). Here, r/* is a torque measurement obtained using a Mixer Torque Rheometer (MTR). The MTR compares the measured torque to the applied shear in order to measure the consistency of the wet mass [41]. Other references provide rheological measurements based on compression of the wet mass [42]. Shear cells have also been used to measure the cohesivity or tensile strength of a wetmass sample as a function of its compression state [43]. Each of these methods provide a reasonable correlation between a measured constitutive property and the power draw in the granulation process, where product samples are collected intermittently at different residence times in a batch operation and measurements are made on their rheo-mechanical consistency. The MTR torque is assumed to relate to bulk flow behavior of the wet mass, in a way that is analogous to viscosity in a liquid system. The Froude number (Fr) is the ratio of centrifugal to gravitational forces, and describes the state of fluidization in the mixer (equation (11)). The Fill number describes the relative loading level of the mixer (equation (12)).

Np

AP pN3D 5

Re* = pND2 Jl* N2D Fr= ~ g h Fill # - 5

(9)

(1 O)

(11)

(12)

Analysis of data over a range of mixer scales collapse to an apparent power-law relationship between Np and the product of Fr, Re* and fill numbers [40]. The strongest correlation appears between the power draw and the rate of energy dissipation (i.e., pseudo-viscosity) in the wet mass. The overlap of the data at different scales implies that there is a consistent scale-up relationship between the power draw of the mixer and the wet-mass consistency of the mixture; further, this relationship can be extended across mixers that are not necessarily geometrically similar. This approach demonstrates the use of MTR to characterize samples extracted from the process. It shows that the relevant rheo-mechanical properties of the wet-mass change as the bulk material is transformed during the agglomeration process. Although this approach does not directly address the

874

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scaling of micro-scale product attributes, the inclusion of product density and wet-mass viscosity in the dimensionless groups provide indirect linkages. Some correlation has been shown between the wet-mass properties and subsequent dry-granule product attributes [44]. The importance of the pseudo-Reynolds number underscores the interaction between the wet-mass rheo-mechanical properties (i.e., the transmission of stress through the material) and the tip speed (ND) of the mixer. Note that the collision velocity (U in equations (1), (4), (5), and (6), a key parameter in the micro-scale analysis, is dependent on the tip speed. This highlights the importance of tip speed in scaling up mixer-granulation devices. In another example from the pharmaceutical literature, lab scale tests were done to define an optimum power level for endpoint control in the scaleup of a granulation process in a vertical mixer granulator [45]. The granulation process was followed by tabletting. The critical properties of granular flow, tablet weight variation and tablet disintegration time were optimized together at a single power-draw endpoint on the lab scale. On scale-up to a larger mixer, however, several product attribute issues were encountered. In maintaining similar mechanical fluidization for binder/powder dispersion (i.e., constant Fr), more granular densification occurred, which had a negative effect on tablet properties. Increased granular densification due to the higher impeller tip speed is often encountered when using a Froude Number scale-up to a larger diameter mixer. To adjust the density, the rotational speed can be reduced to approach tip speed (i.e., kinematic) similarity. To maintain equivalent binder distribution at the lower state of fluidization, a reduction of the binder spray flux (i.e., a longer batch time) may be required. It should be noted that the method of binder addition and its distribution in the powder typically becomes more and more critical at larger scales. Another approach to scale-up using power-measurement employs a small-scale batch mixer to estimate the optimal binder loading levels for a formulation to be produced at a larger scale (Fig. 13). In this example, an excess of a binder liquid is intentionally added to the batch mixer-agglomerator at a controlled feed rate, and the power-draw or torque is monitored. In a system where growth is driven by saturation coalescence, a sudden increase in the power draw indicates the onset of rapid agglomerate growth. The level of binder present in the mixer at the powerdraw onset point is defined as an empirical limit for binder addition in the given formulation. To avoid over-agglomeration on scale-up to a production system, the binder addition level is maintained at or below this limit. Note the increase in power consumption can also result in increased product heating due to shaft work (Fig. 13b). Additional examples showing the correlation between power consumption and temperature change are documented in the literature [46]. It should be noted that the binder content at the power draw onset in a small batch mixer is an empirical indicator, not an absolute measure of binder loading

Scale-Up of High-Shear Binder-Agglomeration Processes Add binder

=3

miti

875 Frictional heat, 'k

(1) D ET t_ O F" t_ O

L..

t_ l:D

E

t_ D

Q.

"0

i._

0

a_

Power draw onset

O &.

!

(a)

Batch time

(b)

Batch time

Fig. 13. Determination of formulation binder limit using analysis of power draw onset in a batch mixer: (a) link from power-onset to binder level; (b) increased power draw (i.e., postonset over-agglomeration) results in an increase in frictional heating of the product.

capacity. The more fundamental characteristic of wet agglomerate structure is the saturation [47], which is discussed in more detail earlier in this chapter. Accelerated growth by coalescence and increased power draw typically occur at a critical state of capillary-filled saturation [48]. This structure depends not only on the binder loading level, but also on other scale-dependent process parameters and/or environmental conditions that can affect consolidation, e.g., the tip speed of the impeller, temperature, relative humidity. There is a nesting effect of interrelationships between binder loading, consolidation, saturation, granule growth and power draw. While feedback among these interrelationships may have a confounding effect, one can pose a rational sequence of cause and effect as follows: (1) binder loading and/or consolidation causes an increase in the saturation of the granular structure; (2) increased saturation causes an acceleration of the granular growth kinetics; (3) the combination of the increased particle size and surface-moist cohesion (due to higher saturation) can increase the shear stress transmission within the flow pattern, resulting in an increase in power draw. Further implications are discussed in Section 3.4.2.

3.2. Specific energy (E/M) The net specific energy is a measure of the transformation work being done on the product. Integrating the net power draw over the residence time gives the net energy consumed in the agglomeration process. In a batch process, the net energy divided by the mass holdup gives the net specific energy input, or E/M. In

876

P. Mort

a continuous process, the specific energy can be obtained directly by dividing the net power draw by the feed rate. Specific energy is an appealing scale-up approach, with analogies in other process technologies, e.g., extrusion, kneading and milling. Recent work reports that process work can be effectively used to complement power draw analysis for more robust process control [49]. On the one hand, the advantage of specific energy is that it combines effects of net power, time and mass into a single group. On the other, the practical difficulty of the approach is determining the net power draw. The net power draw is that which is used to do productive work of agglomeration, i.e., to transform the product. Net power draw can be calculated as the difference between the gross power draw, which is easily measured, and the baseline power consumption. As a first approximation, the baseline can be measured by running the empty mixer. However, there are typically additional parts of the gross power consumption that are not directly related to the productive work of granulation. Examples include product fluidization, mixing, conveying, and/or drag caused by build up of product on mixer walls and/or impeller tools [50,51]. These effects may change from batch to batch, within a batch or during a continuous run and hence it can be difficult to pin down a constant value for the power draw baseline. Nevertheless, the specific energy approach offers some advantages. If care is taken to measure baseline power consumption, the resulting net energy can be shown to be a useful parameter for scale-up, especially in an agglomeration process that is driven by coalescence. With the coalescence mechanism, smaller agglomerates are fused together to make larger agglomerates by a mechanical consolidation process. If the energy of the process provides a force that is sufficient to overcome the plastic yield stress of the agglomerates, then they will deform at their contact points and coalesce to a larger size. This energy balance can be expressed as a dimensionless group (see x-axis, Fig. 14b). This group is similar to the Stokes' deformation number described later in the micro-scale section, except that the energy in current expression is measured directly from the power draw consumption. The yield stress of the wet agglomerate (i.e., a binder-powder composite) is a critical material property that lumps together the composite effects of raw material properties (binder and solids) as well as process and environmental factors, such as temperature and relative humidity. Yield stress is typically measured using a mechanical testing machine to collect load-displacement data on a small bed of granules (e.g., in a tablet die); these data can be analyzed by a number of different methods to determine a yield stress value [52-54]. Note that conventional load-displacement experiments are typically done at fairly low compression rates. While these data typically provide a useful and convenient basis for comparison, it should be noted that the in situ compression rates can be significantly higher in the granulation device, especially for direct impact consolidation. On the other hand, in situ shear interactions are generally more gradual. Measuring energy dissipation

Scale-Up of High-Shear Binder-Agglomeration Processes 100 __.

1~176 l

high [N, T, binder] o

o

lo:

-

In(d/d~ = f(x)

I~~lill~

10

"

! --

(a)

877

I ....

I ,

batch time

bind~ ,,

1

.......

x

' /1"" (3-'y

f(T,binder)l

t(

l

Fig. 14. Scaling of agglomerate growth by coalescence mechanism using specific energy vs. yield stress of the wet-mass material. (a) The data in represent various binder loading levels, operating temperatures (7-) and operating speeds (N) in a horizontal-axis ploughshare mixer. The batches are run for various batch times and then characterized for size growth, where the geometric mean size on a mass basis (d) is compared to the initial mean size (do). (b) When rescaled as specific energy (E/M) relative to yield stress (O-y),the data collapse to a master growth curve.

and deformation behavior at higher strain rates is a more difficult endeavor. Results of such experiments highlight the importance of viscous limitations in the kinetics of binder redistribution at high consolidation rates [55].

3.3. Swept volume Relative swept volume can be used to compare different mixing equipment designs and size scales [56]. It considers the volume of product swept away by the impeller of mixing blade in a given period of time, combining the affects of product fill level, impeller speed and impeller design. This approach is valid as long as there is good mixing (i.e., powder flow) throughout the filled volume of the mixer. The idea of swept volume analysis can be extended using a modeling approach to consider the probability, frequency and distribution of interactions between the active mixing elements (tools) and the product. Ideally, one seeks to have a tight distribution of interaction frequency such that transformations are uniform across the whole product. This approach can be useful in estimating relative impact velocities between product and active mixing elements or between a moving product and vessel wall. The velocity of impact and frequency thereof can be used as a way to scale physical transformations such as coalescence (growth) and consolidation (densification). As such, this approach can link equipment parameters and micro-scale analyses of product transformations. Once again, the key to completing this link is an understanding of the constitutive properties of the wet-mass mixture.

878

P. Mort powder feed

charging shovels

binder

. ~ - ~ CFD Model Section

mixing tools

pin tools and shovels V .....

I T product exit

Approach: ~ Measureor estimate residence time, RTD [CFD model used here]; ~ Use geometry (tool design), shaft speed and fluidization (Fr#) to estimate product / tool interactions (i.e., swept volume). I

virtual particle injection Fig. 15. Model of product-tool interactions in a continuous high-shear mixer-agglomerator: the RTD is predicted based on the distribution of trajectory paths of particles added to the mixer in the coalescence section. The particle trajectories depend on the CFD solution of airflow in the mixer plus direct collisions with mixing tools.

An example of a swept-volume approach is presented for a continuous highshear mixer-agglomerator (Fig. 15). In this case, the shaft is running at a high speed, giving rise to an annular product flow (i.e., a high Froude number). The interaction zone is primarily at the tips of the tools (i.e., impact) or in the highshear zone between the tool ends and the wall of the mixer. One can consider the swept volume in terms of the probability of interaction between the product and the mixing element per axis rotation. Using a computational fluid dynamics (CFD) model to estimate the residence time distribution (RTD) is helpful in that it allows the process developer to do preliminary virtual experiments on tool design, tool configuration, operation speed, etc. Integrating this over the predicted RTD gives the net interaction in the process. As in the case of the specific energy discussion, the net interaction of shear and impact can be quantified using a force or energy balance to predict constitutive transformations in the process. The modeling approach can help to improve the efficiency of the scale-up process and minimize the need for costly full-scale experimentation. Another approach to quantify swept volume interactions in a batch mixer is experimental particle tracking to map out a distribution of interaction over the course of an agglomeration process [57]. Flow patterns in the mixer will typically change as fine starting powder is transformed into moist granules, and the

Scale-Up of High-Shear Binder-Agglomeration Processes

879

patterns of stress transmission and fluidization can change significantly. Thus, it is essential to consider swept volume in the context of the powder flow, i.e., the powder's reaction to "being swept", and how this may change during the course of the granulation residence time. In regards to cohesive fine powder flow, problems with the swept-volume approach can arise in the scale-up of vertical axis batch mixers where "phase separation" in the flow of the fine powder is often observed in scaling up to larger volume mixers. In this case, some of the powder (on the bottom layer of a vertical granulator) is actively swept by the impeller element while the upper layer is in a dead zone with little mass exchange between the layers (Fig. 18a). This can be especially problematic when one considers that the binder is typically added to the top (unmixed) portion [16]. A more detailed analysis is given in the following section.

3.4. Stress and flow fields The physical quantification of granular stress and flow fields is an emerging area of study, encompassing theoretical, simulation-based and experimental efforts. While this work is in its nascent stages, the application of continuum powder mechanics and granular dynamics to describe flow and stress fields within granulation unit operations may provide useful insight for scale-up, equipment design and process control. In the interest of furthering progress in this area, this section presents a hypothetical framework for analysis of flow regimes in mixer granulators followed by two examples: (1) a cohesive powder mechanics approach to the analysis of scale limitations in a mixer with gravitational flows; and (2) a continuum analysis of centripetal flow patterns in vertical axis high-shear granulators. A tentative regime map of granular flow (Fig. 16) is proposed as a way to elucidate the state of flow in a mixer-granulator [58,59]. Three regimes are identified depending on a dimensionless shear rate (7*) which is the shear rate (7) made dimensionless using a characteristic particle size (dp) and gravitational acceleration (g) [60]. In dry granular flows, the shear rate is calculated based on a particle velocity (Up) and a characteristic dimension such as the particle size (dp) or a relatively narrow shear-band of particles (i.e., 6-10 particle diameters). In a mixer-granulator, particle velocity is often scaled using the impeller tip speed (U~), even though it may be only a fraction thereof. In a cohesive binder-powder mixture (i.e., a wet-mass), the characteristic dimension for the relaxation of shear may be significantly larger than in dry flows. In Fig. 16, physical phenomena that are characteristic of each flow regime are shown at various scales of scrutiny, ranging from continuum approximations to cluster interactions and single particle interactions. The following examples focus

880

P. Mort

k!!); J

continuum I: ~: f ( ~ t )

1: - 'itn

Domain

~

interactions (coherence length scale) Particle

packing contacts

oJ

0

GranularTemp. (gas continuum)

Fluid-like continuum (N.S. analogy)

Frictional

1: _ ~,2

n
Spatial and temporal distribution of coherence, stress chains

Transient clusters?

Combined interaction (frictional/rolling/ collisional), multiple contacts

Binary collisions

0.2

3

Dimensionless shear rate,

~ _ ~,~dpg

>>

Fig. 16. A schematic representation of different regimes in powder and granular flows, following Tardos et al., where the flow regime depends on a gravity-based dimensionless shear rate [58,60]. Regimes include: (i) slow-frictional or quasi-static; (ii) intermediate, fluid-like or dense-inertial; (iii) free collisional or granular temperature regime. on the continuum scale. To develop scaling criteria for particle attributes, much more work needs to be done to link continuum models with micro-scale phenomena. In addition, please note the boundaries on both sides of the intermediate regime are not as clear-cut as shown in the figure, and much more work is needed before these boundaries are better defined.

3.4.1. Granulation under gravitational flow In some granulation equipment, bulk flow of the material is driven by gravity, for example, drum-granulators, V-blenders and other tumbling blenders. While the powder is typically moving at the point where binder is dispersed into the powder, there are periodic stops and starts in the bulk flow. In moving from the static to the flowing condition, the material must pass through a stage of incipient flow in the slow-frictional regime, i.e., the LHS boundary of the Slow-frictional regime (Fig. 16i). While there is a significant body of work dealing the use of shear cells to measure and analyze incipient flow behavior for application in hopper and bin design [61,62], there has been relatively little attempt to apply these methods and analyses to the scale-up of binder-granulation processes. This hypothetical example considers the application of continuum powder mechanics to scale-up of a formulation over a scaled-up series of granulation equipment. The theory includes the material properties (i.e., flow function) of the in situ wet-mass granulate as well as the features of the mixer design (geometry) and mixer-product interactions (wall friction) that are described in a hypothetical flow factor.

Scale-Up of High-Shear Binder-Agglomeration Processes

881

Many powders and granular materials exhibit downward curving flow functions over the range of relevant pressures in bin flow - i n this case, there is no "upper limit" to the bin design problem, only a lower limit for the bin opening. On the other hand, it should be noted that some materials exhibit upward curving flow functions, as illustrated by Jenike [61]. In the upward curving case, there is an upper limit to the bin diameter, above which whole bulk mass of material in the hopper is in a no-flow condition. An example of an upward-curving flow function for a wetgranular material is contrasted with that of a free-flowing dried granule in Fig. 17, where the unconfined failure stress (fc) is plotted as a function of the principal consolidation stress (a~). The unconfined failure stress corresponds to the onset of incipient bulk flow under gravity. While there is little published information on flow functions of wet-mass agglomerates, it is likely that a significant proportion of wet-mass granular materials may exhibit upward-curving flow functions, especially at higher wet-binder concentration. The upward curving flow function is characteristic of plastic materials that may significantly increase in strength as they are compressed. A practitioner of granulation might compare this to the familiar "squeeze test" in which the wet granulate is squeezed by hand to form a "ball" and the processability of the product is judged based on how easily the ball crumbles. When the material gains significant strength with compression, there may be difficulty in scaling up,

[ ~ f

12 10

Dried agglomerates

non-

nowin

cohesive

8 ~

I ~

/

/ Q'

f

. i / ;f

6

~ O - ~ Wet-mass agglomerates

cohesive

4

/ [~

J

j

.

t

--

--

Mixer Flow Factor

(hypothetical)

f

A

Stress limit (A), minimum discharge opening

[]

Stress limit (B), maximum scale-up

easy flow

f free flow ~

0

"

'

-

-

T

v

~

-

5

-

"~'~

---"

-

l0 (3"1

~"

15

,

20

,

I

25

(kPa)

Fig. 17. Flow functions for wet (ex-granulator) and post-dried granulations along with a hypothetical flow factor for the mixer, plotted at the boundary of the cohesive and verycohesive regions. Point (A)is the lower intersection of the wet-granulate flow function and the flow factor- it defines the minimum opening required to discharge the wet mass. At point (B), the upward-curving flow function crosses back over into the no-flow condition this represents the hypothetical maximum mixer size limit for scale-up of the wet-mass formulation.

882

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especially in mixer geometries where the principal consolidation stress increases with the process scale. Crossing into a no-flow condition in a larger scale mixer (e.g., Fig. 17B) may cause build-up in the mixer and an increased incidence of oversize product. The hypothetical flow factor for a mixer granulator is analogous to that for a bin, except that contributing factors are dynamic in the mixer. For example, wall angles constantly change with a rotation (e.g., in a V-blender) or with the angle of rotation in a drum. The wall friction in a mixer-granulator increased as binder and wet-mass material smears and/or accumulates on walls or tool surfaces. While it may be unwieldy to calculate instantaneous, localized flow factors and integrate over the full mixer, it may be useful to consider a critical flow factor at the point in the process that is most prone to product smearing or build-up due to a potential no-flow condition.

3.4.2. Granulation with centripetal flows On scale-up, it is advantageous to maintain similar patterns of granular flow and inter-granular stress. This is especially relevant in high shear mixer-granulators where inter-particle stress is critical to micro-scale transformations including coalescence, consolidation and breakage. In a collisional flow, the stress depends primarily on the collision velocity, which scales with impeller tip speed. In a more dense flow, the collisional impact of a mixing blade within a slower-moving wetmass is relevant, along with the contact or consolidation time and boundary conditions, especially in compressive flows. In either case, the magnitude of fluctuations in the flow and stress fields may be even more critical to the microscale transformations, and much work remains to be done in this area. In the current analysis, however, we consider flow regimes broadly based only on continuum averages of flow fields. A regime analysis of granular flow (Fig. 16) is helpful to elucidate the state of flow in a mixer-granulator. Empirically, many practitioners observe an operational "sweet spot", corresponding to a stable or resonant flow condition in the mixer. In the current analysis, we hypothesize that this stable flow falls within the "fluid-like continuum" or intermediate flow regime (Fig. 16ii). For example, in a vertical-axis granulator, a material in this flow pattern may be observed to follow a spiral "roping" flow, i.e., a toroidal flow with a helical spin, where the entire batch of material is uniformly participating in the flow field (Fig. 18b). In some cases, this type of flow may induce an audible resonance or "ringing" in the mixer. This type of flow provides a relatively uniform stress field throughout the product mixture and may result in a product with a narrow distribution of granular attributes (a narrow particle size distribution, uniform particle porosity, compositional homogeneity, etc.). Detailed simulations of centripetal flows further elucidate the shear gradients in such flows [63].

Scale-Up of High-Shear Binder-Agglomeration Processes

......

~'~"~!

.......

i"

..........

Impeler

(a)

883

(b)

Fig. 18. A vertical section of a flow patterns in a vertical-axis mixer-granulator. In case (a), the shear stress from the impeller decays over a short distance (5) relative to the mixer scale (R), net, the flow above the impeller may remain in frictional regime (i) even though the flow in volume swept by the impeller may be highly agitated or collisional (iii). In case (b), the shear stress is substantially transmitted into the granular mass, resulting in a spiral flow pattern (ii).

To place the centripetal spiral flow on the regime map, we use a modified the definition of the dimensionless shear rate. For mixers operating at high particle Froude number, i.e., in substantial excess of unity, it is relevant to use centripetal acceleration instead of gravity. Further, we notice that in a binder-granulation process, the shear-induced flow may extend substantially across the ring-width of the spiral flow. As such, the characteristic length scale (5) used to calculate the shear rate may be significantly larger that the particle size (dp). In the presence of cohesive binders, 5 may even approach the full width of the spiral flow. Lastly, the shear rate should reflect the actual granular particle velocity rather than the impeller tip speed. Combining these adjustments, one can re-write the dimensionless shear rate for a vertical-axis mixer-granulator in terms of two other dimensionless quantities: K1 is the ratio of the average particle velocity (Up) to the impeller tip velocity (U i); and K2 the ratio of the shear stress decay length scale (5) relative to the mixer radius (R) (equations (13-15)).

Op 2K1U/ 4KI~R ~-5/2- 5 = ~ K2 - R

5

~* - ~ V/_~ r - ~ -2K~ ~

(131

(14)

(15)

K1 is the ratio of the average tangential particle velocity relative to the impeller tip speed. It represents the normal transfer of momentum from the impeller to the granular material, i.e., in the direction tangential to the impeller rotation. The value of K~ may depend on the design of the impeller and its angular velocity, the

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constitutive properties of the material and the fill level. Two sorts of analyses have been published for vertical axis machines: (1) bulk flow at the free surface, using high-speed image processing [17,63,64]; and (2) tracer particle tracking using positron emission particle tracking (PEPT) to elucidate distributions of particle translation and velocity based on tracking individual particles within the bulk flow [57,65,66]. The former shows have shown typical values for K~ on the order of ~10-15% with pharmaceutical-grade excipient powders in an industrial mixer granulator while the latter, using mm-scale glass beads in a customized flat-blade mixer, shows a skewed velocity distribution with the a well-defined mode at ~60% [65]. PEPT studies in a horizontal axis mixer at moderate Froude numbers show K~ values ranging from 2 to 25% for an agglomeration system of PEG solution binder and calcite powder, depending on the position in the mixer and the amount of binder addition [57]. Note that the instantaneous velocity of a particle may fluctuate substantially from the mean particle velocity. Indeed, the magnitude of the velocity and stress fluctuations may be more relevant to micro-scale transformations such as coalescence, consolidation and breakage. K2 is the ratio of the shear stress decay length scale relative to the mixer scale; it also depends on the constitutive properties of the powder or granular material as well as the fill level and mixer scale. For a wet-mass granulation in a lab-scale granulator, one might estimate typical values of K2 in the range of ~10%. On the other hand, a larger-scale granulator will tend to see smaller values of K2 because ~ does not necessarily scale with the mixer radius. This is especially critical at the start of a batch as binder is initially added to the dry powder. In a dry powder, shear stress decays substantially on the order of a few particle (or cohesive cluster) diameters and ~ may be very small compared to R. Indeed, scaling-up to a larger mixer diameter may cause flow bifurcation (Fig. 18a) [16]. It is only after the binder is distributed throughout the powder mass that ~ increases due to bulk cohesion and the intermediate flow pattern is achieved. Using the modified version of the dimensionless shear rate (equation (15)), the flow behavior of powder or granules in the mixer-granulator can be mapped as a function of the tangential and shear flow components, K~ and K2 (Fig. 19). The intermediate or "fluid-like" regime is shown in the middle of the diagram (Region ii). At higher K~ and lower K2 values, the flow may become more excited and collisional (Region iii). On the other hand, lower relative particle velocities combined with more cohesive interactions may result in slow-frictional flow (Region i). Generally it is preferable to operate mixer granulators in a more uniform flow and stress field (Region ii). It is fortunate that this region appears to be large compared to the range of reasonable parameter values on the diagram. In this example of the centripetal mixer-granulator, a key result of the analysis is that the angular velocity (~) drops out of the dimensionless shear rate. In other words, the flow regime hypothesis predicts that is not necessary to maintain the exact value of the Froude Number on scale-up, only that the Froude number is

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885

5,*=2 ~i! . . . . .i.9. .

II

(iii

10%

c-.l

1% 1%

10%

100%

Kj =UP~ui Fig. 19. Hypothetical flow regime map for a mixer-granulator operating at high Froude Number. The dimensionless shear rate, defined according to equation (15), is used to define flow regions: (i) frictional, ~,*<0.2; (ii) intermediate, fluid-like; and (iii) rapid collisional, 7*> 3. K1 represents the transfer of tangential momentum from the impeller to the powder or granular material; K2 represents momentum transfer by shear along the axial direction. high enough to assure that centripetal acceleration exceeds gravity. This means that the impeller tip speed is the more relevant parameter for scale-up, as it relates directly to the inter-particle stress in the bed. This theoretical result is consistent with many experimental and empirical findings where tip speed (or a tip-speed favored compromise with Froude number) is used as a basis for scaleup for high-shear mixer granulators.

3.5. Delivery number The delivery number is a measurement of throughput capacity in a continuous agglomeration system (equation (16)). It relates the size of the mixer (D) to the speed of the mixing blades (N) and the volumetric throughput rate of the product (Q).

Q

delivery # - - -

ND 3

(16)

On scaling up, the delivery number can be used as starting point calculation of the physical throughput capacity in a continuous mixer-agglomerator system; however, similarity of the delivery number does not guarantee similarity of other parameters which may have more important effects on the transformations occurring in the process. For this reason, it is recommended to consider details of

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the swept volume interactions along with the delivery number, specifically in regards to potential differences in the direct interaction between the mixing tools and the product (i.e., impact) vs. shear interactions where the product is not directly impinging on the tools.

3.6. Spray flux The spray flux is related to the dispersion of an atomized binder in the powder, and it is related to the homogeneity of the product on a micro-scale. A dimensionless spray flux for drop-templated nucleation is defined as a measure of droplet density on the surface of a moving powder bed (equation (17)), expressed in terms of the volumetric liquid spray rate (V'), average droplet size (dd) and the speed of the powder bed surface traversing the spray zone (A') [19,67]. spray flux

=

~Ja =

3V' 2A'dd

(17)

Other aspects of the spray (e.g., conventional spray flux, number of droplets/ particle) are relevant to dispersion and coating. Additional discussion of the spray flux, nucleation and product homogeneity is provided in the micro-scale section. There are many advantages that a binderspray system can afford to a granulation process; however, there can be difficulties both in scaling-up and in scaling-down equipment on the basis of the dimensionless spray flux [64]. From an equipment scale-up perspective, it may be necessary, from a microscale perspective, to maintain the size of the droplet diameter (dd). And the range of adjustment in the volumetric liquid flow rate (V') may be narrow based on formulation and throughput rate requirements. Therefore, to maintain similarity of the spray flux, one is required to maintain the flux of powder traversing the spray zone (A'). In most industrial mixer-granulators, the bed depth increases on scaleup, making the above requirement unfeasible unless the powder in the spray zone can be actively refreshed by a more rapid turnover of the powder bed surface. To an extent, this latter approach can be achieved by increasing the level of fluidization of the powder in the spray zone, i.e., by operating at a higher Froude number; however, this may introduce other complications, e.g., by increasing consolidation or breakage. In this case, agitated fluid-bed mixers may be advantageous [10]. There are also practical limitations in scaling down a spray-on system. It may be desirable to scale down to the smallest practical size for development work. However, in a system that involves spray-nozzles, especially single-fluid atomizers, there is typically a minimum working distance for atomization to occur, i.e., for the breakup of the fluid sheet and/or ligaments to form discrete droplets.

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3.7. Process ancillaries In industrial installations, ancillary powder-handling infrastructure is also critical to scale-up. The stability of a continuous operation depends on the precision of feeders and flow controls. Conveying, handling and, in some cases, climate control of sensitive raw materials can be critical to processing. Care in conveying and handling of the finished product is important in preventing attrition or other degradation of the finished granular material. Transport of intermediate material between unit operations can be especially critical to process reliability. In scaling up continuous agglomeration processes from pilot to full scale, it is common to see an increase in the ratio of product/air flux in ancillary chutes, bucket elevators, classification screens, etc. On the pilot scale, the average product rate is intentionally low relative to the instantaneous handling capacity of chutes and other transport operations. On the other hand, the economic objective of the full-scale plant is to maximize the production rate relative to the equipment capacity. This can create issues for moist products in chutes and other conveying systems between unit operations. If the product/air ratio becomes too high, then the air-stream can become saturated and condensate will form on cooler surfaces, leading to product build-up and potential blockages. The analysis of instantaneous vs. mean rates is especially relevant to the sizing of recycle handling systems. In some cases, the instantaneous recycle in an agglomeration plant can be very substantial compared to the mean recycle rate. Instantaneous surges in recycle can clog conveyors, overload bucket elevators, etc. Design of product handling systems based on mean product rates can fail in cases of startup, shutdown or other process disturbance where the instantaneous rates may be substantially higher than the mean. The value of process control is amplified when considering opportunities for capital avoidance in handling systems. A more robust control strategy can minimize surges and reduce the need for over-sized handling equipment. This is a good example of how linkages between macro-scale process design and micro-scale analysis and control strategies for specific product attributes can be very cost effective.

4. MULTI-SCALE A P P R O A C H - LINKING MICRO- AND MACROSCALE A P P R O A C H E S The transformation approach provides an overall framework for considering how scale-up decisions on a macro-scale may influence micro-scale particle attributes. Conversely, if specific product attributes are known to be very important to the performance of a granular product, then the scale-up decisions can be focused on maintaining similarity of these specific attributes. Beyond this framework, however, the transformation approach does not give explicit linkages

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between the micro and macro scales. More recently, the linkage of micro and macro scales, i.e., in the form of a multi-scale approach, has evolved into the current state-of-the-art in granulation research. It may be convenient to develop meso-scale linkages using a collection of models (Fig. 20) [68]. Combining the micro and macro approach is important to achieve a practical scale-up and control strategy. The two approaches often overlap at a constitutive level (e.g., case 3 in Fig. 20), where the physical response of the raw materials to process energy and power is defined [24-27]. Given the degree of complexity posed by the agglomeration process (i.e., both powder and liquid material properties, where the distribution of the two change during the process), it may not be practical to attempt to model the full system in a purely fundamental way. On the other hand, an empirical or phenomenological understanding of the rheo-mechanical properties of the in situ wet-mass materials is very helpful in building models that link the micro and macro scales. For this reason, it is often convenient to define a meso-scale based on constitutive interactions in the agglomeration process. Another key area where multi-scale modeling may offer breakthroughs is in the understanding and manipulation of powder and granular flows in agitated mixer granulators. The flow of the material inside of the unit operation is a direct result

_Scale:

Particle production / handling:

Macro / system

Plant

Macro / Unit-op

Process equipment

Meso

Many particle constitutive relations

Micro

Single particle

Micro

Particle surface

Ah,

C)

~V

,)

Fig. 20. A multi-scale diagram for a particle production. Examples of models that span scales: (1) Optimize arrangements of unit-operations within a production system, e.g., a dynamic process model used to optimize the throughput and reliability of a continuous manufacturing process with recycle streams; (2) Visualization of flow patterns in process equipment and the interaction between product transformations and flow patterns; (3) Constitutive models linking equipment operating parameters with material properties to predict product transformations; (4) Design of micro-scale granular features to improve meso-scale constitutive behavior, for example, surface modification of granules for improved flow and dispersion; and (5) Design of granular structures based on simulation of desired performance attributes; for example, the use of coating layers with various mechanical properties to provide attrition-resistant granules.

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of the interaction between the mechanical mixing elements and the product in the mixer, as discussed in earlier sections: swept volume, stress and flow fields. The resultant flow patterns depend on the rheo-mechanical properties of the powder/ granules and the stress transmission therein. Inversely, the flow patterns can influence many of the transformations in the process, as the powder is converted to a granular form. As such, the characterization of transitional flows is a promising area of work that may help advance the subject of granulation scale-up. Progress is being made in both modeling and experimental investigation of transitional flow phenomena [39,57] as well as in sensors that can detect changes in flow patterns [69].

5. SUMMARY AND FORWARD LOOK This chapter is primarily focused on reviewing the considerable body of work that is relevant to scale up of binder agglomeration processes, much of which has been published over the past decade. Over this time has evolved the realization that binder granulation is both a sequential and interconnected set of complex sub-processes that can be categorized into binder wetting and spreading, granule growth and consolidation, and granule attrition and breakage. A more detailed progression of the product through these sub-process categories can be conveniently analyzed using the concept of transformations. Several key advances complement this view of agglomeration, including the analysis of flow patterns in mixer-granulators, the effect of spray flux on binder dispersion and granule nucleation, and the linkage of process parameters with material properties to develop controlling groups for product transformations. The linkage between mixer flow patterns and the deformation of wet-mass materials is especially apt for scaling of mechanically agitated mixer granulators [70].

5.1. Flow patterns in mixers On a macro-scale, there have been significant advancements in understanding flow patterns within granulation equipment and the importance of distributed flow patterns to critical transformations. Flow patterns are relevant to the binder dispersion, shear and impact interactions within the product. For batch processes, one often finds significant changes in the flow patterns inside of the mixer on scaling-up to a larger volume. An appreciation for the bulk flow patterns may affect the operating strategy relative to the introduction of a liquid binder. For example, a strategy to temporally separate the dispersion and growth transformations suggests that it may be more efficient to start the addition of binder in a more highly-fluidized mixer (e.g., following a Froude number scale-up), but then

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reduce the speed to a constant tip-speed basis as the saturation increases and the shear stress is more effectively transmitted through the bulk bed. Continuous processes offer the option to spatially separate flow-dependent transformations across multiple mixers or multiple zones in a mixer. Flow patterns in mixers are important for both of the following discussion points.

5.2. Binder spray flux On a micro-scale, the effect of spray flux on the nucleation of granules is an important concept for both scale-up and control applications. Maintaining a constant spray flux from small to large-scale process equipment is typically a challenge. A rigorous scale-up strategy based on dimensionless spray flux may compromise the economy of the larger scale. Given the economic objectives of scale-up, it is common to see an increase in the spray flux as material flow rates and/or batch sizes increase. Increasing the spray flux typically results in a broadening of distributed product characteristics, e.g., a broader agglomerate size distribution. The spray-flux concept underscores the balance between binder atomization (i.e., droplet size) and the location of the spray zone relative to the powder flow in the mixer. In a mechanical mixer, a well-mixed powder flow can be used to effectively compensate for a higher binder spray flux.

5.3. Linkage of process parameters with material properties In the case of mechanically agitated granulators, the development of controlling groups that link process parameters with material properties has been an important advancement. Balancing the force and energy acting on the wetted particles with wet-mass constitutive properties provides a more fundamental basis for understanding the importance of tip-speed as a primary scale-up parameter. In a mixer granulator, the motion of the impeller creates a distributed range of shear and collisional impacts within the product, where the maximum shear and impact events are related to the impeller tip-speed. These forces are linked directly to consolidation and coalescence of the wet-mass materials. Both average and maximum forces are relevant to product transformations, where the distribution of the applied stress and net energy may be significantly related to the flow patterns in the mixer. Both force and energy balances are applicable to the analysis. The force balance considers single shear or impact events. Energy balance can be applied to discrete deformation events as well as the cumulative energy obtained by integrating power draw over the RTD. While the latter approach is attractive

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because of the convenience of measuring power draw, challenges remain on how to partition the gross power consumption into net power associated with critical transformations vs. other power that is lost in the process. The material characteristics of the wet mass are the other part in the constitutive balance. Linking the applied forces (e.g., via tip speed of the mixer) with material properties (e.g., via binder loading and/or temperature) expands the palette of design options in scaling-up an agglomeration process. For example, an empirical understanding of how wet-mass material properties change with raw material or seasonal variations (e.g., alternate suppliers, lot to lot variation, temperature, humidity, etc.) can be used as a basis for specifying an adjustable range of process parameters that can be used to compensate for the material variations. Empirical characterization of lumped properties can be a useful way to quantifying parameters in controlling groups. For example, an apparent yield stress of a granule or wet-mass mixture can be a useful indicator of the constitutive response of the composite material. A yield stress measurement includes the lumped effects of raw material properties (powder and binder), the interaction of these properties in the mixture and the structure of the composite mixture. Another example of this practical, if not elegant, lumped-approach include the droplet penetration time measurement developed in conjunction with the investigation of binder spray-flux [8,17], which considers the effect of powder surface chemistry as well as the surface tension and the viscosity of the liquid binder. Another more recent example is the use of in situ sensor particles to measure the net physical effect over a distribution of shear and impact stresses within an agitated granular flow inside a mixer-granulator [29]. During scale-up, it may be advantageous to include process control features that enable product attribute adjustments by adjusting characteristics or properties of the raw material inputs. This approach requires a model that links fundamental material properties to a product transformation. For example, a process adjustment for binder viscosity has been used to control particle density according the Stokes criteria for consolidation [4]. More broadly speaking, however, the use of constitutive models based on fundamental raw material properties remains as a practical challenge for both scale up and control applications.

5.4. Batch and continuous systems Batch and continuous processes each have advantages and disadvantages. On the one hand, batch processes are best suited to small production quantities and/or when frequent product changeovers are required in a set of production equipment. While product changeovers and equipment cleanouts are never efficient usages of capital, cleanout is considerably simpler in a batch process

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vessels compared to cleanout of transport and recycle streams associated with continuous processes. Batch processing also provides a basis for mass balance closure between raw material inputs and the product assay. On the other, continuous processes are much more efficient for production of large product quantities, and offer increased capability for on-line process control. In addition, scaling-up the production rate by moving from a small-scale batch prototype system to a continuous production system with similar critical dimensions is typically more robust than scaling from small to large batch vessels because the pattern of flow within the similarly sized mixers can be more easily maintained.

5.5. Productive use of recycle The effect of recycle can be significant in a scale-up strategy. Continuous systems typically include integrated or downstream classifying steps. The center-cut product is consistently high in quality, and the outlying cuts (e.g., fines and oversize) can be recycled back to the granulation unit. The oversize material is usually reduced in size (e.g., by a grinder) before it is re-introduced to the granulator. The recycle stream can be very useful in stabilizing the granulation process, especially when recycle streams are metered back to the process in a controlled way (e.g., from a surge bin). A controlled recycle stream in a continuous operation can improve product quality and process control, e.g., by increasing product homogeneity, seeding growth and providing a means to implement feed-forward control strategies. Adding a fractional amount of recycled material in a batch process can also provide an operational advantage. Recycle material is typically coarser in size and has a higher bulk density than the raw materials which are often cohesive fine powders. In this case, the effect of the recycle can be to "seed" or ignite the bulk flow of powder inside the mixer, providing a more consistent pattern of powder flow during the binder addition stage of the process.

5.6. Models The development of population balance models has seen considerable academic progress over the past decade and there has been progress toward the formulation of models with growth kernels based on physical mechanisms [71]. The population balance has been applied to process simulators and to feed-forward control of continuous systems with recycle streams [72]. However, the practical use of such models for many scale-up applications remains on the technical frontier [73]. Recent work using multi-dimensional population balances is moving

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toward the capability to model multiple granule attributes [74]. Multivariate modeling promises to become a useful way to formalize knowledge of critical transformations as interdependent kernel functions, e.g., coalescence and breakage functions that are dynamically dependent on binder distribution (dispersion) and granule structure (consolidation) functions. Stochastic population balances and simulation methods are becoming attractive for multivariate analyses. Constitutive models can be used to describe physical transformations in terms of force or energy balances. The ability to quantify applied force or energy relative to material properties is vital to the utility of these models. For initial scale-up estimates, it may be sufficient to calculate applied energy based on tip speed of an impeller, and to use a simple lumped-property measurement (e.g., yield stress) as an estimate of the complex rheo-mechanical interactions in the wetmass material. Moving forward, more sophisticated modeling techniques (e.g., CFD, DEM, and quasi-continuum models) are anticipated to predict particle flow patterns, shear distributions and collision velocities for mixer-granulators of different scales.

6. CONCLUSION Scale-up is complicated by the many product transformations that may occur simultaneously in agglomeration processes. Although transformations may overlap and feedback among each other, they can be modeled discretely on a micro-level. Deeper understanding of discrete transformations lends insight to the fundamental mechanisms affecting the product attributes. Ideally, scale-up based on product attributes would maintain similarity across all transformations that effect key product attributes. However, when it is not possible to maintain similarity across all transformations within a given unit operation, it may be advisable to separate the transformations, for example, by staged processing in a batch unit or adding additional unit operations for specific transformations in a continuous process. Transformations depend on interactions between the process and material properties. Scale-up is often complicated because process parameters may effect more than one transformation. Additional complexity is introduced by the requirement to consider material properties in all relevant states, including intermediate binder-powder mixtures and local temperature and humidity conditions. It is often the case that the relevant material properties are based on a mixture of powder and binder that is changing depending on the degree of saturation. To move ahead, we need to continue to link micro-scale analysis with key product transformations. Sorting out the complexities of in situ material property transformations requires continued progress in on-line monitoring of process-parameters and material properties. This expanded capability of materials characterization is important for both micro-scale and macro-scale approaches.

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ACKNOWLEDGMENTS I would like to acknowledge my extensive collaboration with Prof. Gabriel Tardos as well at the fruitful discussions on granulation and multi-scale modeling projects supported by the International Fine Particle Research Institute (IFPRI), especially Prof. Peter York, Prof. Jim Litster and Dr. Karen Hapgood. In addition, I would like to acknowledge my colleagues at the Procter & Gamble Co., especially Dr. Hasan Eroglu for his contributions on CFD modeling, Larry Genskow, George Kaminsky, Wayne Beimesch and Scott Capeci for their insight on the efficient and practical scale-up of industrial granulation processes.

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[4] P. Mort, S. Capeci, J. Holder, Powder Technol. 117 (2001) 173-176. [5] B.J. Ennis, J.D. Litster, Size reduction and size enlargement, in: D. Green, (Ed.), Perry's Chemical Engineer's Handbook, McGraw-Hill,, 1997, Section 20, pp.56-89. [6] W. Pietsch, Agglomeration Processes: Phenomena, Technologies, Equipment, Wiley-VCH, Weinheim, 2002. [7] K.V.S. Sastry, D.W. Fuerstenau, Powder Technol. 7 (1973) 97-105. [8] S.M. Iveson, J.D. Litster, K. Hapgood, B.J. Ennis, Powder Technol. 117 (2001) 3-39. [9] T. Schaefer, C. Mathiesen, Int. J. Pharm. 139 (1996) 125. [10] S. Watano, Y. Sato, K. Miyanami, T. Murakami, Chem. Pharm. Bull. 43 (7) (1995) 1212-1220. [11] P.C. Knight, T. Instone, J.M.K. Pearson, M.J. Hounslow, Powder Technol. 97 (1998) 246-257. [12] D.M. Newitt, J.M. Conway-Jones, Trans. Inst. Chem. Eng. 36 (1958) 422-441. [13] H.G. Kristensen, Particle Agglomeration, in: D. Ganderton, T. Jones, J. McGinty (eds), Advances in Pharmaceutical Sciences, Academic Press, London, 1995. [14] S.H. Schaafsma, P. Vonk, P. Segers, N.W.F. Kossen, Powder Technol. 97 (1998) 183-190. [15] T. Schaefer, C. Mathiesen, Int. J. Pharm. 139 (1996) 125-138. [16] J.D. Litster, K.P. Hapgood, J.N. Michaels, A. Sims, M. Roberts, S.K. Kaminini, Powder Technol. 124 (2002) 272-280. [17] K.P. Hapgood, Nucleation and Binder Dispersion in Wet Granulation, The University of Queensland, Ph.D. Thesis, 2000. [18] S.H. Schaafsma, P. Vonk, N.W.F. Kossen, Int. J. Pharm. 193 (2000) 175-187. [19] K.P. Hapgood, J.D. Litster, E.T. White, P. Mort, D.G. Jones, Powder Technol. 141 (2004) 20-30. [20] B.J. Ennis, G.I. Tardos, R. Pfeffer, Powder Technol. 65 (1991) 257-272. [21] P. Mort, R.E. Riman, Kona 12 (1994) 111-117. [22] N. Ouchiyama, T. Tanaka, I&EC Process Des. Dev. 14 (1975) 286-289. [23] H.G. Kristensen, P. Holm, T. Schaefer, Powder Technol. 43 (1985) 225. [24] S.M. Iveson, J.D. Litster, B.J. Ennis, Powder Technol. 88 (1996) 15. [25] S.M. Iveson, J.D. Litster, AIChE J. 44 (7) (1998) 1510-1518. [26] S.M. Iveson, N.W. Page, J.D. Litster, Powder Technol. 130 (2003) 97-101. [27] G.I. Tardos, M. Kahn, P. Mort, Powder Technol. 94 (1997) 245-258.

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