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Linking manufacturing strategy to the design of a customized hybrid production control system
Computer Integrated Manufacturing Systems 1994 7(2) 134-141
Linking manufacturing strategy to the design of a customized hybrid production control system A K BHATTACHARYA and J L COLEMAN
Abstract: In recent years, increasing attention has been paid to manufacturing strategy. Considerable work has been done in defining market-driven competitive priorities as part of manufacturing strategy and linking them to 'structural' decision areas. Linkage to 'infrastructural' decision areas like Production Control Systems (PCS) is found to be inadequately researched. This paper presents a three-staged approach which links manufacturing strategy to PCS. First, the PCS environment is described using three dimensions of: competitive priorities, product complexity and process complexity. The environment defined in the first stage is then used to select the appropriate level of multi-level 'decision variables' which fully define a PCS in Stage 2. In the third stage, the set of selected levels for each of the decision variables, which form the guidelines for detailed PCS design, are then integrated into a hybrid PCS customised to the manufacturing strategy of the firm. This approach to PCS design was then tested at several firms and was found to be useful for identifying the inconsistencies between existing PCS and the manufacturing environment and strategy. Keywords: manufacturing strategy, production control system
-n recent years, increasing attention has been paid to manufacturing strategy as a means to attain ,competitive advantage. The focus has been twopronged - first to understand the contents of a successful manufacturing strategy; and second, to find out the best or the most effective way to evolve the strategy. What has been under-represented both in theory and practice is the question of implementation. Mathews and Foo ~, in a study of the subject, observed that 'because one cannot assume that all planned strategies are implemented well, implementation research becomes important to strategy evaluation and performance'. Thus there is a need for more research linking
l
Warwick ManufacturingGroup, Universityof Warwick, Warwick, UK
134 0951-5240/94/02/0134--08(~ 1994 Butterworth-HeinemannLtd
strategic decisions to operational decision making. In this paper, we first look at the need for a theoretical construct which would help in implementing the manufacturing strategy decisions in the design and procurement of the production control systems of a firm. We present such a construct, and make some conjectures on the linkage between strategy and PCS selection. P h i l o s o p h i c a l b a c k g r o u n d to m a n u f a c t u r i n g strategy
The philosophical foundation of manufacturing strategy has often been traced to Skinner's 2 seminal work: 1. 'Manufacturing: The missing link in corporate strategy' 2. 'The focused factory', first published in 1969 and 1974, respectively. In them, Skinner first mooted the twin concepts of 'focus' and 'consistency', which still form the basis of most research in manufacturing strategy. However, the phenomenal success of the 'Japanese' manufacturing strategies, and also the advent of flexible manufacturing systems, have lead to the broadening the definition of 'focus' to enable multiple manufacturing objectives to be achieved simultaneously3-7. But there is no doubt on the need to align the manufacturing objectives/task/ strategy with process/technologies and operating systems/policies. C u r r e n t research in m a n u f a c t u r i n g strategy
The two broad areas of research currently much in vogue can be classified as 'content' and 'process' models of manufacturing strategy. Many authors have
Linking manufacturing strategy to the design o f a PCS: A K Bhattacharya and J L Coleman
defined manufacturing strategy 8-11. Ward et al. 12 capture the content of manufacturing strategy in two broad categories: 1. Decision areas that are of long term importance in the manufacturing function, (which have been categorized into 'structural' and 'infrastructural' decision areas by most authors). 2. Competitive priorities based on corporate and/or business unit goals (or what Hill -~ calls the OWC/ OQC). From the survey of literature on manufacturing strategy, we conclude that considerable work has been done in defining competitive priorities and also their linkage to the 'structural' decision areas, i.e. how to achieve consistency between strategy and manufacturing structure. But the linkage to 'infrastructural' decision areas or operating systems and policies has been inadequately researched.
Production control systems The objective of any control system is to ensure that for the process or activity under control, the desired behaviour is attained. Production control systems attempt to control the manufacturing plant. This is viewed as a hierarchical process with three distinct phases or activities. Vollmann et al. 13 call them the front end (production planning and demand management), engine (detailed material and capacity planning) and rear end (shop floor systems). Traditionally, the implementation of a PCS has been seen as selecting the appropriate system like MRP, JIT/ Kanban, Reorder-point, etc. based on the needs of process/technology and internally generated performance variables. Most of the research has been limited to the sensitivity of a particular system to changes in operating parameters 14-16, or comparative study of different systems and identification of application conditions14.17 19.
Design o f production control systems Some authors 2'17"2° have mentioned the need to 'design' a PCS rather than select one of the standard systems. They and others, like Kochhar et al. 2~, have identified some of the factors or key characteristics that affect the design. They also identified some of the 'design variables' or decisions like inventory levels, produce to stock or order, level of monitoring/ expediting, etc., which form the framework for PCS design. Berry and Hill 22 appear to be one of the few authors to have looked in detail at this linkage between the influencing factors and the PCS decision variables. They identify three PCS variables of make-to-stock, make-to-order or assemble-to-order, and link these variables to the requirements of order winning/order qualifying criteria and manufacturing process in order to achieve consistency.
However, what we find is a lack of research in systematically identifying the factors that influence the decisions to be made when designing a PCS and putting them in a usable framework or a model. Secondly, we also find that few authors have systematically identified all the decision variables which can then form the guidelines for detailed PCS design and a relationship between influencing factors and these design variables. In this paper, we present an approach which we hope provides the missing links in linking manufacturing strategy to the design of production control systems an 'infrastructural' decision area.
Proposed approach to PCS design We propose that a customized PCS can be designed by following a three-stage approach, as shown in Figure 1. The first stage consists of using a theoretical construct or model which fully defines the environment in which the PCS will operate by incorporating the influencing factors. In the second stage, PCS is viewed as a set of 'multi-level decision variables'. By concentrating on each decision variable and selecting the appropriate level to match the needs of the environment defined in stage 1 (rather than looking to select a system such as MRP, JIT or OPT), we get the guidelines or framework for developing a customized PCS. In the third stage, these chosen set of 'levels' for each of the decision variables are integrated to constitute the customised PCS. We think such an approach is especially desirable, as it appears that no single PCS model meets the requirements of today's environment, and an increasing need is felt for 'hybrid' PCS solutions customized to the needs of each firm. The objectives of such an approach are to achieve: 1. Focus - which is redefined as the environment constituting the set of factors that affect the design and operation of the PCS, and help to differentiate between the various PCSs which are desirable for either different product groups, or between current and future requirements for the same product group, or between different areas of processing for the same product group. 2. External consistency - which is redefined as consistency between the individual design decisions of the PCS and the focused environment of the first objective. 3. Internal consistency - which is redefined as consistency between the individual elements of the PCS.
Formulate description of PCS environment using theoretical construct STAGE 1
i
Use environment ] model to choose ~ 'level' within each PCS decision variable STAGE 2
r
I Integrate selected set of 'levels' to design a customised Production Control System STAGE 3
Figure 1. Proposed approach for design of customized hybrid PCS Computer Integrated Manufacturing Systems Volume 7 Number 2
135
Linking manufacturing strategy to the design of a PCS: A K Bhattacharya and J L Coleman Stage 1: Theoretical construct o f PCS environment
Table 1. Factors which influence PCS design
Factors which affect PCS design can be divided into three categories:
Dimension 1: Market- Manufacturing
• Manufacturing strategy (which is represented by market driven competitive criteria) • Process • Product.
Dimension 2: Product Complexity
It is proposed that different combinations of these three dimensions of market, product and process characteristics will warrant a particular configuration of PCS decison variables. But these three factors are not independent. In the long run, we must remember that the product and process variables are themselves influenced by manufacturing strategy/task. The market-manufacturing strategy dimension has two components: competitive criteria, as developed by the Warwick Manufacturing Group (given below), which would be classified using Hill's 5 classification of order winning, order qualifying and losing sensitive criteria. The seven competitive criteria are: • • • • • • •
Price/cost Product quality Delivery lead time Delivery reliability Delivery flexibility/volume flexibility Design flexibility Enquiry lead time.
The other component of this dimension is what we call market complexity, which depends upon demand uncertainty, demand stability and volumes per period. Higher uncertainty, instability or low volume per period leads to higher market complexity, and vice versa. The second dimension of product complexity can be viewed in three levels of high, medium and low complexity. If there are large number of products with divergent requirements/options and/or a greater number of bill of materials levels, the product will be considered a complex one. If there are a few homogeneous product lines, the product would be considered less complex. Similarly, the third dimension of process complexity is also viewed in three levels. A highly complex process would be using a number of process technologies in a batch type or job shop environment, utilizing concepts like FMSs. The low complexity process environment would be flow shops or large batch processing with few, less complex and similar technologies, and having more of a rigid product routing, unlike more complex environment which would have flexible routing. These influencing factors are shown in Table 1. One can picture this theoretical construct as a kind of tetrahedron, as shown in Figure 2. The base gives the two dimensions of product and process complexity, and the height denotes the combination of market driven
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Computer Integrated Manufacturing Systems Volume 7 Number 2
• Competitive Criteria: Set of OWC/OQC • Complexity: Demand uncertainty Demand stability Volume per period BOM Level Option Offered Degree of standardization Dimension 3: Process Complexity
Routings Process technologies used Level of AMT
criteria, which gives rise the manufacturing strategy competitive criteria and market complexity. We draw an important conclusion from this construct. The environment of the PCS is governed by the market-manufacturing dimension and the complexity (or the lack of it) of product and process. Since, ultimately, a PCS has to be consistent with the market-manufacturing dimension, it can look on product and process dimensions as constraints in the short-term. This implies that product and process dimensions dictate what kind of systems are possible, and not what is desirable when designing the system. In fact, as Ward et al. 23 had pointed out, PCS can sometimes be used to correct misalignments between manufacturing strategy and product/process. Stage 2: Decision variables in a production control system
In this stage we identify the decision variables which form the framework of any PCS, and discuss their linkage to the three dimensions of Stage 1. We have viewed a PCS as consisting of the three phases of production planning, detailed material planning and shop floor controls. Phase 1: Production planning, demand management and master production schedule
1. The first question to be asked is how should different product groups be handled? Should they be planned for and controlled separately, or should the same PCS design handle all the product groups? Different manufacturing tasks should ideally be handled by different hybrid PCS. 2. The policy of whether to produce to stock, assemble to order or produce to order has to be decided upon. This would be dependent upon whether the manufacturing lead time is less or more than the customer lead time, the type of products and distribution system (e.g. consumer products distributed through large warehouses are normally fed through stocks), whether customer service requirements can be met
Linking manufacturing strategy to the design of a PCS: A K Bhattacharya and J L Coleman
/
Market Manufacturing
/
H : High M : Medium L : Low
.! C L
Strategy and
H
Complexity B
L H
M/
A
Process
Complexity
L L
M
H
> Product Complexity
Figure 2. Stage 1: Classification of PCS environment. X: Manufacturing strategy A/complexity low, medium product & low process complexity; Y: Manufacturing strategy C/complexity high, high product and process complexity
only through stocks, etc. Make to order is suited to custom-built products, large variety products or higher process complexity, while a standard, predetermined and narrow range of products is better suited for make to stock. 3. The firm has to decide the accuracy of forecasts required. Higher accuracy requires more investment in forecasting, and would be desirable for a make to stock policy, where high customer service and delivery reliability are essential, to reduce excess rescheduling, and also for a higher level of market complexity. 4. Should the firm chase demand or follow a level schedule and meet fluctuations through inventory? The trade-off is between carrying excess capacity or carrying excess inventory, and thus has the major responsibility of deciding the level of finished goods. If flexibility is desired, then a higher capacity would be the better choice. High market complexity calls for a chase policy. 5. Production planning is based on the forecasts of the future, which can never be accurate, and so production plans are continuously revised. The firm has to decide how often to permit revisions, and what should be the time fence for freezing the plan. High stability may decrease the volume and mix flexibility of the production system.
Phase 2: Detailed material and short-term capacity planning I. How much detailed planning for material flow through the plant should be done? Should the quantity and time for each component and subassembly be planned? What should the time buckets be? This depends upon factors like product
complexity (levels in BOM, end-items options offered, etc.), process complexity (e.g. whether an FMS is used, if product routings are fixed or variable, etc.), manufacturing lead time, etc. If order priority and lead times are OWC, detailed planning is desirable, but makes the shop-floor system less flexible. 2. Should material planning be based on time-phasing, or should it be rate-based? A time-phased system is more suited to a batch type, more complex process environment, and allows a wider range and custombuilt products (higher product complexity) and better product-mix flexibility, but it is not a schedule or volume flexible system. A rate-based approach is more suited to a line process, stable demand and low product complexity, and permits easier schedule changes. 3. What should the detail in capacity planning be? This would depend on how flexible the production process itself is, i.e. how rapidly can the capacity be changed. Also, if the production and material plans are more unstable, more detailed capacity planning is desirable. If cost is an OWC, capacity utilization becomes important, and so more detailed capacity planning is desirable. Higher product and process complexity requires a more detailed capacity planning. 4. How much flexibility and consequent instability should be allowed in the detailed material plan? By freezing the plan for a predecided time fence, the stability and capacity utilization can be increased and is more suitable for high process complexity, but flexibility would be sacrificed and is thus not suitable for high market complexity. Thus the central decision in this phase is how much should be planned centrally and how much latitude is left for shopfloor managers. Should less central planning be done, and more support provided to the front-line supervisors?
Phase 3: Shopfloor systems 1. How important is capacity utilization? If the process environment is highly complex and cost of the OWC utilization is important, and thus finite loading techniques would be desirable. If flexibility and meeting due dates are OWC, then capacity utilization becomes secondary. 2. The extent of tracking/monitoring/expediting has to be decided upon. For orders competing on delivery schedules and lead times, higher monitoring is necessary than in an environment where products are competing on cost or flexibility. 3. How closely should this phase be linked to the earlier phases for sending status and warning signals? In situations where reliable or fast delivery is important, early warning signals are necessary for fast corrective response. 4. Should a pull or push type of control system be
Computer Integrated Manufacturing Systems Volume 7 Number 2
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Linking manufacturing strategy to the design of a PCS: A K Bhattacharya and J L Coleman
used? Pull is simpler, more visible, carries much lower inventory, and gives low lead times which a push system cannot match, but then it is a more rigid and volume-sensitive system. If a push system is chosen, then should reordering be done through MRP or reorder-point? But for successful pull, other techniques like Total Quality Control, Total Productive Maintenance, etc. are essential, and the management must be committed to implement them. 5. What should the batch size and extent of work-inprogress inventory be? Big batches leads to high decoupling inventory, and would give better machine utilization and customer service, but increases costs, increases lead times and requires more detailed material planning. It is more appropriate for a high level of process complexity and low market complexity. Lower WIP inventory, besides reducing costs, would improve the material flow through the shop and reduce throughput time, and so would be desirable where delivery time is crucial for success. These decision areas have been summarized in Table 2. The above discussion gives a broad but detailed picture of the decision areas involved in designing a PCS, and how the manufacturing strategy/task and constraints of product and process affect the choice in each of these decisions. Stage 3: Integration
The set of selected levels of each decision variable forms the guidelines for the detailed design of the complete system. This detailed design will require integrating the levels selected while bearing in mind the peculiarities of each firm's operations.
Customized PCS design We would like to draw an inference from the above discussion, which is that more than one set of PCS design decisions can be made to form the guidelines for the detailed design of the PCS in Stage 3, which are appropriate for a given manufacturing task and product/process constraints. What is important is that when making these design decisions, clear linkage with the market-manufacturing dimension should be sought, and any trade-offs should be made intentionally and objectively. The other main conclusion is that the selected set of design decisions, when seen holistically, may well mean selecting a hybrid PCS system which meets the manufacturing strategy within the product/process constraints. This flexibility of the model is particularly important given the increasing importance being given to hybrid systems for controlling production.
Case examples We now look at some of the case examples of using this approach on four medium-sized automotive component suppliers. The first two examples will deal with the objectives of this approach, i.e. how focus is lost and inconsistencies crop up. In the next two examples, we have followed through the first and second stage of the approach to develop the guidelines for the PCS to match the needs of manufacturing strategy. Case A: Company A is supplying automotive components to both the O E M and the spares market. The market complexity and the set of competitive criteria are different. While the O E M market demands flexibility and annual target-pricing with delivery reliability as an order qualifying-losing sensitive criteria, the
Table 2. Summary of multi-level PCS decision variables Phase
Decision variables
Phase 1
Usage of PCS
Production planning demand management Phase 2
Detailed material and capacity planning Phase 3
Shopfloor control systems
Levels
Produce to
Same for all product groups Stock
Assemble to order
Different for each product group Order
Forecast accuracy Demand
High Level
( (
) )
Low Chase
Material planning Material plan
Detailed Time-phased
( ~
) )
Low detail Rate-based
Capacity planning Stability
Detailed High
( (
) )
Low detail Low
Importance of capacity utilization Tracking/monitoring
High
(
)
Low
)
Low
> ) >
Low Pull Low
Linkage to Phase 2 & I Based on WIP inventory
High expediting High Push High
138 Computer Integrated Manufacturing Systems Volume 7 Number 2
(
( (
)
Linking manuJacturing strategy to the design of a PCS: A K Bhattacharya and J L Coleman
market complexity is relatively low. The spares marked demands a high level of service with both delivery reliability and delivery lead times being important, and the market complexity being fairly high as uncertainty is higher and volumes varying from high to low period. The company is using the same PCS for these entirely different markets with the part manufacture being combined. This has led to problems of due-dates being missed for the O E M market, as the system is less flexible than desired, and also stock-outs or high inventory of spares stocks. This is a result of lack of focus, which has led to external inconsistencies between the PCS and the influencing factors.
Table 3. Current and future environments and respective decision variable levels Current environment and PCS
Future environment and PCS
Stage 1: PCS Environment Dimension 1
Manufacturing • Strategy
• Complexity Product Complexity Process Complexity
Delivery Reliability -OWC/OQClosing sensitive, quality, price OQC; Low Low
Lead time, Flexibility OWC, PriceOWC/OQClosing sensitive, Quality-OQC; Medium Low
Medium to high
Low
Stage 2: PCS Decision Variables Phase 1
• Usage of PCS • Produce to • Forecast accuracy • Demand
Same for all stock high
Same for all order low
level
chase
low
low
time-phased high
rate-based low
high
low
high
high
high
low
low
high
push high
pull low
Phase 2
• Material planning • Material plan • Capacity planning • Stability Phase 3
• Importance of capacity utilisation • Tracking/ monitoring/ expediting • Linkage to Phase 2 & 1 • Based on • WIP inventory
Table 4. Summary of existing PCS for Company D PCS decision variables
Existing levels
Phase 1
• Usage of PCS • Produce to • Forecast accuracy • Demand
Same for all product groups stock high for auto, low for leisure level
Phase 2
• • • •
Material planning Material plan Capacity planning Stability
• • • • •
Importance of capacity utilization Tracking/monitoring/expediting Linkage to Phase 2 & 1 Based on Batch size & WIP inventory
medium time-phased high low
Phase 3
high high medium push medium
Case B: Company B is supplying automotive components to car manufacturers. Unlike Company A it faces a higher market complexity as its products are part of options selected by each buyer, resulting in higher uncertainty. It realizes that it needs higher volume and schedule flexibility, has reduced its plan stability, and uses a combination of make-to-order and make-to-stock policy to achieve it. However, it uses a complex batching process with a push-type system which cannot match the flexible planning. This internal consistency has led to high inventory levels and longer lead times than they would like. Case C: Company C is a medium-sized engineering firm supplying high volume per period automotive components to car manufacturers. They had followed a strictly cost-based manufacturing strategy with PCS geared to achieve this task for a low product complexity environment and complex, functional process. However, the automobile firms they were supplying were slowly moving to a make-to-order system and flexibility - deliver and product-mix were becoming order winning criteria while cost is still as important. The company is only now realizing this change, and taking steps to modify their PCS to meet the need for 'refocusing' the system along with simplifying their processes. The different levels of the PCS decision variables for these two environments have been summarized in Table 3. Case D: Company D is a plastics moulding company supplying products both to the automotive (80%) and leisure markets (20%). Many of the automotive products are assembled before supply, unlike leisure products. The automotive products vary from high volume (50%) to low volume per period. The high volumes per period are produced in mostly dedicated
Computer Integrated Manufacturing Systems Volume 7 Number 2 139
Linking manufacturing strategy to the design of a PCS: A K Bhattacharya and J L Coleman lines. The others follow a flexible routing. Product varieties are large for both types, but higher for leisure products. While the market-manufacturing dimension for automotive products is the same as Company C, the leisure products compete differently, with delivery lead time and volume flexibility being crucial; this market is also highly seasonal with high uncertainty of demand. The company uses the same PC-based PCS for all products. The existing PCS decision variables are shown in Table 4. This lack of focus has resulted in high inventory levels and low flexibility, and a need for high tracking/monitoring/expediting. By using the tetrahedron of Figure 2, we have identified that the environment can be categorized in three types. The guidelines for the PCS, which focuses on each type of environment, has been shown in Table 5. From this table, we can see that while a pull-type of PCS can be used for high volume auto products, a push-type of system is required to plan and control the low volume auto and leisure products.
grapple with shifts from make-to-stock to make-toorder, from low cost, more standardized products to an increasingly fragmented and differentiated market, technologies which allow flexibility at high volumes, customers willing to wait less and less time for delivery, etc. To be able to flourish in this environment, manufacturing strategy needs to be explicitly developed, and systems/policies designed to match the strategy. We have proposed an approach which has been found to be effective in identifying issues of focus and consistency, and leads to a PCS design which achieves the objectives of focus and internal and external consistency, as shown in Figure 3. STAGE 1 Formulatedescri- I ption of PCS ~ environment using theoretical construct
STAGE 2 STAGE 3 I Use environment ] I Integratethe modelto choose ~ selected'levels' 'level' within each into customised PCS decision ProductionControl variable System
Focus
Conclusion There has been a slow but steady shift in the environment facing the production system today. Firms have to
External Consistency
Internal Consistency
The Approach
The
Objectives
Figure 3. Three-stage approach achieves PCs design objectives
Table 5. Application of Stages 1 & 2 of the proposed approach to Company D Stage
Product Group A (high volume~period auto products)
Product Group B (low volume~period auto products)
Product Group C (leisure products)
Delivery Flexibility - OWC, Price - OWC/OQC-losing sensitive, quality, delivery reliability - OQC; Low
Delivery Flexibility - OWC, Price - OWC/OQC-losing sensitive, quality, delivery reliability - OQC; Low
Volume and delivery flexibility - OWC, price, quality - OQC;
Medium
Medium
Low
Low
Medium
Low to medium
Stage 2 Phase 1 Produce to order
Build to stock
Build to order
Forecast accuracy Demand
Low investment in forecasting Level
Higher investment Chase
Combine produce to stock and order Highest investment Level/chase
Less detailed material planning Less detailed capacity planning Rate based Stable plan
More detailed
More detailed
More detailed
More detailed
Time-phased More stable plan
Time-phased Less stability
Pull Capacity utilization less important Tracking/monitoring important WlP/batch size small
Push Capacity utilization more important Tracking/monitoring less important Larger
Push Capacity utilization less important Tracking/monitoring less important Smaller
Stage 1: Dimension 1: Manufacturing • Strategy
• Complexity Dimension 2: Product Complexity Dimension 3: Process Comple~ty
Phase 2 Material planning Capacity planning Material plan Plan stability Phase 3 Based on Importance of Capacity utilization Tracking/monitoring Batch size/WlP Level
140 Computer Integrated Manufacturing Systems Volume 7 Number 2
Medium-to-high
Linking manufacturing strategy to the design of a PCS: A K Bhattacharya and J L Coleman References
13 I Mathews, J P and Foo, S T 'The focus, span and links in research on operations management strategy', Joint Industry University Conference on Manufacturing Strategy', Ann Arbour. MI (1990) 2 Skinner, W Manufacturing- The Formidable Competitive, Weapon, Wiley, Chichester (1985) 3 Wheelwright, S D 'Japan - Where operations really are strategic', Harvard Bus. Rev., Vol 59 No 4 (1981) 4 Nemetz, P N 'Bridging the strategic outcome measurement gap in manufacturing organisations', Joint Industry University Conference on Manufacturing Strategy, Ann Arbour, MI (1990) 5 Hill, T Manufacturing Strategy, Macmillan, London (1985) 6 Draaijer, D J 'Market orientedness of improvement programmes in manufacturing: results from field study research', Int. J, Operat. Prod. Manage., Vol 12 No 7/8 (1992) pp 24-41 7 New, C 'World-class manufacturing versus strategic trade-off', J. Operat. Prod. Manage., Vol 12 No 4 (1992) pp 19-31 8 Swamidass, P M 'Manufacturing strategy: Its assessment and practice', J. Operat. Manage., Vol 6 No 4 (1986) pp 471-484 9 Hayes, R H and Wheelwright, S C Restoring our Competitive Edge, Wiley, Chichester (1984) 10 Platts & Gregory, 'Manufacturing audit in the process of strategy formulation', Int. J. Operat. & Prod. Manage., Vol 10 No 9 (1990) pp 5-26 11 Schroeder, R G and Lahr, T N 'Development of manufacturing strategy: A proven process', Joint Industry University Conference on Manufacturing Strategy, Ann Arbor, MI (1990) 12 Ward, P T et al. 'Manufacturing strategy: An overview of current process and content models',
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Joint Industry University Conference on Manufacturing Strategy, Ann Arbor, MI (199(I) Vollmann et aL Manufacturing Planning and Control Systems, Dow Jones-Irwin, Homewood, IL (1988) De Toni, A et aL 'Production management techniques: Push-pull classification and application conditions', Int. J. Operat. Prod. Manage., Vol 8 No 2 (1988) pp 35-51 Hirakawa, F et al. 'A hybrid push/pull production control system for multi-stage manufacturing processes', Int. J. Operat. Prod. Manage., Vol 12 No 4 (1992) pp 69-81 Minfie, R J and Davis, R A 'Interaction effects on MRP nervousness', Int. J. Prod. Res., Vol 28 No 1 (199/)) pp 173-183 Grunwald, H et al. 'Framework for quantitative comparison of production control concepts', Int. J. Prod. Res., Vol 27 No 2 (1989) pp 281-292 Lee, L C 'A comparative study of push and pull production systems', Int. J. Operat. Prod. Manage., Vol 9 No 4 (1989) pp 5-18 Sarkar, L and Fitzsimmons, J 'The performance of push and pull systems: A simulation and comparative study', Int. J. Prod. Res., Vol 27 No 10 (1989) pp 1715-1731 Finch, B J and Cox, J F'Process-oriented production planning and control: Factors that influence system design', Academy of Manage. J., Vol 31 No 1 (1988) pp 123-153 Kochhar, A and McGarrie, B 'Identification of requirements of manufacturing control system: A key characteristics approach', Integrated Manuf. Syst., Vol 3 No 4 (1992) pp 4-15 Berry, W L and Hill, T 'Linking systems to strategy', Int. J. Operat. Prod. Manage., Vol 12 No 10 (1992) pp 3-15 Ward, P T et aL 'Mapping manufacturing concerns and action plans', Int. J. Operat. Prod. Manage., Vol 7 No 3 (1987)
Computer Integrated Manufacturing Systems Volume 7 Number 2 141
Linking manufacturing strategy to the design of a customized hybrid production control system A K BHATTACHARYA and J L COLEMAN
Abstract: In recent years, increasing attention has been paid to manufacturing strategy. Considerable work has been done in defining market-driven competitive priorities as part of manufacturing strategy and linking them to 'structural' decision areas. Linkage to 'infrastructural' decision areas like Production Control Systems (PCS) is found to be inadequately researched. This paper presents a three-staged approach which links manufacturing strategy to PCS. First, the PCS environment is described using three dimensions of: competitive priorities, product complexity and process complexity. The environment defined in the first stage is then used to select the appropriate level of multi-level 'decision variables' which fully define a PCS in Stage 2. In the third stage, the set of selected levels for each of the decision variables, which form the guidelines for detailed PCS design, are then integrated into a hybrid PCS customised to the manufacturing strategy of the firm. This approach to PCS design was then tested at several firms and was found to be useful for identifying the inconsistencies between existing PCS and the manufacturing environment and strategy. Keywords: manufacturing strategy, production control system
-n recent years, increasing attention has been paid to manufacturing strategy as a means to attain ,competitive advantage. The focus has been twopronged - first to understand the contents of a successful manufacturing strategy; and second, to find out the best or the most effective way to evolve the strategy. What has been under-represented both in theory and practice is the question of implementation. Mathews and Foo ~, in a study of the subject, observed that 'because one cannot assume that all planned strategies are implemented well, implementation research becomes important to strategy evaluation and performance'. Thus there is a need for more research linking
l
Warwick ManufacturingGroup, Universityof Warwick, Warwick, UK
134 0951-5240/94/02/0134--08(~ 1994 Butterworth-HeinemannLtd
strategic decisions to operational decision making. In this paper, we first look at the need for a theoretical construct which would help in implementing the manufacturing strategy decisions in the design and procurement of the production control systems of a firm. We present such a construct, and make some conjectures on the linkage between strategy and PCS selection. P h i l o s o p h i c a l b a c k g r o u n d to m a n u f a c t u r i n g strategy
The philosophical foundation of manufacturing strategy has often been traced to Skinner's 2 seminal work: 1. 'Manufacturing: The missing link in corporate strategy' 2. 'The focused factory', first published in 1969 and 1974, respectively. In them, Skinner first mooted the twin concepts of 'focus' and 'consistency', which still form the basis of most research in manufacturing strategy. However, the phenomenal success of the 'Japanese' manufacturing strategies, and also the advent of flexible manufacturing systems, have lead to the broadening the definition of 'focus' to enable multiple manufacturing objectives to be achieved simultaneously3-7. But there is no doubt on the need to align the manufacturing objectives/task/ strategy with process/technologies and operating systems/policies. C u r r e n t research in m a n u f a c t u r i n g strategy
The two broad areas of research currently much in vogue can be classified as 'content' and 'process' models of manufacturing strategy. Many authors have
Linking manufacturing strategy to the design o f a PCS: A K Bhattacharya and J L Coleman
defined manufacturing strategy 8-11. Ward et al. 12 capture the content of manufacturing strategy in two broad categories: 1. Decision areas that are of long term importance in the manufacturing function, (which have been categorized into 'structural' and 'infrastructural' decision areas by most authors). 2. Competitive priorities based on corporate and/or business unit goals (or what Hill -~ calls the OWC/ OQC). From the survey of literature on manufacturing strategy, we conclude that considerable work has been done in defining competitive priorities and also their linkage to the 'structural' decision areas, i.e. how to achieve consistency between strategy and manufacturing structure. But the linkage to 'infrastructural' decision areas or operating systems and policies has been inadequately researched.
Production control systems The objective of any control system is to ensure that for the process or activity under control, the desired behaviour is attained. Production control systems attempt to control the manufacturing plant. This is viewed as a hierarchical process with three distinct phases or activities. Vollmann et al. 13 call them the front end (production planning and demand management), engine (detailed material and capacity planning) and rear end (shop floor systems). Traditionally, the implementation of a PCS has been seen as selecting the appropriate system like MRP, JIT/ Kanban, Reorder-point, etc. based on the needs of process/technology and internally generated performance variables. Most of the research has been limited to the sensitivity of a particular system to changes in operating parameters 14-16, or comparative study of different systems and identification of application conditions14.17 19.
Design o f production control systems Some authors 2'17"2° have mentioned the need to 'design' a PCS rather than select one of the standard systems. They and others, like Kochhar et al. 2~, have identified some of the factors or key characteristics that affect the design. They also identified some of the 'design variables' or decisions like inventory levels, produce to stock or order, level of monitoring/ expediting, etc., which form the framework for PCS design. Berry and Hill 22 appear to be one of the few authors to have looked in detail at this linkage between the influencing factors and the PCS decision variables. They identify three PCS variables of make-to-stock, make-to-order or assemble-to-order, and link these variables to the requirements of order winning/order qualifying criteria and manufacturing process in order to achieve consistency.
However, what we find is a lack of research in systematically identifying the factors that influence the decisions to be made when designing a PCS and putting them in a usable framework or a model. Secondly, we also find that few authors have systematically identified all the decision variables which can then form the guidelines for detailed PCS design and a relationship between influencing factors and these design variables. In this paper, we present an approach which we hope provides the missing links in linking manufacturing strategy to the design of production control systems an 'infrastructural' decision area.
Proposed approach to PCS design We propose that a customized PCS can be designed by following a three-stage approach, as shown in Figure 1. The first stage consists of using a theoretical construct or model which fully defines the environment in which the PCS will operate by incorporating the influencing factors. In the second stage, PCS is viewed as a set of 'multi-level decision variables'. By concentrating on each decision variable and selecting the appropriate level to match the needs of the environment defined in stage 1 (rather than looking to select a system such as MRP, JIT or OPT), we get the guidelines or framework for developing a customized PCS. In the third stage, these chosen set of 'levels' for each of the decision variables are integrated to constitute the customised PCS. We think such an approach is especially desirable, as it appears that no single PCS model meets the requirements of today's environment, and an increasing need is felt for 'hybrid' PCS solutions customized to the needs of each firm. The objectives of such an approach are to achieve: 1. Focus - which is redefined as the environment constituting the set of factors that affect the design and operation of the PCS, and help to differentiate between the various PCSs which are desirable for either different product groups, or between current and future requirements for the same product group, or between different areas of processing for the same product group. 2. External consistency - which is redefined as consistency between the individual design decisions of the PCS and the focused environment of the first objective. 3. Internal consistency - which is redefined as consistency between the individual elements of the PCS.
Formulate description of PCS environment using theoretical construct STAGE 1
i
Use environment ] model to choose ~ 'level' within each PCS decision variable STAGE 2
r
I Integrate selected set of 'levels' to design a customised Production Control System STAGE 3
Figure 1. Proposed approach for design of customized hybrid PCS Computer Integrated Manufacturing Systems Volume 7 Number 2
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Linking manufacturing strategy to the design of a PCS: A K Bhattacharya and J L Coleman Stage 1: Theoretical construct o f PCS environment
Table 1. Factors which influence PCS design
Factors which affect PCS design can be divided into three categories:
Dimension 1: Market- Manufacturing
• Manufacturing strategy (which is represented by market driven competitive criteria) • Process • Product.
Dimension 2: Product Complexity
It is proposed that different combinations of these three dimensions of market, product and process characteristics will warrant a particular configuration of PCS decison variables. But these three factors are not independent. In the long run, we must remember that the product and process variables are themselves influenced by manufacturing strategy/task. The market-manufacturing strategy dimension has two components: competitive criteria, as developed by the Warwick Manufacturing Group (given below), which would be classified using Hill's 5 classification of order winning, order qualifying and losing sensitive criteria. The seven competitive criteria are: • • • • • • •
Price/cost Product quality Delivery lead time Delivery reliability Delivery flexibility/volume flexibility Design flexibility Enquiry lead time.
The other component of this dimension is what we call market complexity, which depends upon demand uncertainty, demand stability and volumes per period. Higher uncertainty, instability or low volume per period leads to higher market complexity, and vice versa. The second dimension of product complexity can be viewed in three levels of high, medium and low complexity. If there are large number of products with divergent requirements/options and/or a greater number of bill of materials levels, the product will be considered a complex one. If there are a few homogeneous product lines, the product would be considered less complex. Similarly, the third dimension of process complexity is also viewed in three levels. A highly complex process would be using a number of process technologies in a batch type or job shop environment, utilizing concepts like FMSs. The low complexity process environment would be flow shops or large batch processing with few, less complex and similar technologies, and having more of a rigid product routing, unlike more complex environment which would have flexible routing. These influencing factors are shown in Table 1. One can picture this theoretical construct as a kind of tetrahedron, as shown in Figure 2. The base gives the two dimensions of product and process complexity, and the height denotes the combination of market driven
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• Competitive Criteria: Set of OWC/OQC • Complexity: Demand uncertainty Demand stability Volume per period BOM Level Option Offered Degree of standardization Dimension 3: Process Complexity
Routings Process technologies used Level of AMT
criteria, which gives rise the manufacturing strategy competitive criteria and market complexity. We draw an important conclusion from this construct. The environment of the PCS is governed by the market-manufacturing dimension and the complexity (or the lack of it) of product and process. Since, ultimately, a PCS has to be consistent with the market-manufacturing dimension, it can look on product and process dimensions as constraints in the short-term. This implies that product and process dimensions dictate what kind of systems are possible, and not what is desirable when designing the system. In fact, as Ward et al. 23 had pointed out, PCS can sometimes be used to correct misalignments between manufacturing strategy and product/process. Stage 2: Decision variables in a production control system
In this stage we identify the decision variables which form the framework of any PCS, and discuss their linkage to the three dimensions of Stage 1. We have viewed a PCS as consisting of the three phases of production planning, detailed material planning and shop floor controls. Phase 1: Production planning, demand management and master production schedule
1. The first question to be asked is how should different product groups be handled? Should they be planned for and controlled separately, or should the same PCS design handle all the product groups? Different manufacturing tasks should ideally be handled by different hybrid PCS. 2. The policy of whether to produce to stock, assemble to order or produce to order has to be decided upon. This would be dependent upon whether the manufacturing lead time is less or more than the customer lead time, the type of products and distribution system (e.g. consumer products distributed through large warehouses are normally fed through stocks), whether customer service requirements can be met
Linking manufacturing strategy to the design of a PCS: A K Bhattacharya and J L Coleman
/
Market Manufacturing
/
H : High M : Medium L : Low
.! C L
Strategy and
H
Complexity B
L H
M/
A
Process
Complexity
L L
M
H
> Product Complexity
Figure 2. Stage 1: Classification of PCS environment. X: Manufacturing strategy A/complexity low, medium product & low process complexity; Y: Manufacturing strategy C/complexity high, high product and process complexity
only through stocks, etc. Make to order is suited to custom-built products, large variety products or higher process complexity, while a standard, predetermined and narrow range of products is better suited for make to stock. 3. The firm has to decide the accuracy of forecasts required. Higher accuracy requires more investment in forecasting, and would be desirable for a make to stock policy, where high customer service and delivery reliability are essential, to reduce excess rescheduling, and also for a higher level of market complexity. 4. Should the firm chase demand or follow a level schedule and meet fluctuations through inventory? The trade-off is between carrying excess capacity or carrying excess inventory, and thus has the major responsibility of deciding the level of finished goods. If flexibility is desired, then a higher capacity would be the better choice. High market complexity calls for a chase policy. 5. Production planning is based on the forecasts of the future, which can never be accurate, and so production plans are continuously revised. The firm has to decide how often to permit revisions, and what should be the time fence for freezing the plan. High stability may decrease the volume and mix flexibility of the production system.
Phase 2: Detailed material and short-term capacity planning I. How much detailed planning for material flow through the plant should be done? Should the quantity and time for each component and subassembly be planned? What should the time buckets be? This depends upon factors like product
complexity (levels in BOM, end-items options offered, etc.), process complexity (e.g. whether an FMS is used, if product routings are fixed or variable, etc.), manufacturing lead time, etc. If order priority and lead times are OWC, detailed planning is desirable, but makes the shop-floor system less flexible. 2. Should material planning be based on time-phasing, or should it be rate-based? A time-phased system is more suited to a batch type, more complex process environment, and allows a wider range and custombuilt products (higher product complexity) and better product-mix flexibility, but it is not a schedule or volume flexible system. A rate-based approach is more suited to a line process, stable demand and low product complexity, and permits easier schedule changes. 3. What should the detail in capacity planning be? This would depend on how flexible the production process itself is, i.e. how rapidly can the capacity be changed. Also, if the production and material plans are more unstable, more detailed capacity planning is desirable. If cost is an OWC, capacity utilization becomes important, and so more detailed capacity planning is desirable. Higher product and process complexity requires a more detailed capacity planning. 4. How much flexibility and consequent instability should be allowed in the detailed material plan? By freezing the plan for a predecided time fence, the stability and capacity utilization can be increased and is more suitable for high process complexity, but flexibility would be sacrificed and is thus not suitable for high market complexity. Thus the central decision in this phase is how much should be planned centrally and how much latitude is left for shopfloor managers. Should less central planning be done, and more support provided to the front-line supervisors?
Phase 3: Shopfloor systems 1. How important is capacity utilization? If the process environment is highly complex and cost of the OWC utilization is important, and thus finite loading techniques would be desirable. If flexibility and meeting due dates are OWC, then capacity utilization becomes secondary. 2. The extent of tracking/monitoring/expediting has to be decided upon. For orders competing on delivery schedules and lead times, higher monitoring is necessary than in an environment where products are competing on cost or flexibility. 3. How closely should this phase be linked to the earlier phases for sending status and warning signals? In situations where reliable or fast delivery is important, early warning signals are necessary for fast corrective response. 4. Should a pull or push type of control system be
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Linking manufacturing strategy to the design of a PCS: A K Bhattacharya and J L Coleman
used? Pull is simpler, more visible, carries much lower inventory, and gives low lead times which a push system cannot match, but then it is a more rigid and volume-sensitive system. If a push system is chosen, then should reordering be done through MRP or reorder-point? But for successful pull, other techniques like Total Quality Control, Total Productive Maintenance, etc. are essential, and the management must be committed to implement them. 5. What should the batch size and extent of work-inprogress inventory be? Big batches leads to high decoupling inventory, and would give better machine utilization and customer service, but increases costs, increases lead times and requires more detailed material planning. It is more appropriate for a high level of process complexity and low market complexity. Lower WIP inventory, besides reducing costs, would improve the material flow through the shop and reduce throughput time, and so would be desirable where delivery time is crucial for success. These decision areas have been summarized in Table 2. The above discussion gives a broad but detailed picture of the decision areas involved in designing a PCS, and how the manufacturing strategy/task and constraints of product and process affect the choice in each of these decisions. Stage 3: Integration
The set of selected levels of each decision variable forms the guidelines for the detailed design of the complete system. This detailed design will require integrating the levels selected while bearing in mind the peculiarities of each firm's operations.
Customized PCS design We would like to draw an inference from the above discussion, which is that more than one set of PCS design decisions can be made to form the guidelines for the detailed design of the PCS in Stage 3, which are appropriate for a given manufacturing task and product/process constraints. What is important is that when making these design decisions, clear linkage with the market-manufacturing dimension should be sought, and any trade-offs should be made intentionally and objectively. The other main conclusion is that the selected set of design decisions, when seen holistically, may well mean selecting a hybrid PCS system which meets the manufacturing strategy within the product/process constraints. This flexibility of the model is particularly important given the increasing importance being given to hybrid systems for controlling production.
Case examples We now look at some of the case examples of using this approach on four medium-sized automotive component suppliers. The first two examples will deal with the objectives of this approach, i.e. how focus is lost and inconsistencies crop up. In the next two examples, we have followed through the first and second stage of the approach to develop the guidelines for the PCS to match the needs of manufacturing strategy. Case A: Company A is supplying automotive components to both the O E M and the spares market. The market complexity and the set of competitive criteria are different. While the O E M market demands flexibility and annual target-pricing with delivery reliability as an order qualifying-losing sensitive criteria, the
Table 2. Summary of multi-level PCS decision variables Phase
Decision variables
Phase 1
Usage of PCS
Production planning demand management Phase 2
Detailed material and capacity planning Phase 3
Shopfloor control systems
Levels
Produce to
Same for all product groups Stock
Assemble to order
Different for each product group Order
Forecast accuracy Demand
High Level
( (
) )
Low Chase
Material planning Material plan
Detailed Time-phased
( ~
) )
Low detail Rate-based
Capacity planning Stability
Detailed High
( (
) )
Low detail Low
Importance of capacity utilization Tracking/monitoring
High
(
)
Low
)
Low
> ) >
Low Pull Low
Linkage to Phase 2 & I Based on WIP inventory
High expediting High Push High
138 Computer Integrated Manufacturing Systems Volume 7 Number 2
(
( (
)
Linking manuJacturing strategy to the design of a PCS: A K Bhattacharya and J L Coleman
market complexity is relatively low. The spares marked demands a high level of service with both delivery reliability and delivery lead times being important, and the market complexity being fairly high as uncertainty is higher and volumes varying from high to low period. The company is using the same PCS for these entirely different markets with the part manufacture being combined. This has led to problems of due-dates being missed for the O E M market, as the system is less flexible than desired, and also stock-outs or high inventory of spares stocks. This is a result of lack of focus, which has led to external inconsistencies between the PCS and the influencing factors.
Table 3. Current and future environments and respective decision variable levels Current environment and PCS
Future environment and PCS
Stage 1: PCS Environment Dimension 1
Manufacturing • Strategy
• Complexity Product Complexity Process Complexity
Delivery Reliability -OWC/OQClosing sensitive, quality, price OQC; Low Low
Lead time, Flexibility OWC, PriceOWC/OQClosing sensitive, Quality-OQC; Medium Low
Medium to high
Low
Stage 2: PCS Decision Variables Phase 1
• Usage of PCS • Produce to • Forecast accuracy • Demand
Same for all stock high
Same for all order low
level
chase
low
low
time-phased high
rate-based low
high
low
high
high
high
low
low
high
push high
pull low
Phase 2
• Material planning • Material plan • Capacity planning • Stability Phase 3
• Importance of capacity utilisation • Tracking/ monitoring/ expediting • Linkage to Phase 2 & 1 • Based on • WIP inventory
Table 4. Summary of existing PCS for Company D PCS decision variables
Existing levels
Phase 1
• Usage of PCS • Produce to • Forecast accuracy • Demand
Same for all product groups stock high for auto, low for leisure level
Phase 2
• • • •
Material planning Material plan Capacity planning Stability
• • • • •
Importance of capacity utilization Tracking/monitoring/expediting Linkage to Phase 2 & 1 Based on Batch size & WIP inventory
medium time-phased high low
Phase 3
high high medium push medium
Case B: Company B is supplying automotive components to car manufacturers. Unlike Company A it faces a higher market complexity as its products are part of options selected by each buyer, resulting in higher uncertainty. It realizes that it needs higher volume and schedule flexibility, has reduced its plan stability, and uses a combination of make-to-order and make-to-stock policy to achieve it. However, it uses a complex batching process with a push-type system which cannot match the flexible planning. This internal consistency has led to high inventory levels and longer lead times than they would like. Case C: Company C is a medium-sized engineering firm supplying high volume per period automotive components to car manufacturers. They had followed a strictly cost-based manufacturing strategy with PCS geared to achieve this task for a low product complexity environment and complex, functional process. However, the automobile firms they were supplying were slowly moving to a make-to-order system and flexibility - deliver and product-mix were becoming order winning criteria while cost is still as important. The company is only now realizing this change, and taking steps to modify their PCS to meet the need for 'refocusing' the system along with simplifying their processes. The different levels of the PCS decision variables for these two environments have been summarized in Table 3. Case D: Company D is a plastics moulding company supplying products both to the automotive (80%) and leisure markets (20%). Many of the automotive products are assembled before supply, unlike leisure products. The automotive products vary from high volume (50%) to low volume per period. The high volumes per period are produced in mostly dedicated
Computer Integrated Manufacturing Systems Volume 7 Number 2 139
Linking manufacturing strategy to the design of a PCS: A K Bhattacharya and J L Coleman lines. The others follow a flexible routing. Product varieties are large for both types, but higher for leisure products. While the market-manufacturing dimension for automotive products is the same as Company C, the leisure products compete differently, with delivery lead time and volume flexibility being crucial; this market is also highly seasonal with high uncertainty of demand. The company uses the same PC-based PCS for all products. The existing PCS decision variables are shown in Table 4. This lack of focus has resulted in high inventory levels and low flexibility, and a need for high tracking/monitoring/expediting. By using the tetrahedron of Figure 2, we have identified that the environment can be categorized in three types. The guidelines for the PCS, which focuses on each type of environment, has been shown in Table 5. From this table, we can see that while a pull-type of PCS can be used for high volume auto products, a push-type of system is required to plan and control the low volume auto and leisure products.
grapple with shifts from make-to-stock to make-toorder, from low cost, more standardized products to an increasingly fragmented and differentiated market, technologies which allow flexibility at high volumes, customers willing to wait less and less time for delivery, etc. To be able to flourish in this environment, manufacturing strategy needs to be explicitly developed, and systems/policies designed to match the strategy. We have proposed an approach which has been found to be effective in identifying issues of focus and consistency, and leads to a PCS design which achieves the objectives of focus and internal and external consistency, as shown in Figure 3. STAGE 1 Formulatedescri- I ption of PCS ~ environment using theoretical construct
STAGE 2 STAGE 3 I Use environment ] I Integratethe modelto choose ~ selected'levels' 'level' within each into customised PCS decision ProductionControl variable System
Focus
Conclusion There has been a slow but steady shift in the environment facing the production system today. Firms have to
External Consistency
Internal Consistency
The Approach
The
Objectives
Figure 3. Three-stage approach achieves PCs design objectives
Table 5. Application of Stages 1 & 2 of the proposed approach to Company D Stage
Product Group A (high volume~period auto products)
Product Group B (low volume~period auto products)
Product Group C (leisure products)
Delivery Flexibility - OWC, Price - OWC/OQC-losing sensitive, quality, delivery reliability - OQC; Low
Delivery Flexibility - OWC, Price - OWC/OQC-losing sensitive, quality, delivery reliability - OQC; Low
Volume and delivery flexibility - OWC, price, quality - OQC;
Medium
Medium
Low
Low
Medium
Low to medium
Stage 2 Phase 1 Produce to order
Build to stock
Build to order
Forecast accuracy Demand
Low investment in forecasting Level
Higher investment Chase
Combine produce to stock and order Highest investment Level/chase
Less detailed material planning Less detailed capacity planning Rate based Stable plan
More detailed
More detailed
More detailed
More detailed
Time-phased More stable plan
Time-phased Less stability
Pull Capacity utilization less important Tracking/monitoring important WlP/batch size small
Push Capacity utilization more important Tracking/monitoring less important Larger
Push Capacity utilization less important Tracking/monitoring less important Smaller
Stage 1: Dimension 1: Manufacturing • Strategy
• Complexity Dimension 2: Product Complexity Dimension 3: Process Comple~ty
Phase 2 Material planning Capacity planning Material plan Plan stability Phase 3 Based on Importance of Capacity utilization Tracking/monitoring Batch size/WlP Level
140 Computer Integrated Manufacturing Systems Volume 7 Number 2
Medium-to-high
Linking manufacturing strategy to the design of a PCS: A K Bhattacharya and J L Coleman References
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