Application of design parameters space search for belt conveyor design

Pergamon PII:S0952-1976(97)00044-4

EngngApplic. Artifi lntell. Vol. 10, No. 6, pp. 617--629, 1997 © 1998 Published by Elsevier Science Ltd. All rights reserved Printed in Great Britain 0952-1976/97 $17.00 + 0.00

Contributed Paper

Application of Design Parameters Space Search for Belt Conveyor Design S. S. T S A L I D I S University of Patras, Patra, Greece A. J. D E N T S O R A S University of Patras, Patra, Greece (Received March 1997) Belt conveyor design is examined as an application of a proposed Design Parameters Space Search technique. First, the main characteristics of the belt-conveyor design process are presented as they appear in the current literature. Furthermore, a proposed general knowledge-representation platform is described, and its ability to house the relevant conveyor design knowledge is also shown. Next, the extended search technique of the design space is discussed, and an integrated example of a beltconveyor design is presented, based on the proposed representation platform and the extended search technique. Finally, it is shown that the design of belt conveyors according to the proposed approach presents the following significant advantages: • Due to the knowledge-representation scheme adopted, both qualitative and quantitative knowledge can be used within the same platform. • Multiple solutions can be easily produced through user-defined design criteria. These solutions can be further modified and~or evaluated to produce more-specific designs. • The requirement for user-input data is kept to a minimum. Due to the applied extended search method, semiautomatic design can be achieved. As a consequence, the design process is completed in less time than that required by the conventional methods. © 1998 Published by Elsevier Science Ltd. All rights reserved Keywords: Belt conveyors, design space, searching.

1. INTRODUCTION 1.1. Routine design and artificial intelligence

The modem trend, in almost all engineering fields where design activities are involved, is the extended use of computer programs (design tools) that cover a wide spectrum of design tasks and substantially facilitate the overall design process. These design tools, however, present certain shortcomings which mainly refer to their weakness of reasoning with non-numerical, qualitative or fuzzy design knowledge. Additionally, the majority of these programs use conventional numerical procedures that are not-due to their nature-capable of performing high-level, abstract elaboration of the available design data. Correspondence should be sent to: Dr P. Maresca, Universita di Napoli Federico 11, Dip di Informatiea e Sistemistica, Via Claudio, 21, 80125 Napoli, Italy. [E-mail: [email protected]].

For every distinct design case, there may be different types of design problems to be solved in order to obtain a final optimum design solution. Ullman (1992) describes a classification of these design problems, and emphasizes the fact that for the most of the design cases, more than one design problem is usually involved. Redesign is the modification of a new product, machine or system to meet new requirements. Many redesign problems are routine if the design domain is so well understood that the method used can be put in a handbook as a series of formulas or rules (Ullman, 1992). Usually, routine design involves parametric design for finding allowed values for the design parameters that characterize the object being designed. However, the accumulated designer's experience in conjunction with the appearance of slightly different new problems can complicate the routine, 1990 design process so that, eventually, some original

617

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S.S. TSALIDIS:APPLICATIONOF DESIGN PARAMETERSSPACE SEARCH FOR BELT CONVEYOR DESIGN

design may be needed to accomplish the design task (Ullman, 1992; Homer and Brown, 1990). According to a slightly different definition by Homer and Brown (1990) a design is considered routine when the design attributes, problem-solving methods and strategies and problemsolving alternatives are known prior to the beginning of the design process. The process of finding solution(s) to design problems emerges from the general theory of solving real-world problems established by the science of artificial intelligence. It must be noticed, however, that according to Brown and Chandrasekaran (1986) design is a complex activity, one that artificial intelligence has only weak theories of, especially for those design types that contain a lot of original design. Expert systems (or knowledge-based systems) are computer programs that have resulted from research in artificial intelligence (Ullman, 1992; Korane, 1986). Here, the expert's knowledge is usually represented in terms of rules. A designer may use hundreds or thousands of rules during the design of a product. Expert systems have been successfully applied in configuration design, selection design, cost estimation and project planning (Marcus et al., 1988; Banares-Alcantara, 1991). However, difficulties have been encountered in formulating design experience as rules in the case of expert systems using rule-based reasoning, and formulating the necessary domain knowledge into models in the case of expert systems using model-based reasoning, while recently applied case-based reasoning techniques seems to improve their behavior (Pu, 1993). Moreover, design problems with a significant original component have proved to be too complex to be handled by expert systems (Ullman, 1992). Routine design does not include creative components of design (the conceptual design phase) unless if, for some reasons, a need for some original design emerges (see above). However, a large number of empirical design rules are used. These usually express the accumulated experience of a wide spectrum of field experts, and their significance is widely accepted. These rules can formulate an expertsystem module which, together with the established conventional calculational modules, could form an integrated system for performing routine design.

the design methodology. Roberts et al. (1985) have also reviewed the basic design methodology of belt conveyors and show the impact of applying modem design procedures on both cost and performance, focusing mainly on longdistance overland transportation of bulk solids. Haivorsen (1983) proposes a new design program that mainly incorporates established calculation procedures. Moreover, new techniques based on intense exploitation of the existing design knowledge and on well-known artificial intelligence methods have been proposed (Dentsoras and Gavrielatos, 1993) Deepak et al. (1994); Chattopadhyay et al. (1994). Finally, a number of belt manufacturers and institutes have also developed relative design techniques (Alles, 1988; Transilon, 1989), always in accordance with international standards, established mainly by DIN and ISO. In the present paper, the process of belt-conveyor design is examined as an application of a proposed extended design space search for assigning values to design parameters. In the subsequent sections, a description of the most significant aspects of this approach is given. First, the main characteristics of both the conventional methods and the current trends on belt-conveyor design are presented as they appear in the relevant literature. Furthermore, a proposed general knowledge-representation platform is described, and its ability to house the relevant conveyor design knowledge is also shown. Next, the extended technique for searching the design space in order to assign values to the design parameters is discussed. An example of a belt-conveyor design is also developed, based on the proposed representation platform and the extended search technique. Finally, a discussion is given of the most significant results emerging from the proposed approach.

1.2. Trends in belt conveyor design

(1) Belt-conveyor design is mainly a problem where the design attributes, problem-solving methods and strategies are well established and well defined. If redesign is needed, then this is implemented, for the majority of the cases, through a priori known methods and techniques. (2) There is a large number of strongly-interrelated design parameters whose values can, for the majority of the cases, be acquired by applying well-established calculational formulas and empirical knowledge rules. (3) There are a lot of design constraints resulting from the existing empirical knowledge and the international standards which apply to both the specific procedures that have to be followed, and the final acceptable values of the design parameters.

During the last few decades, the knowledge about the belt-conveyor design process has been substantially enriched, and new design procedures have been proposed, based on the capabilities offered by modem materials and computer systems (Lewis, 1985). In a relevant paper, Foote et al. (1988) examine the payoff of simulation and network analysis in conveyor-system design. In another paper, Roberts et al. (1983) suggest a procedure for the optimum design of continuous conveying, focusing mainly on cost optimization. The same author, (Roberts, 1994) in another paper, presents an overview of the technical and economic factors involved in conveyor design, and focuses mainly on the influence of economic and technical considerations in

2. BELT-CONVEYOR DESIGN

The design of belt conveyors conforms with the general principles, concepts and procedures that apply to all cases where machine design is involved. More specifically, it can easily be proved that belt-conveyor design presents all those characteristics that classify it as a routine design problem, containing only few redesign or innovative design aspects. Some general remarks concerning this classification are given below:

S. S. TSALIDIS: APPLICATION OF DESIGN PARAMETERS SPACE SEARCH FOR BELT CONVEYOR DESIGN

(4) The design process is well-partitioned into completely discrete phases, and the interrelations between these phases are well defined. It must be noticed that the above verifications refer mainly to the nature of the design of conventional conveyors--which covers the majority of the systems installed-and do not apply either to the cases when specific

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operational requirements arise, or when new technology-as a result of research and development--is incorporated. For those cases it is obvious that a lot of either innovative design and/or redesign must apply. For conventional belt conveyors, the design phases are well defined, as well as their interrelations. In Figs 1-4, some block diagrams are given concerning the structure of these phases (Alles, 1988; Spivakovsky and Dyachkov,

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1985). Each phase contains one or more sub-phases (the blocks in the relevant figures) that have to be completed before the phase itself can be considered as having been completed. These phases have been followed for the implementation of the proposed belt-conveyor design. It is not considered necessary to provide details on them here, due to the fact that they are widely known, and used as necessary steps for implementing conveyor designs.

3. THE KNOWLEDGE-REPRESENTATION PLATFORM AND THE SEARCH FOR DESIGN PARAMETER VALUES---THE CONVEYOR DESIGN KNOWLEDGE 3.1. Introduction

The proposed approach establishes a new environment for those design cases where only few innovative design aspects are needed. It incorporates both conventional calculations and empirical knowledge manipulation under a

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unique structure where the same search-for-solutions strategies apply. It also supplies the designer with a platform for implementing his(her) own design procedures, and provides domain-independent mechanisms that could facilitate the design process. 3.2. The structure of the design process

In Fig. 5, the design process is shown schematically. This general design scheme can apply to any routine design problem, and the designer's knowledge can be represented through the proposed representation formalism, which consists of design parameters, tasks, state prototypes, rules and evaluation criteria. By applying search techniques, one or more design states can eventually arise. This is achieved by assigning values, either manually or automatically, to the design parameters. It is assumed that the design states produced have been already checked against the design constraints that are formally incorporated in the design parameter frames. One or more evaluation criteria can also be applied in order to produce a set of final, acceptable solutions.

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3.3. The representation of design parameters, tasks, state prototypes and rules Every design state contains an amount of non-homogeneous design information which can be decomposed into smaller, homogeneous pans, referringto both the product to be designed as well as to the relationships of the current design state with other related design states in the design process. There are five major concepts used for the implementation of the proposed routine design methodology, namely:

calculation", "mass calculation" and "material selection". (4) Design state (DS). This is a certain instance of a DSP at a certain point in the design space, containing all the necessary information for the engaged DPS and DTS that correspond to that point. (5) Design rule (DR). Rules of this kind are mainly used for the assignment of values to the design parameters. In Fig. 6, an example is given of a design configuration for a specific routine design problem. Here, the final design consists of two design tasks, namely the stress calculation and the mass calculation. These tasks require, for their completion, some other tasks. It becomes obvious from this figure that the design process can be represented as a tasktree structure which can easily be searched by using any of the well-known artificial intelligence exhaustive or heuristic search methods. In Fig. 7, the design state prototype "final design" and one of the design tasks ("stress calculation") are shown in a frame-like form, consistent with the formalism described above.

(1) Design parameter (DP). Any individual parameter used to describe elementary operational and structural features of the designed object, e.g. "speed", "material", etc., represented as a frame (Rich and Knight, 1991). (2) Design task (DT). A meaningful design task which aims at the determination of certain feature(s) of the designed object, e.g. "Volume calculation", "material selection", etc., represented as a frame (Rich and Knight, 1991). (3) Design state prototype (DSP). A design prototype scheme is formed through a combination of the available dts and is used to express a certain desirable design. For example, for a certain solid, "physical attributes" is a DSP which, according to a certain point of view, could be formed by the DTS "volume

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3.4. The assignment of design parameter values All design parameters that take pan in the actual design process can generally get their values from: • calculation of expressions, formulas and equations • files, databases, standards and nomograms • designer's experience

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It is assumed that calculation formulas, files and designer's specific ("shallow") knowledge, expressed as rules, constitute the design knowledge for the proposed routine design approach. Under certain circumstances, the calculation of a certain DP can require the calculation of one or more other DPs which, possibly, would require the calculation of some other DPs, etc. If a directed tree structure is adopted for every DP in order to represent its calculation dependencies, then this directed tree structure may serve as a general representation scheme for which a general search method for calculations could be applied. This is shown in Fig. 8 through a

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relatively simple calculation tree for a DP named tr (stress). When the designer asks for the value of o- or some other lower-level DP (e.g. F or A) all existing lower-level calculations within the tree (directed sub-trees) must be completed, and all DPs must have a value prior to the assignment of the required DP value. In order to perform calculations, a depth-first exhaustive search technique can be used (Rich and Knight, 1991). At all times during the design process, all calculation trees must preserve the value consistency of the DPs involved, otherwise the design process would deteriorate. This implies that: (1) The current set of DP values of a certain normal calculation tree are absolutely consistent with the corresponding symbolic formulas, expressions and equations.

DESIGN STATE PROTOTYPE:

FINAL DESIGN RELATIVE DESIGN TASKS:

- STRESS CALCULATION - MASS CALCULATION a.

Fig. 8. A simple stress calculation.

(2) When an alteration of the value of a certain DP takes place, all calculation trees in which it participates, must be automatically updated. There are some design cases when one or more DPs get their values from design rules instead of calculation expressions, equations and formulas according to the method previously described (see Fig. 9). According to the formalism adopted, all rules that contain a value assignment to the specific DP in their THEN part must subsequently be fired. 3.5. Design states and design solutions-the design space topology and the search for solutions-evaluation of solutions Usually, the solution of the design problem starts by the definition of all the design parameters and the design tasks that are expected to be involved in the design process. A design state prototype must be also defined, which then will form the basis for the generation of multiple instances (design states) (see Figs 2 and 3). Every DP modification produces a new design state. A complicated design space, in the form of a network of

DESIGN TASK: STRESS CALCULATION RELATIVE DESIGN TASKS:

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belt thickness is small; belt pulley diameter is small

Fig. 9. Design rules and backward chaining.

S. S. TSALIDIS: APPLICATION OF DESIGN PARAMETERS SPACE SEARCH FOR BELT CONVEYOR DESIGN design states, is shown in Fig. 10. The design states DS i and DS k (gray-shaded nodes) are design solutions, while DS 6 (dot-lined node) is an unacceptable design state because the values of one or more DPs have violated the posed constraints. A D S becomes a design solution if all the design tasks contained in its prototype have been completed. This design solution can be further treated and modified in order to produce other design solutions. Every time one or more design solutions are created, they must be evaluated so that one or more of them will be saved, while all the rest will be ignored. The evaluation criteria used are related to the allowed value ranges of one or more DPs. Then, through a filtering process, only these design solutions will be kept that have been proved successful in satisfying the posed criteria. Multiple schemes of criteria can be configured and then applied on the design solutions created. Depending on the scheme applied each time, different design solutions will pass the filtering process. The situation is shown in Fig. 11.

3.6. The conveyor design knowledge It has previously been proved that the design approach introduced can be used for any problem where mainly

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routine design is involved. Since belt conveyor design is mainly routine, it is possible to apply the approach in order to produce design solutions. This, however, implies that: • Before starting design, the belt-conveyor design knowledge must be completely firm and well-defined, so that it can subsequently be easily expressed according to the approach formalism (knowledge engineering phase) adopted. • The qualitative knowledge which, due to its nature, cannot be expressed through conventional calculation formulas, equations, etc., must be brought into the form of rules which then will be properly processed during the design phases. • The process has to be restricted within the design knowledge regions where there is no case for either the appearance of fuzzy knowledge or a demand for innovative design. Additionally, the criteria for evaluating design states in order to produce design solutions must be completely known (at least during the final design stages). The main objective of the present work was the verification of the ability of the proposed approach to

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Fig. 11. The application of evaluation criteria schemes to design solutions. perform belt-conveyor design. In order to simplify this process, some non-important design tasks and their related design parameters have been intentionally omitted. For those included, 188 design parameters have been used in order to describe the main design features o f the belt conveyor. In Table 1, some examples of design parameters are shown, together with their allowed values and their interrelations. Additionally, in Fig. 12 an example of a calculation tree is given for Filling Cross-Section Area Design Parameter. It is possible to form such trees for every design parameter that takes part in the design. The tree's depth, however, will vary according to the complexity of the design parameter's value-estimation procedure. Besides the conventional calculation formulas used, 121 design rules have also been used in order to express the qualitative empirical knowledge involved in the conveyor

design process. These rules are searched in a forwardchaining manner, and some design parameters o f major importance are allocated their values through their "firing". In Table 2 the 18 tasks that comprise the conveyor design are shown. One or more o f these tasks can be freely chosen in order to formulate a single or multiple design prototype(s) which then will be used for the creation o f design solutions. 4. AN E X A M P L E O F BELT C O N V E Y O R D E S I G N 4.1. Introduction In this section, an example o f a belt conveyor design is given, based on the design approach discussed above. A draft sketch o f the conveyor's configuration is shown in Fig. 13. In Table 3 all the user-defined design parameters are

Table I. Examplesof design parameters Name

Type

Allowed values

Material Bulk Density Material Mechanical Effect Belt Width

R

Belt Speed

R

Resistance Coefficient

R

Entry Starting Belt Tension

R

Troughing Angle Minimum Number of Plies

R

0, 20, 25, 30, 35, 40, 45

R

>= 1, <=5

Relative design par.

Procedure

Units

User access

Material

MatBulkDens

t/m 3

y

T

no wear, medium wear. heavy wear

Material

MatMechEffect

R

300, 400, 500, 600, 650, 800, 1000, 1200, 1400, 1600, 1800, 2000, 2200, 2400, 2600, 2800, 3000, 3200 0.42, 0.52, 0.66, 0.84, 1.05, 1.31, 1.68, 2.09, 2.62, 3.35, 4.19, 5.2, 6.6, 8.4

LumpSize, Trough Scheme,Material Gradation

Belt Width

mm

Y

ApplicationFeature, Belt Speed Level

BeltSpeed

m/sec

N

Conveyor Slope, Material Internal Friction, System Operating Conditions, Corrective Temperature Factor, Belt Speed Exit Starting B e l t Tension, Corrected Starting Peripheral Force TroughScheme

ResistCoefficient

Belt Width, Maximum Starting Tension, Belt Starting Safety Factor, Nominal Starting Belt Strength

Y

N

EntryStartBelt-Tension

N

N

TroughAngle

deg

Y

MinNumPlies

plies

N

S. S. TSALIDIS" APPLICATION OF DESIGN PARAMETERS SPACE SEARCH FOR BELT CONVEYOR DESIGN

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Fig. 12. The calculation tree for the Filling Cross-Section Area Design Parameter.

shown. The user is asked by the program itself to assign values to these design parameters for the design process to continue. 4.2. The design process

First, a Design State Prototype must be chosen. The program offers to the user the "Total Belt Conveyor Design" Table 2. Design tasks of belt-conveyor design Design tasks 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. I 1. 12. 13. 14. 15. 16. 17. 18.

Num. of des. par. Material Characteristics Material Flow Environment Application Characteristics Conveyor Geometry Material Feeding Part Masses (except belt) Belt Mass Belt Geometry-Belt Movement Belt Cover Resistance Elements Tension Member Operational Tensions and Forces Drive Unit(s) Motor(s) Pulleys and Reflectors (idle) Conveyor Starting Conveyor Braking

21 2 2 7 5 7 6 3 17 3l 13 16 11 17 10 4 9 7

Prototype, which includes all the Design Tasks shown in Table 2, together with all the 188 Design Parameters. When the user chooses this, a total design of the belt conveyor is performed. Nevertheless, the user always has the option of adding one or more new Design State Prototypes, or of modifying the already existing ones and choosing one of them at a time in order to perform design. By choosing a Design State Prototype, the designer has two further choices (see Fig. 14). The first is to start a new design, and the second one is to redesign based on an existing Design State that has been created and stored during a previous design session. For both cases, the designer can use the interface form shown in Fig. 15, in order to assign values to the Design Parameters shown in Table 3. Prior to this, the appropriate Design Task has to be selected from the list in the interface form shown in Fig. 14. For the present example to be implemented, the values shown in Table 3 must be assigned to the corresponding Design Parameters. When all the Design Tasks have been completed, a new Design State can be created. Based on this new Design State, the user can produce more Design States by modifying the values of one or more Design Parameters (Fig. 16). In Table 4 some examples are given of new Design States that emerge from variations of certain Design Parameter values.

Fig. 13. A dra~ sketch of a simple belt conveyor.

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S.S. TSALIDIS: APPLICATION OF DESIGN PARAMETERS SPACE SEARCH FOR BELT CONVEYOR DESIGN

For all Design States produced during the current design session, as well as for the already existing Design States, one or more evaluation criteria may successively apply in order to produce Design Solutions. As a consequence, the designer may save only the Design States that have been transformed to Design Solutions through this simple filtering process. For the current case, by applying the 1st criterion (see Table 5), five Design States seem to satisfy it and they might be Design Solutions. By applying the 2nd criterion, only two Design States are found to satisfy it. 5. C O N C L U D I N G R E M A R K S The approach described above constitutes a new methodology for performing routine design. When it is combined with design knowledge concerning belt conveyors it becomes a valuable design tool that can potentially shorten

the design time required, and improve the final quality o f the conveyor design. More specifically: (1) The program environment developed here offers the capability o f combining quantitative (calculation formulas) and qualitative (empirical rules) knowledge through a simple frame formalism that can incorporate almost all kinds o f design information (design parameters, rules, tasks states and solutions). A n y alteration o f these features is allowed during run-time. Additionally, multiple different designs can be implemented on the same design information through the adoption o f the design state prototype concept. (2) The use o f a simple exhaustive search technique for assigning and propagating value changes to the design parameters can integrate every design task in a very

Table 3. User-defineddesign parameters A/A

Designparameter

Value

l 2 3 4 5 6 7 8 9 I0 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38-57 58 59 60 61 62 63 64

Material Mass Flow Conveying Gradient Angle Belt WidthQ Conveying Length Application Feature Belt SpeedQ Idler Speed Trough Scheme UniformityCoefficient System Operating Conditions Belt Carcass Material Loading Properties Belt Carcass Material Resistanceto Chemicals Belt Carcass Material Trough Properties Belt Cover Density Motor Type Motor Mass Moment of Inertia Drive Brake MaterialInternal Friction OutdoorTemperature Material Feed Speed MaterialFeed Height Special Resistance Drive Scheme OperatingConditions Pulley Surface LoadingConditions Acceleration Run-down-Time First Drive Wrap Angle Safety Operating Conditions Take-upType TroughingAngle TransverseRigidity Factor Lump Shape Mass of Cubic Lump MaterialSurface Texture RequiredCover Characteristics~ RequiredCover Material Suitability LoadingFrequency Load Aggresivity Additional Mean Wear Top Cover Thickness Planned Operating Period Return Trough Scheme Feed Chute Height

Gravel 280 10 400 80 standard conditions 2.62 450 three-part 1.1 standard good poor good 1.6 squirrel cage 0,02 900 average - 20 2 1 100 drive via secondary transmission wet Rubber Covered full load 0.3 10 180 normal adapted with adjustable tension force 35 18 cubic 5.65 x 10 3 irregular and angular general conveying frequent moderate 5 16 flat 0.3

Design Parameters whose value computation is based upon other design parameters, but for which user-definedvalues are also permitted. h Set of 20 Design Parameters, necessary for the selection of Belt Cover Material

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Fig. 15. The interface form for "Conveying Gradient Angle" Design Parameter where all its attributes are shown, together with its current value. The designer can move either forwards (Next Design Parameter) or backwards (Previous Design Parameter) in the design space.

628

S. S. TSALIDIS: APPLICATIONOF DESIGN PARAMETERS SPACE SEARCH FOR BELT CONVEYOR DESIGN

Additionally, there is no constraint as to the design task from which the design should start. The design is considered as complete simply when all design tasks have been completed. Moreover, and for every value change, an exhaustive search for value constraint violations is performed, and the designer is immediately informed about every violation, if any exists. (3) For every design, multiple design states can be produced, which can be stored or further manipulated in order to produce design solution through the application of suitable simple design criteria. This facility enables the creation of libraries which contain previous designs that can be recalled later for performing design reviews or modifications. Some parts of the program are currently being further elaborated in order to increase its functional efficiency. One main task now being implemented is the creation of a compiler capable of translating calculation formulas and "ifthen" rules entered by the designer into valid design-parameter calculations and dependency trees. The Table 4. New design states Design state

Design parameter

Value

Design State 2

Material Conveying Length Conveying Gradient Angle Trough Scheme Belt Speed Belt Speed

Dry Sand 150 12 V-Trough 4.19 1.68

Design Design Design Design

State State State State

3 4 5 6

completion of this task will upgrade the program's design capability, and will both extend and enhance its design applicability. As far as belt-conveyor design is concerned, the following major remarks must be made: (1) During the present work, it has been proved that conveyor design is mainly a routine design problem, where the relevant general-purpose techniques and methods can apply. (2) There is a lot of well-established domain-specific design knowledge that had to be expressed according to the formalism introduced by the proposed design approach. This has been proved to be a comparatively easy task, since the formalism used for the design knowledge representation--according to the general proposed approach-managed to incorporate it very easily. (3) The time required for performing a single integrated design, that is, the production of a single design state, has been proved to be a function of design progress and accumulated experience. In other words, only the production of the first design state has been proved to be time-consuming, since a great number of design parameters had to have new values, and this fact resulted in extended tree searches. It can be mentioned here that 30 minutes were required for 188 design parameters to acquire their values through 64 value assignments of user-defined parameters; see Table 3. By applying certain changes to parameter values based on

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S. S. TSALIDIS: APPLICATION OF DESIGN PARAMETERS SPACE SEARCH FOR BELT CONVEYOR DESIGN

Acknowledgements--The present paper has been developed within the

Table 5. Design criteria First criterion Material Trough Scheme

frame of the research project EA 827 fund by the Greek General Sec. of Research and Technology.

Second criterion Gravel Three Part

Material Belt Speed Second Angle of Wrap

629

Gravel ---2.62 < 180

pre-existing design states in order to obtain alternatives, these have been obtained in almost negligible time. Additionally, as experience on conveyor design was gained, and only for the production of the first design state, an appropriate sequence of value assignments to parameters was formed, which resulted in further decrease of the design time required. (4) The design solutions obtained by the program have been tested against solutions obtained either manually or by two other conventional programs that had been created during recent years in order to perform conveyor design. For the first case, the comparison showed that the present approach, while gaining in time and robustness, is not yet capable of obtaining the completeness of the traditional design method. This is mainly due to the fact that the knowledge available in the form of "if-then" rules in the program is very "shallow" and is based upon the "closed world assumption", which means that it cannot adapt itself to unexpected situations. On the other hand, it was proved that, when compared with the two conventional programs, a more integrated approach to the conveyor design process was obtained. This is due to the fact, among others, that the system can handle qualitative knowledge, and can reason about parameters such as material characteristics (abrasiveness, chemical action, etc.), environmental effects, belt cover characteristics, loading/unloading conditions, etc. Additionally, the design time required was proved to be considerably shorter.

REFERENCES Alles, I. R., ed. (1988) Conveyor Belt System Design, 3rd edn. Continental Aktiengesellschaft. Hannover, Germany. Banares-Alcantara, R. (1991) Representing the engineering design process: two hypotheses. CAD, 23(9), November Brown, D. C. and Chandrasekaran, B. (1986) Knowledge and Control for a Mechanical Design Expert System. In IEEE Computer Magazine, Special Issue on Expert Systems for Engineering Problems, ed. Se June Hong, pp. 92-101. Chattopadhyay, A., Rao, K. R. and Parameswaran, M. A. (1994) Development of a Database System on Bulk Solids-A Relational Model Approach. Bulk Solids Handling, 14(3), 585-590. Deepak, C. R., Chattopadhyay, A. and Rao, K. R. (1994) An Integrated Knowledge-based Software for Belt Conveyor Design. Bulk Solids Handling, 14(4), 775-779. Dentsoras, A. and Gavrielatos, T. (1993) Applying Expert Systems to Belt Conveyor Design. J. Syst. Eng., 3, 121-134. Foote, B. L., Bobble, L., Radidran, A. and Bedim, A. B. (1988) Simulation and Network Analysis Pay Off in Conveyor System Analysis. Indust. Eng., 20, 48-53. Halvorsen, N. M. (1983) Computer Aided Design of Belt Conveyors. Best Bulk Solids Handling, 3(4), 1! 3-118. Homer, R. and Brown, D. C. (1990) Knowledge Compilation Using Constraint Inheritance,--Proc. 5th Int. Conf. on Applications of Artificial Intelligence in Engineering, Boston, MA, pp. 161-174. Korane, K. J. (1986) Applying Expert Systems to Mechanical Design. Machine Design, 11, 121-124. December Lewis, R. K. (1985) The Impact of Technology on Conveyor Belt Performance. Best Bulk Solids Handling, 5(2), 25-29. Marcus, S., Stout, J. and McDermott, J. (1988) VT: An Expert Elevator Designer that Uses Knowledge-Based Backtracking. ,41 Magazine, Spring 1988, pp. 95-111. Pu, P. (1993) Introduction: Issues in Case-Based Design Systems..41 EDAM, 7(2), 79--85. Roberts, A. W. (1994) Advances in the Design of Mechanical Conveyors. Bulk Solids Handling, 14(2), 255-281. Roberts, A. W., Harrison, A. and Hayes, J. W. (1985) Economic Factors Relating to the Design of Belt Conveyors for Long Distance Transportation of Bulk Solids. Bulk Solids Handling, 5(6), 41-47. Roberts, A. W., Hayes, J. W. and Scott, O. J. (1983) Optimal Design of Continuous Conveyors. Best Bulk Solids Handling, 3(4), 5-14. Rich, E. and Knight, K. (1991)Artificial Intelligence. McGraw-Hill, Inc. Spivakovsky, A. and Dyachkov, V. 0985) Conveying Machines, Vol. I. Mir Publishers, Moscow. Transilon (1989) Conveyor and Processing Belts. Ref. No. 213-Issue 10.89/2, Siegling. Ullman, D. G. (1992) The Mechanical Design Process. McGraw-Hill, Inc.