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Computers and Industrial Engineering Vol. 25, Nos 1---4,pp. 329-332, 1993
0360-8352/9356.00+0.00 Copyright © 1993 PergamonPress Ltd
Printed in Great Britain. All fights reserved
MULTICRITERIA EVALUATION OF THE DESIGN/BUILD PROCESS Thomas M. West and Sabah U. Randhawa Department of Industrial and Manufacturing Engineering Oregon S.tate University Corvallis, Oregon 97331
INTRODUCTION The professional environment of the industrial/ manufacturing engineer has undergone substantial change over the past decade. A number of factors have driven this process, but the primary cause has been the realization that domestic industries were losing their competitive position in both home and overseas markets. After years of corporate neglect, the importance of strong manufacturing organization has slowly dawned on a number of administrative personnel. This has placed a growing emphasis on the manufacturing engineering function within many companies and brought to the forefront the need to consider product design and production under a new set of operating conditions. These include: New products are being introduced at an ever increasing rate. 2.
Product life is in many cases quite short with volume sales over a compressed time period.
3.
The rate of technological development in both materials and processes is very high.
4.
Markets are international and so is the competition.
The effect of these factors on the manufacturing environment is reflected in the rate at which manufacturing requirements change. In addition, the performance criteria that companies have to satisfy has changed considerably. Efficiency and low unit costs were traditionally the most important criteria for most manufacturing companies. Now consumers are more quality conscious and are interested in obtaining the latest available technology. In order to react faster to volume or mix of sales, industries have to design and produce for flexibility. This does not mean that efficiency is no longer important. However, it is clear that today's manufacturing is operating in a muiticriteria environment, where quality and flexibility are just as important as cost, if not more.
The effective design and operation of a manufacturing facility involves factors, both technical and operational in nature. Two of the more important technical factors are (1) product design, and (2) process design. Achieving flexibility may require a fundamental change in product design to accommodate characteristics of flexible automation systems, and manufacturing operations may have to be modified to accommodate diversified product flow and production control. THE EVALUATION PROCESS Many companies have found that "up to 85 percent of the product's manufacturing costs are typically determined before the manufacturing department becomes involved with the design of a new product" (Funk et al., 1989). Many product designers are not familiar with the manufacturing aspects of the product; thus, manufacturability concerns and manufacturing costs are often not considered in the product design until it is too late to economically make significant design changes. In the conventional approach to designmanufacturing, the design engineers produce product specifications based primarily on input from sales and marketing with limited consideration of the available processes or technology. On the other hand, production often must spend large amount of time and resources meeting product tolerances and quality specifications when a minor change in product design could have eliminated a number of these problems. By considering manufacturing alternatives in the design process, the system can be simplified or modified to improve its efficiency and productivity. The role of product design in new manufacturing technologies is discussed at length by the authors in West, Randhawa and Brings (1989). Concurrent Evaluation of Product Design and Manufacturing Process
The selection of a design for a new or modified product can no longer be made independently of the
329
330
Proceedings of the 15th Annual Conference on Computers and Industrial Engineering
Model Design
manufacturing process. Every element of the design affects the selection of an economically efficient process to manufacture that component or subeomponent of the product. This is also true of material specification and interworking relationships between materials and processes, quality, life cycle costs and time to market.
The first step in the evaluation process is the selection of the material properties for the features to be produced. Next, characteristics of the processes for the creation of these features need to selected. Finally, a simulation model is used to analyze the designprocessing sequence. A schematic drawing of the model is shown in Figure I.
This paper addresses the development of a computer-based methodology to assist the manufacturing engineer in the evaluation of alternative design~material~process combinations in the specification of metal components. The economical manufacture of machined metal parts involves the consideration of several sometimes conflicting objectives. Cutting speeds, machine tool efficiency, tool life, tool material costs, and ehangoover costs all must be considered in the specification of production methods, tolerances and quality goals. The economic model developed in this research considers the incorporation of four basic components of this decision: machining costs, tool costs, tool changing costs and workpiece handling costs.
A computer initiated dialogue with the user (query manager) is used to obtain product specifications and parameters of the system. Since input requirements differ for different operations (turning, milling, grinding, etc.), a different screen is presented to the user for each operation specified. An example screen for the milling operation is shown in Figure 2. The system uses two sets of databases, one which describes features of tool and work materials, and another which describes the features of the processes used in machining and metal removal. The query manager continuously interacts with these
USER
productdescription, designcons~aints SystemDatabases MaterialsDatabase
economic,operational measures
material,process characteristics
~, SimulationModule t
qualitative a~bute assessment
Multiat'aibuteModel
J,
/
] rankingof alternates
I ProcessDatabase
SelectedAlternative
Figure 1. Design Evaluation Modeling Framework --Function
Work m a t e r i a l Tool material
TI~
0.75 0.75 0.25
: : :
Horse p o w e r • 20.0 Tool d l a m e t e r ~ 0.375 No. of teeth/rev. : 4
inch inch inch
motor, Efficiency: inch, <-(Shift FS)
.6
Parameter Parameter Distributioo Parameter 2 3 Shift F6 1 2.0 min, mln min, : ( ON ) 1.5 2.0 min, min min, : ( ON ) 1.5 min : CO
Load/Unload Tool changing Process time COST
3
( WM0040 ) <-Shift F3 ( TM0100 ) <-Shift F4
: G R A Y CAST IRON : H I G H SPEED STEEL
L e n g t h of work Width of w o r k Depth of work
WORK
MACHINE & TOOL
Record
: MILLING
O p e r a t i n g Cost T o o l i n g Cost
: :
20.0 4.0
Figure 2. Milling Screen
$/hr S/tool
WEST and RANDHAWA:Multicriteria Evaluation
databases to obtain information on work and tool materials, and equipment capabilities and shapes that each operation is capable of producing. Both the databases and the query manager are implemented in Paradox (Paradox 3.0, 1988). The emphasis in the design of the dialogue has been to make it simple and interactive so that it can be used with no knowledge of the database structure or the simulation program. The simulation module analyzes the material and process combination in terms of technical and economic performance measures. Technical measures include throughput, work-in-process inventories, and machine utilizations; economic measures include production costs. The simulation model is developed in SIMAN simulation language (Pegden, Shannon and Sadowski, 1990). Two type of simulation outputs are available to the user: a customized output report and SIMAN summary report. The customized report has been designed to compute and present results on production economics. The SIMAN summary report, produced using the report generating features of the SIMAN language, provides information on technical performance measures, such as throughput levels, utilizations, and inventories (Figure 3).
331
addressed before capacity planning and new technology introductions can be implemented. A simple modeling framework that can be used for this evaluation is the additive linear model (West and Randhawa, 1990). The use of this model requires: Develop attribute weights reflecting the relative importance of attributes in the decision environment. The evaluation process needs to include both technical, economic, and strategic attributes. Different procedures that can be used to develop weights include ranking, pairwise comparison, and ratio-weighting. 2.
Score the alternatives on each attribute. Here alternatives represents the design-manufacturing combinations evaluated in the first phase. Some strategic attributes may require judgmental scales for their evaluation. However, excluding such attributes may result in incorrect representation of the decision environment.
3.
Combining the attribute scores (fii) and attribute weights (wi) for each altern:itive into an aggregate measure CtJj) using the additive linear model: s
Multieriteria Evaluation
Integrating product design and manufacturing analysis, as described in the previous section, is the first phase in evaluating the "production system" at the design phase of a product. The second phase is combining the results obtained from the first phase with strategic considerations that extend beyond the specific production subsystem. Issues such as manufacturing flexibility, integration of individual production subsystems, interfaces through information networks, and customer quality requirements all need to be
Uj = E wifij ' ill where n represents the number of attributes. The aggregate scores can then be used to compare alternative design-manufacturingcombinations in terms of their effectiveness in meeting organizational goals.
Tally Variables
Number
Identifier Average Standard Minimum Maximum Number Deviation Value Value of Obs ................................................................... 1 T I M E IN S Y S T E M 37.53 1.91 18.57 40.96 200
D i s c r e t e Change V a r i a b l e s ......................... Number
Identifier Average Standard Minimum Maximum Time Deviation Value Value Period ................................................................... 1 2 3 4
Q0~UE 1 Qu~u~ 2 MACHINE 1 MACHIITE 2
1.00 .33 .99 .00
.04 .48 .08 .00
.00 .00 .00 .00
Figure 3. Output Report
1.00 1.00 1.00 0.00
3227.53 3227.53 3227.53 3227.53
332
Proceedings of the 15th Annual Conference on Computers and Industrial Engineering CONCLUSIONS The models presented in this paper deal with performance evaluation and selection of "production" systems. A simulation-based methodology is used for evaluating the alternatives on different performance characteristics. A multiattribute decision model is then presented to integrate performance characteristics with strategic considerations. The methodology is useful in a number of ways. First, simulation allows to model and evaluate production and cost factors for complex systems that are difficult to analyze analytically. Second, by combining different facets of the manufacturing environment, the multi-attribute approach considers the long term implications of the planning decisions. REFERENCES Funk, J.L., et al., "Programmable automation and design for manufacturing economic analysis,~ Pro. 15th Conference on Production Research and Technology: Advances in Manufacturing Systems Integration and Processes, Berkeley, CA, Jan. 9-13, 1989. Paradox 3.0: Introduction to Paradox, Boreland International, Scotts Valley, CA, 1988. Pegden, C.D., R.E. Shannon and R.P. Sadowski, Introduction to Simulation using SIMAN, McGraw-Hill, Inc., New York, NY, 1990.
West, T.M. and S.U. Randhawa, "Capacity planning in a flexible manufacturing environment," in (Eds.) H.R Prasei, T.L Ward and W. Karwowski, Justification Methods for Computer Integrated Manufacturing Systems, Elsevier Science Publ., Amsterdam, 1990. West, T.M., S.U. Randhawa and S.D. Brings, "The role of product design in the evaluation of new manufacturing technologies," Pro. International Industrial Engineering Conference, Toronto, Canada, May 14-17, 1989. AU~O~ Thomas West, PhD, PE, is the Associate Dean of Engineering at Oregon State University. Prior to joining the faculty at OSU, he held positions with the University of Tennessee, Monsanto Chemicals, and IBM. He is a former Vice-President of the Institute. Sabah Randhawa, PhD, is an Associate Professor and the Acting Department Head of Industrial and Manufacturing Engineering at Oregon State University. He holds an undergraduate degree in chemical engineering and graduate degrees in industrial engineering. His research interests are in simulation, decision support systems, and production control.
0360-8352/9356.00+0.00 Copyright © 1993 PergamonPress Ltd
Printed in Great Britain. All fights reserved
MULTICRITERIA EVALUATION OF THE DESIGN/BUILD PROCESS Thomas M. West and Sabah U. Randhawa Department of Industrial and Manufacturing Engineering Oregon S.tate University Corvallis, Oregon 97331
INTRODUCTION The professional environment of the industrial/ manufacturing engineer has undergone substantial change over the past decade. A number of factors have driven this process, but the primary cause has been the realization that domestic industries were losing their competitive position in both home and overseas markets. After years of corporate neglect, the importance of strong manufacturing organization has slowly dawned on a number of administrative personnel. This has placed a growing emphasis on the manufacturing engineering function within many companies and brought to the forefront the need to consider product design and production under a new set of operating conditions. These include: New products are being introduced at an ever increasing rate. 2.
Product life is in many cases quite short with volume sales over a compressed time period.
3.
The rate of technological development in both materials and processes is very high.
4.
Markets are international and so is the competition.
The effect of these factors on the manufacturing environment is reflected in the rate at which manufacturing requirements change. In addition, the performance criteria that companies have to satisfy has changed considerably. Efficiency and low unit costs were traditionally the most important criteria for most manufacturing companies. Now consumers are more quality conscious and are interested in obtaining the latest available technology. In order to react faster to volume or mix of sales, industries have to design and produce for flexibility. This does not mean that efficiency is no longer important. However, it is clear that today's manufacturing is operating in a muiticriteria environment, where quality and flexibility are just as important as cost, if not more.
The effective design and operation of a manufacturing facility involves factors, both technical and operational in nature. Two of the more important technical factors are (1) product design, and (2) process design. Achieving flexibility may require a fundamental change in product design to accommodate characteristics of flexible automation systems, and manufacturing operations may have to be modified to accommodate diversified product flow and production control. THE EVALUATION PROCESS Many companies have found that "up to 85 percent of the product's manufacturing costs are typically determined before the manufacturing department becomes involved with the design of a new product" (Funk et al., 1989). Many product designers are not familiar with the manufacturing aspects of the product; thus, manufacturability concerns and manufacturing costs are often not considered in the product design until it is too late to economically make significant design changes. In the conventional approach to designmanufacturing, the design engineers produce product specifications based primarily on input from sales and marketing with limited consideration of the available processes or technology. On the other hand, production often must spend large amount of time and resources meeting product tolerances and quality specifications when a minor change in product design could have eliminated a number of these problems. By considering manufacturing alternatives in the design process, the system can be simplified or modified to improve its efficiency and productivity. The role of product design in new manufacturing technologies is discussed at length by the authors in West, Randhawa and Brings (1989). Concurrent Evaluation of Product Design and Manufacturing Process
The selection of a design for a new or modified product can no longer be made independently of the
329
330
Proceedings of the 15th Annual Conference on Computers and Industrial Engineering
Model Design
manufacturing process. Every element of the design affects the selection of an economically efficient process to manufacture that component or subeomponent of the product. This is also true of material specification and interworking relationships between materials and processes, quality, life cycle costs and time to market.
The first step in the evaluation process is the selection of the material properties for the features to be produced. Next, characteristics of the processes for the creation of these features need to selected. Finally, a simulation model is used to analyze the designprocessing sequence. A schematic drawing of the model is shown in Figure I.
This paper addresses the development of a computer-based methodology to assist the manufacturing engineer in the evaluation of alternative design~material~process combinations in the specification of metal components. The economical manufacture of machined metal parts involves the consideration of several sometimes conflicting objectives. Cutting speeds, machine tool efficiency, tool life, tool material costs, and ehangoover costs all must be considered in the specification of production methods, tolerances and quality goals. The economic model developed in this research considers the incorporation of four basic components of this decision: machining costs, tool costs, tool changing costs and workpiece handling costs.
A computer initiated dialogue with the user (query manager) is used to obtain product specifications and parameters of the system. Since input requirements differ for different operations (turning, milling, grinding, etc.), a different screen is presented to the user for each operation specified. An example screen for the milling operation is shown in Figure 2. The system uses two sets of databases, one which describes features of tool and work materials, and another which describes the features of the processes used in machining and metal removal. The query manager continuously interacts with these
USER
productdescription, designcons~aints SystemDatabases MaterialsDatabase
economic,operational measures
material,process characteristics
~, SimulationModule t
qualitative a~bute assessment
Multiat'aibuteModel
J,
/
] rankingof alternates
I ProcessDatabase
SelectedAlternative
Figure 1. Design Evaluation Modeling Framework --Function
Work m a t e r i a l Tool material
TI~
0.75 0.75 0.25
: : :
Horse p o w e r • 20.0 Tool d l a m e t e r ~ 0.375 No. of teeth/rev. : 4
inch inch inch
motor, Efficiency: inch, <-(Shift FS)
.6
Parameter Parameter Distributioo Parameter 2 3 Shift F6 1 2.0 min, mln min, : ( ON ) 1.5 2.0 min, min min, : ( ON ) 1.5 min : CO
Load/Unload Tool changing Process time COST
3
( WM0040 ) <-Shift F3 ( TM0100 ) <-Shift F4
: G R A Y CAST IRON : H I G H SPEED STEEL
L e n g t h of work Width of w o r k Depth of work
WORK
MACHINE & TOOL
Record
: MILLING
O p e r a t i n g Cost T o o l i n g Cost
: :
20.0 4.0
Figure 2. Milling Screen
$/hr S/tool
WEST and RANDHAWA:Multicriteria Evaluation
databases to obtain information on work and tool materials, and equipment capabilities and shapes that each operation is capable of producing. Both the databases and the query manager are implemented in Paradox (Paradox 3.0, 1988). The emphasis in the design of the dialogue has been to make it simple and interactive so that it can be used with no knowledge of the database structure or the simulation program. The simulation module analyzes the material and process combination in terms of technical and economic performance measures. Technical measures include throughput, work-in-process inventories, and machine utilizations; economic measures include production costs. The simulation model is developed in SIMAN simulation language (Pegden, Shannon and Sadowski, 1990). Two type of simulation outputs are available to the user: a customized output report and SIMAN summary report. The customized report has been designed to compute and present results on production economics. The SIMAN summary report, produced using the report generating features of the SIMAN language, provides information on technical performance measures, such as throughput levels, utilizations, and inventories (Figure 3).
331
addressed before capacity planning and new technology introductions can be implemented. A simple modeling framework that can be used for this evaluation is the additive linear model (West and Randhawa, 1990). The use of this model requires: Develop attribute weights reflecting the relative importance of attributes in the decision environment. The evaluation process needs to include both technical, economic, and strategic attributes. Different procedures that can be used to develop weights include ranking, pairwise comparison, and ratio-weighting. 2.
Score the alternatives on each attribute. Here alternatives represents the design-manufacturing combinations evaluated in the first phase. Some strategic attributes may require judgmental scales for their evaluation. However, excluding such attributes may result in incorrect representation of the decision environment.
3.
Combining the attribute scores (fii) and attribute weights (wi) for each altern:itive into an aggregate measure CtJj) using the additive linear model: s
Multieriteria Evaluation
Integrating product design and manufacturing analysis, as described in the previous section, is the first phase in evaluating the "production system" at the design phase of a product. The second phase is combining the results obtained from the first phase with strategic considerations that extend beyond the specific production subsystem. Issues such as manufacturing flexibility, integration of individual production subsystems, interfaces through information networks, and customer quality requirements all need to be
Uj = E wifij ' ill where n represents the number of attributes. The aggregate scores can then be used to compare alternative design-manufacturingcombinations in terms of their effectiveness in meeting organizational goals.
Tally Variables
Number
Identifier Average Standard Minimum Maximum Number Deviation Value Value of Obs ................................................................... 1 T I M E IN S Y S T E M 37.53 1.91 18.57 40.96 200
D i s c r e t e Change V a r i a b l e s ......................... Number
Identifier Average Standard Minimum Maximum Time Deviation Value Value Period ................................................................... 1 2 3 4
Q0~UE 1 Qu~u~ 2 MACHINE 1 MACHIITE 2
1.00 .33 .99 .00
.04 .48 .08 .00
.00 .00 .00 .00
Figure 3. Output Report
1.00 1.00 1.00 0.00
3227.53 3227.53 3227.53 3227.53
332
Proceedings of the 15th Annual Conference on Computers and Industrial Engineering CONCLUSIONS The models presented in this paper deal with performance evaluation and selection of "production" systems. A simulation-based methodology is used for evaluating the alternatives on different performance characteristics. A multiattribute decision model is then presented to integrate performance characteristics with strategic considerations. The methodology is useful in a number of ways. First, simulation allows to model and evaluate production and cost factors for complex systems that are difficult to analyze analytically. Second, by combining different facets of the manufacturing environment, the multi-attribute approach considers the long term implications of the planning decisions. REFERENCES Funk, J.L., et al., "Programmable automation and design for manufacturing economic analysis,~ Pro. 15th Conference on Production Research and Technology: Advances in Manufacturing Systems Integration and Processes, Berkeley, CA, Jan. 9-13, 1989. Paradox 3.0: Introduction to Paradox, Boreland International, Scotts Valley, CA, 1988. Pegden, C.D., R.E. Shannon and R.P. Sadowski, Introduction to Simulation using SIMAN, McGraw-Hill, Inc., New York, NY, 1990.
West, T.M. and S.U. Randhawa, "Capacity planning in a flexible manufacturing environment," in (Eds.) H.R Prasei, T.L Ward and W. Karwowski, Justification Methods for Computer Integrated Manufacturing Systems, Elsevier Science Publ., Amsterdam, 1990. West, T.M., S.U. Randhawa and S.D. Brings, "The role of product design in the evaluation of new manufacturing technologies," Pro. International Industrial Engineering Conference, Toronto, Canada, May 14-17, 1989. AU~O~ Thomas West, PhD, PE, is the Associate Dean of Engineering at Oregon State University. Prior to joining the faculty at OSU, he held positions with the University of Tennessee, Monsanto Chemicals, and IBM. He is a former Vice-President of the Institute. Sabah Randhawa, PhD, is an Associate Professor and the Acting Department Head of Industrial and Manufacturing Engineering at Oregon State University. He holds an undergraduate degree in chemical engineering and graduate degrees in industrial engineering. His research interests are in simulation, decision support systems, and production control.