Approaches to Improve Engineering Design (2001) / Chapter Skim
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4. Methods, Theories, and Tools
4. Methods, Theories, and Tools
Pages 17-38
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From page 17... ...
Table 4-1 highlights the contrast between concurrent engineering and conventional engineering design. The concurrent engineering environment has the following characteristics: Reduced cycle time Overlapping of functional activities Collaboration in functional decisions 5 17
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Engineering Sequential design Independent designer Concurrent consideration of product life cycle Total quality management tools All stakeholder inputs Sequential consideration of product life cycle Conventional engineering tools Customer and supplier not involved Concurrent evolution of system and component decisions . Critical sequencing Concurrent engineering strives to meet the need for continually shorter product development cycles and the need to represent the inputs of all stakeholders.
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As decisions are made in the concurrent environment, the impact of each decision on the product is evaluated. This makes the concurrent engineering environment not only contextual but also a fundamental part of the decision process.
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. Quality Function Deployment is used to identify critical customer attributes and to create a specific link between customer attributes and design parameters.
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DECISION MATRIX TECHNIQUES Decision matrix techniques are used to define attributes, weight them, and appropriately sum the weighted attributes to give a relative ranking among designs. An example of the framework for such a process is shown in Figure 4-3.
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The "Weighted Sum of Attributes" decision matrix shown in Figure 4-4 is an example typical of frequently encountered design decisions in which a variety of concepts are viable but vary considerably in their ability to meet conflicting requirements. In the example, for instance, all the concepts will provide attachment, but only one has loose parts.
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As part of playing "what if," sensitivity studies can also be conducted by perturbing the values with varying ranges or probability distribution functions. The "Weighted Sum of Attributes" decision matrix is an important decision tool, but its limitations need to be well understood by the decision maker.
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METHODS AND TOOLS TO ADDRESS VARIABILITY, QUALITY, AND UNCERTAINTY Once the decisions have been made and product design concept finalized, the next steps are to translate the concept to reality. This section deals with decision-making tools, which are methods to address the quality of the design process, to address the variability in the process, and to convert the concept to final product.
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The variation in environmental and manufacturing parameters either is known or can be measured and included in sensitivity analysis of design parameters. Experience has shown that inclusion of environmental and manufacturing noise variation in design decisions is crucial for products to consistently meet the design intent.
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~ , ...., an......... / Design Rang / Design ~ ~ , Acceptable ~ Performance Unacceptable Performance Also called Partial Least Squares or PLS, Projected Latent Structure is a method for constructing predictive models when controllable variables are many and highly redundant.
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27 Taguchi argues for the application of statistical methods throughout the entire engineering design process, from product concept to customer usage. He was among the first to emphasize the importance of statistical planning and analysis of experiments to identify and measure sources of variability and sensitivity to assist in resolving the problems of design engineering.
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Gero and Sudweeks (1996, 1998) , in two recent proceedings of the biennial International Conference on Artificial Intelligence in Design, provide a broad view of the many efforts in this area, which include design processes (decision-driven process models, cognitive theories of design decision making)
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More realistically, however, for all but routine design decisions, AI can best provide powerful knowledge-based support of design decision making, rather than automated decision making. It does this in part by building on an understanding of human decision making in design contexts and tailoring support to enhance human abilities (e.g., pattern recognition)
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FORMAL METHODS FOR REPRESENTING DESIGN PROBLEMS This section covers some limited formal methods and theories for representing design problems. They are selected as representatives from different schools of thought in approaching design problems: traditional engineering, decision theory, and artificial intelligence.
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Different languages are used to represent engineering and design knowledge at different times, and the same knowledge is often cast in different languages in order to serve different purposes. For example, fundamental structural-mechanics knowledge can be expressed analytically, as in formulas for the vibration frequencies of structural columns, numerically, as in discrete minimum values of structural dimensions or in finite element meshing algorithms for calculating stresses and displacements; and in terms of heuristics or rules of thumb, as in the knowledge that the f~rst-order earthquake response of a tall, slender building can be modeled as a cantilever beam whose foundation is excited.
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A MATHEMATICAL FRAMEWORK FOR ENGINEERING DESIGN 5 The decision-based design view of engineering design states that much of design consists of decision-making activities, and that decision support methods used in engineering design should reliably produce good advice. This is a non-trivial condition that demands that design methods
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that all design decisions are made under conditions of significant uncertainty and risk; (2) that the preferences of key importance in a decision are those of the decision maker (not those of the customers or stakeholders)
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Economists use techniques from constrained optimization, decision theory, game theory, and microeconomics (the study of resource allocation) in general to solve such problems.
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Engineering considerations enter through the feasibility constraints faced by firms and through their cost functions (which depend on the production technology, the quantity manufactured, and input prices) for each possible product.
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The interactions and interdependencies among individuals, firms, and products can be captured by market equilibrium. When strategic aspects of individual and firm behavior matter, game theory provides a rigorous analytical tool.
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The multiattribute matrix-oriented techniques are often used to select among overall product concepts, while the statistical methods are more typically used to select among process alternatives and among more detailed design differences. This criterion demonstrates the main strength for some of the more mathematically rigorous approaches.
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From page 38... ...
" One could use Table 4-2 and the discussion in this chapter as a guide to choosing approaches for design application. For example, effective choices include: Concurrent engineering as an overall framework for decreasing costs and time to market; TRIZ for generating alternatives; Some form of Decision Matrix Technique for initial screening of ideas; Six Sigma for process design and evaluation with emphasis on quality control; Decision Analysis for making major investment decisions and for selection among viable concepts; and .
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