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3 Enhancing the Materials Selection Process in Design: A Vision To identify the information technologies required for a computer-aided system to support materials selection, the committee articulated a future vision of a full-function Computer-Aided Materials Selection System (CAMSS) based on the information summarized in Chapter 2. In the future, materials selection is envisioned in a business context that has several major differences compared to current environments. The engineering design process is evolving from a stage of emphasis on concurrent engineering (i.e., the simultaneous design of products and manufacturing processes within a company) to one on concurrent enterprise processing (i.e., the simultaneous design of products and processes that takes into account internal and external partnering, preferred supplier relationships, and corporate alliances). There is an ever-increasing pressure for accuracy, flexibility, speed, and competitive leadership. The information systems supporting the concurrent enterprise process will be more ubiquitous, powerful, and integrated into the business process. As a result of these changes, the impact on materials selection is substantial. Materials selection will be based on a much broader range of concerns and not on isolated, sub-optimized steps. The concurrent enterprise process demands that material selection is not only broad based, but done fast, right, at the correct time, and once. Software to support materials selection will be part of an integrated computing environment that spans the concurrent enterprise process and makes use of embedded assistance for many aspects of the product life-cycle. Amidst the evolution of the business context, materials selection continues to occur in two forms: strategic materials selection and routine materials selection. There are no sharp distinctions between these, but strategic decisions are primarily in response to corporate objectives, high-visibility customer requirements, or strategic technology planning. The introduction of new materials or processes for a particular product application is nearly always a strategic decision. Such decisions are strategic because of the time required and capital costs associated with validation and investment in new process capabilities. The pressures for increased agility in response to global competition is a mixed blessing for the introduction of new materials. The competitive pressure places demands on leadership but strips away the time to react. The advanced computing support for strategic and routine materials selection differs but shares a common infrastructure. The following four sections explain the vision for this common business and information processing environment, discuss the unique capabilities required for strategic and routine materials selection, and examine the basis for innovative materials selection in design. INTEGRATED ENGINEERING SUPPORT IN INTEGRATED ENTERPRISES Enterprises consideration are causing organizations to change the way they view themselves. New relationships with internal and external units are emerging. The shift to an emphasis on concurrent engineering is evidence of the shift that concentrates on internal and external partnering. External partnering has led to favoring preferred supplier relationships over low-bid competition. Technology ''food-chains" are being addressed with corporate strategies for strategic technology planning. Alliances with technology suppliers are increasing. As more cooperation emerges between units, more unified communication and computing environments are ramping up to meet the need. Increased emphasis on standards gives evidence to this shift. For example, the Initial Graphics Exchange Standard, which is used to exchange geometry, is expected to be supplanted by the evolving, international Standard for the Exchange of Product Definition Data, the goal of which is the exchange of complete, unambiguous computer-interpretable definitions of the physical and functional characteristics of a product throughout its life-cycle. These shifts provide an
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infrastructure to support future concurrent enterprise processes. In the mean time, computing hardware and software capabilities continue to evolve with an emphasis on integrated computing environments and open systems. Partnerships between software suppliers permit engineering organizations to consider a suite of applications that collectively cover substantial acreage in the art-to-part landscape. Standards in user interface technology (e.g., X-windows) are breaking down conceptual barriers between computer applications. In a few places currently, and more so in the future, the engineer is supported by a computing environment for the rapid transmission of shared data that links to other engineering and manufacturing organizations both within the company and with suppliers and vendors. In the future, functional capabilities of software will be integrated so that conceptual design alternatives can be developed and evaluated for any number of criteria during early product planning phases. The alternative selected in this process must have a high probability of being manufacturable at the target costs negotiated by the product team. There must be an equally high probability that the product meets the requirements of the customer and is aligned with the technology plans of the enterprise. The development and evaluation of these alternatives by design teams could be assisted by integrated computer-aided systems. These knowledge base systems are woven into the computing framework. Because of the integration of the environment, they do not appear to users as separate systems but rather add to the functionality that the system provides. Thus, from the user perspective, knowledge base tools are undifferentiated from analysis and design automation tools. Typically, computer-aided systems are to provide design advice, leaving final decisions to the engineer. The advice given by the system can be as simple as selecting a default material specification. It can tell the engineer where to find suppliers of relevant material or it can retrieve that material. It can analyze a design and provide a quantitative or qualitative judgment. It can suggest an improvement or generate an alternative that includes the improvement. It can search a variety of alternatives and suggest the best or the best few alternatives based on quantitative or qualitative judgments and user-supplied criteria. The alternative selected during concept evaluation is then available for refinement in a coarse-to-fine development process. The details of the computer model of the product then evolve, aided by the use of a number of design advisor tools that provide reference information, analyze a design, critique it, improve it, or optimize it for a given set of design metrics. Analysis and design automation tools also help in the refinement of the product description. Available throughout the process are advice and knowledge about materials. Significant material properties as well as emerging considerations, such as life-cycle costs, are to be increasingly supported by the information infrastructure. Materials knowledge is to be accessible to the engineer as reference material through design advisors that interact with the user as well as product and process models to analyze, critique, improve, or optimize it. Major tools in the integrated environment should provide the following capabilities: managing electronic repositories of data and documents; searching through past development histories to find similar or analogous products; managing interactions with other parts of the enterprise; managing requirements; predicting performance characteristics; predicting manufacturing and maintenance characteristics; estimating costs; suggesting improvements to the proposed product or process description; and releasing material, product, and process descriptions to other components of the enterprise. SUPPORTING STRATEGIC MATERIAL DECISIONS As indicated earlier, strategic materials selection almost always occurs for new material introduction. It also occurs when there are several material alternatives that represent significant tradeoffs in critical customer requirements (e.g., appearance, durability, cost, and risk). In the future, materials experts should use simulations of material performance at both micro- and macro-structural levels to reduce the cost of material validation. Material models must include manufacturing process performance as well as product performance. Major cost savings are found in the reduction of decision-time and rework required. Material supplier and users must regularly join together to develop and specify materials and processes. Strategic decisions are to be made using formal decision methodologies and computer tools for support. Quality Functional Deployment and Decision and Risk Analysis
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are two examples of methods supported by tools (see Chapter 4). Materials are the focus of many strategic decisions but only one of many factors in far more strategic decisions. To support the decision process, performance and cost models for materials and processing are to be used for strategic decisions that include long-range business planning. Strategic decision making cannot be handed over to computers; rather computers and information systems must be relied on to provide access to documented information and models of the business, product, processing capabilities, and processing influences on materials. They can also manage the complexity of related decision variables and keep track of alternatives that are under consideration. Broader access to such information contributes to a better understanding and quantification of the risk from the introduction of new materials. It is important to recognize that materials design for "structure critical" applications tends to be rather conservative. Designers cannot afford to take unnecessary risks with new materials but they can gain expertise with processing and performance of new materials in noncritical or development applications (e.g., composite fishing rods, nitanol eyeglass frames, or ceramic scissors). Such experience is vital in gathering data and confidence for critical purpose applications. However, it is imperative that future systems be able to collect, organize, and distribute such lessons-learned experience. SUPPORTING ROUTINE MATERIAL DECISIONS Routine material decisions happen every day for every component developed by the enterprise. There is increasing emphasis on the process for making such decisions to assure consistency, accuracy, and reliability. Computer systems can provide assistance to the engineering community to follow established processes but should not lock the user into a rigorous framework that strips the user of opportunities to exercise creativity. There is pressure to include more factors in all decisions. Materials selection is influenced by factors such as manufacturing; assembly; service; and environmental impact of material production, use, and disposal or recycling. Computer-aided advisors can help manage the complexity of the many concerns. Supporting the product team in the materials selection process are electronic documents; cost estimation tools; trade-study tools; material, product, and process data bases; and knowledge base systems that provide analysis, critiques, and product improvement suggestions. Materials selection falls within the scope of such tools. SUPPORTING INNOVATIVE MATERIALS SELECTION IN DESIGN A prospective computer-aided system should also be capable of assisting innovative design. It should not just provide a limited series of conventional material or processing choices. This section addresses the characteristics of CAD support systems for solving difficult, nonroutine design problems. The concepts presented here are drawn extensively from the recent publication by Steven Kim entitled The Essence of Creativity: A Guide to Tackling Difficult Problems (Kim, 1990). A design problem can be characterized by its domain, difficulty, and size. Domain refers to the application area or areas, size refers to the amount of work needed to analyze and implement the design solution, and difficulty refers to the level of conceptual challenge to identify an acceptable solution. A difficult problem is one in which resolution is not readily discernible. Design problems can be ill-structured. They are generally not bounded by algorithmic models and may lack complete sets of heuristics to be applied to the design space. Therefore, an innovative design is the creative resolution of a difficult problem. A creative solution exhibits certain features that are close in conceptual space and others that are more distant in that space—a concept Kim terms "the Multidistance Principle." Those aspects of the solution that are closest to the knowledge or experience of the design team may be clearly evident. Those aspects that are more distant in the solution space are the ones that often require insightful thinking. The Multidistance Principle has implications for the development of software tools such as computer-aided systems that enhance finding creative design solutions. These tools must be able to establish links to one or more attributes of the distant elements of the design solution as well as providing access to the more routine, detailed design features.
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There are several factors that contribute to the generation of a creative design solution. The objective of the design must be defined and distilled into its elements in order to begin the design process. The elements of the design objective can be viewed as a logical hierarchy of design alternatives and decisions regarding the alternatives (Weber et al., 1991). The creative solution process has two elements: (1) a structure, characterized by diversity and relationships, and (2) vehicles for enhancing the idea-generating process involving imagery and externalization . Diversity refers to the fusion of disparate ideas (i.e., the Multidistance Principle). It can be aided by memory enhancers, such as access to knowledge bases and historical archives. Relationships define the pattern among design space objects that can be discovered from reference to related problems and rapid enumeration of alternative solutions. Imagery is the generation of ideas through sensory images (auditory and tactile as well as visual). The most powerful imagery for humans is visual. It is possible through imagery to represent numerous objects and their relationships simultaneously. Externalization is the expression or communication of the ideas to others through text, models, and diagrams of the process. Externalization helps to clarify the idea and is often the most important step in achieving a creative design solution. The use of virtual reality is an example of the combination of imagery and externalization. The creative solution process structure represents the important ingredients for innovative design and problem solving. The strategy for enhancing innovation is the development of tools that promote or enhance elements of this structure, especially memory, imagery, and externalization. With this strategy, one can identify several domains of knowledge that can contribute to the enhancement of innovative design: artificial intelligence (learning, inferencing, and knowledge representation); computer and network technologies (parallel processing, storage media, network communications, and workstations); human interface technologies (graphics, vision, touch, animation, simulation, and voice or speech); and cognitive psychology (perception, memory, reasoning, and insight). Human memory, either in an individual or within a group, is both a store of archival knowledge and work area for the development and examination of design alternatives. The contents of human archival memory, enhanced by computer recall of details or related concepts, facilitates the generation of novel elements of a possible design solution. The working memory of the individual or group is a basis by which to craft the full solution. Imagery and externalization that aid in representing various solutions are key to bringing a wide range of information to bear on the design problem at hand. While computer-aided systems have been used to enhance logical, rule-based thinking and neural networks can learn perception, the element of cognitive psychology called "insight" is the key to the discovery of creative solutions to difficult design problems. Computer technologies and tools may not be able to replace human insight but could enhance it. This area needs research emphasis as a critical component of design technology. SUMMARY The materials-specific information technologies that designers require in a CAMSS and some of the computer technologies that are needed to build this system are summarized in Table 3-1. Figure 3-1 specifies the high-level conceptual architecture and some of the contents of a full-function CAMSS based on the vision presented in this chapter. The state of the art of the information technologies pertinent to the materials selection process is discussed in the next chapter.
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Table 3-1 Summary of the Materials-Specific Information Technologies and Some of the Primary Computer Technologies Required for a CAMSS MATERIALS SELECTION CAPABILITIES REQUIRED PRIMARY COMPUTER TECHNOLOGIES REQUIRED Routine Materials Selection—Standard selection process for every component developed that consistently, accurately, and reliably follows established procedures without eliminating opportunities to exercise creativity. System requires tools that manage the complexity of manufacture, assembly, inspection, service, and environmental impact considerations of material production, use, and disposal/recycling, and suggests product improvements. Materials databases and knowledge bases Electronic documentation of previous designs Heuristics and selection reasoning traceback Cost estimation modeling Strategic Materials Selection—Decisions to introduce new materials based on understanding/quantification of risk, impact on customer requirements, and correspondence with enterprise objectives and strategic technology planning. System should not make strategic decisions but should (1) provide design advice; (2) develop and evaluate conceptual design alternatives that meet customer requirements, manufacturing target costs, and enterprise strategic plans; (3) provide access to material-performance models and decision methodologies; and (4) collect, organize, and distribute lessons-learned experience to assist future decisions. Modeling systems for tradeoff analysis: Constitutive Analysis Process modeling Performance simulation Cost estimation Risk assessment Lessons-learned collection and searching systems: Object-oriented databases Neural networks Electronic documentation Case-based reasoning Integrated Enterprise Processes—Materials selection based on broad range of industrial competitiveness considerations, including internal and external partnering and preferred supplier relationships and alliances. Requires ubiquitous, powerful, and well-integrated systems with standardized computing environments and data structures to promote unified communication and permit rapid assembly/transmission of shared data both within companies and with suppliers/vendors. Standardized data structures or data dictionaries Inter- and intra-company networking/communication systems Innovative Materials Selection—Must assist innovative design and help solve difficult, nonroutine problems as opposed to just providing limited series of conventional material or processing choices. Tools that enhance/stimulate creative processes and insight via human interface technologies that promote learning, inferencing, and cognition. Artificial intelligence (learning, inferencing, and knowledge representation) Database and knowledge base acquisition Human interface technologies (graphics, vision, touch, animation, simulation, and voice or speech) Linking of multiple knowledge bases
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Figure 3-1 The conceptual architecture of a CAMSS.
Representative terms from entire chapter: