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--> Product Modularity: a Key Concept in Life-Cycle Design Kosuke Ishii Department of Mechanical Engineering Stanford University Stanford, California The goal of life-cycle design is to maximize the values of the manufacturer's line of products while containing the products' costs to the manufacturer, the user, and society (Figure 1). Engineers must consider performance, cost, and any environmental impact of their designs. Our research develops systematic methodologies that apply to the early stages of product development in integrating life-cycle quality (Ishii, 1995). We address not simply one product but entire product families and changes over product generations. I focus here on the concept of product modularity: a key concept in achieving life-cycle quality. Modularity is particularly important for electromechanical products, such as computers, telecommunication devices, and peripherals. The short technology life-cycle of many of the functions in these products, combined with customer demand for a wide variety of features, necessitates that designers optimize the modularity of components and subassemblies for manufacturability and serviceability. More recently, recyclability of durable products has also become an important consideration. For the past several years we at Stanford University have been developing evaluation metrics of modular designs from different perspectives. Such metrics should lead to design charts that enable engineers to achieve modules with an optimum life-cycle balance. Our current research focuses on three perspectives that drive decisions on modularity. The first perspective is manufacturability. Engineers must address not only one product but the entire product family. They must design the product line in such a way that it has maximum market coverage; at the same time its modularity minimizes the cost of providing variety. This is
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--> Figure 1 Material flow in the life-cycle of a product. Source: Ishii. referred to as design for variety (DFV). Designers must critically evaluate what features require variety, they must identify core platforms with standard features, and they must modularize the design for efficient supply chain and manufacturing. Our research has identified several key metrics (Ishii et al., 1995): Voice of the customer that characterizes the variety requirements (VVOC). Commonality of components and manufacturing processes. Differentiation sequence in the manufacturing process. Figures 2 and 3 show design charts for variety manufacturability of microwave ovens. Figure 2 plots commonality against VVOC, a number derived from quality function deployment. The chart shows that designers should (1) standardize core components that do not require variety and (2) contend with low commonality for features that require variety. Figure 3 plots commonality against stages in the manufacturing line. Empirical data show that one can reduce the cost associated with variety (e.g., inventory and logistics) by communizing the early stages of manufacturing and long lead-time components and then differentiating variety at the final stages of assembly using short lead-time items. Figure 3 illustrates this concept of late point identification (LPI). The charts pinpoint weaknesses in a product line and guide the designers to improved modularization. Ongoing work attempts to quantify more accurately the cost of providing variety. The second perspective addresses both serviceability and reliability. Users must be able to service easily the components requiring routine maintenance or those features that it would cost too much to make highly reliable. This is referred to as design for ownership quality (DFOQ). During the design process, the engineer needs to break into priorities the serviceability in terms of functional importance. A thorough functional analysis, combined with function-based failure modes and effects analysis, guides engineers to an appropriate modularization (DiMarco et al., 1995). Pertinent factors include the following:
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--> Figure 2 DFV Chart 1—Component commonality versus variety voice of the customer. Source: Ishii. Figure 3 DFV Chart 2—Commonality versus manufacturing process sequence. Source: Ishii.
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--> Availability (up-time) requirements and warranty cost targets. Reliability versus maintenance trade-offs. Accessibility of components requiring service. A good example of a modular design for serviceability is the toner cartridge of personal copiers. Companies have opted to embed several key components in the cartridge that require regular maintenance and service. As a result, the end-user can perform most of the service needs simply by replacing the cartridge. Although the service frequencies of various components may vary, the cartridge concept works extremely well for the usage profile of the personal copier. As is illustrated in this example, the service modularity of a product depends heavily on how the product is used. The third perspective is design for recyclability (DFR). To enhance component reuse and the recycling of materials, engineers must embed strategic modularity into the product, and they must reduce the cost to the recycling organizations. Such efforts will lead to overall improvement of industrial ecology through reduction of raw material use, reduction of energy use throughout the product life-cycle, and reduction of solid waste. The key issue is an up-front consideration of recycle modularity at the early stages of product design that addresses product families and their generations. We have proposed several metrics for the complexity of the product demanufacturing process: Variety complexity: commonality of parts in a product family (similar to DFV). Material complexity: number of types of materials used in a product. Sort complexity: levels of disassembly. We now know that the total number of sort bins required for a retirement process of a product family is a good overall indicator of all three of the metrics listed above. In general, more sort bins indicate deeper levels of disassembly, higher material count, and low commonality. A good design for recycle modularity should lead to fewer sort bins. Figure 4 maps the sort bins required for each major module against the average scrap rate of the material recovered from the bins. In this example of a family of ink-jet printers, the I/O paper tray included several types of plastic material and metal fasteners that required four sort bins and resulted in nearly a 40 percent scrap rate. This analysis led to a redesign that cut down the sort bin count to two and the disassembly time to one-third and that improved the scrap rate to 20 percent. Thus, the chart helps designers to select materials, processes, and assembly methods for various components, as well as to make advanced plans for the recycling process. We are now applying the chart to product families from different industries to validate its usefulness.
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--> Figure 4 DFR evaluation chart. Source: Ishii. The metrics and design charts described above guide engineers in formulating modular constructions addressing the issues of: manufacturability, serviceability, and recyclability. These methods also have provided guidance for student design teams in Stanford's graduate course on design for manufacturability. Although the teams felt the metrics and charts helped them analyze current weaknesses and generate improvements, they felt they fall far short of a general methodology for modular designs. We must address the issue of overall evaluation of modularity beyond such simplistic measures as the dismantling cost. However, I feel that such an overall life-cycle evaluation is too complex and inappropriate for early stages of product development. Rather, further work should focus on identifying other criteria for modularization and on developing a trade-off method among the different criteria. To this end, we are developing a computer environment that allows engineers to quickly input rough information about the product family, to evaluate the modularity measures, to plot the design charts, and to also allow iterative trade-off analysis (Ishii et al., 1994).
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--> References Di Marco, P., C. F. Eubanks, and K. Ishii. 1995. Service modes and effects analysis: Integration of failure analysis and serviceability design . Pp. 833-840 in Proceedings of the 1995 ASME Computers in Engineering Conference, September 1995. New York: American Society of Mechanical Engineers. Ishii, K. 1995. Life-cycle engineering design. ASME Journal of Mechanical Design 117:42-47. Ishii, K., C. F. Eubanks, and P. Di Marco. 1994. Design for product retirement and material life. cycle. Materials and Design 15(4):225-233. Ishii, K., C. Juengel, and C. F. Eubanks. 1995. Design for product variety: Key to product line structuring. Pp. 499-506 in ASME Design Technical Engineering Conference Series, September 1995. Vol. 2. New York: American Society of Mechanical Engineers.
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