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Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success (2002)

Chapter: 3 Lessons Learned from Commercial Manufacturing

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Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
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Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
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Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
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Page 49
Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
×
Page 50
Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
×
Page 51
Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
×
Page 52
Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
×
Page 53
Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
×
Page 54
Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
×
Page 55
Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
×
Page 56
Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
×
Page 57
Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
×
Page 58
Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
×
Page 59
Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
×
Page 60
Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
×
Page 61
Suggested Citation:"3 Lessons Learned from Commercial Manufacturing." National Research Council. 2002. Modeling and Simulation in Manufacturing and Defense Acquisition: Pathways to Success. Washington, DC: The National Academies Press. doi: 10.17226/10425.
×
Page 62

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:Lessons Learned from Commercial Manufacturing In recent years, M&S has played a significant role in the development of a variety of commercial products, including the Boeing 777 aircraft, for which three-dimensional M&S was used on both the product design and manufacturing process; jet engine turbine blades at United Technologies, for which M&S was used to refine blade design; new products at Ford Motor Company, where M&S is used extensively in vehicle design, development, trade-off analysis, and verification; the Viper at Daimler- Chrysler, where M&S was used in design; and wheel rims at John Deere & Company, where M&S was used to reduce development time. In addition, M&S was used in the development of new fabrication facilities for Corning and is also used in the design, fabrication, and assembly of semiconductors there. Use of M&S in industrial manufacturing is not without difficulties, however, and significant barriers to pervasive use of M&S throughout the corporate enterprise remain. The committee was asked to identify lessons learned from industry and to identify emerging design, testing, and manufacturing process technologies that can be enabled by M&S. The committee first examined the current uses of M&S technologies in commercial manufacturing, using the automotive industry as an example, and identified barriers to more widespread use. The committee then analyzed the work of the Integrated Manufacturing Technology Initiative (IMTI) to further develop the needs indicated from the commercial manufacturing point of view. 47

48 MODELING AND SIMULATION IN MANUFACTURING MODELING AND SIMULATION IN COMMERCIAL MANUFACTURING The Automotive Industry The automotive industry is one of the world's most competitive industries because of tight profit margins, the need to get vehicles to market quickly, and the need for products that are desirable in different markets worldwide. These factors, added to the complexity of modern automobile design and the complexity of automobile manufacturing facilities, have resulted in increased use of M&S within the industry. The automotive industry needs to reduce the uncertainty involved in designing and building new products. A recent article in Automotive Design and Production quotes one expert as claiming that the entire value of simulation lies in managing risk (Vasilash, 2001~. The article notes that risk reduction results from the ability to make accurate assessments of the performance of a system before money is invested in the tooling to build it Engineering changes can therefore be made at an earlier stage of the project when they are less costly. The same expert states that all automobile manufacturers are now aiming for product development cycles of 18 to 25 months. This results in a reduction of the number of physical prototypes built and less time for physical testing, at the same time that the level of technology in vehicles is increasing. In contrast, automotive product development cycles in the early 1 990s were as long as 5 years (Eisenstein, 2001~. Numerous examples show the automotive industry benefiting from use of models and simulations. Recently, General Motors Corporation was able to complete its Grand River Assembly plant (in Lansing, Michigan) in only 21 months from the start of construction. General Motors credits the use of three-dimensional mathematical modeling with time savings in both the validation of factory design, including ergonomic issues, and the integration of equipment, tools, fixtures, and machinery, which was done before hardware arrived on the factory floor (General Motors Corporation, 2002~. The ability to transfer knowledge developed in the models throughout the company is seen as a form of technical memory. Detroit Diesel Corporation was able to design and build a fully functional prototype V6 diesel engine in 7.5 months. The company credits rapid prototyping tools with permitting the creation of physical models to verify designs, and it credits computer engineering tools with permitting rapid modification of designs as problems were found. The engine was not derived from previous designs (Vasilash, 1998~.

M&S IN COMMERCIAL MANUFACTURING 49 Toyota Corporation made extensive use of simulation in the design and construction of the 2002 Toyota Campy. Among the benefits cited were a 65 percent reduction in the number of prototypes needed and a 10- month reduction in development time. Since the introduction date for the new model had already been fixed, Toyota used the extra time on simulating details of the car, such as overforce calculations on fuel lids and cup holders (Whitfield, 2001~. Like General Motors, Toyota has also used simulation tools to study and resolve ergonomic issues. Toyota has used digital assembly software to characterize the difficulty of motions made by employees in production as green, yellow, or red. A pilot assembly line was used before production began to improve the ergonomics of processes deemed red and to achieve a large reduction in those rated yellow (Whitfield, 2001~. Barriers to Widespread Use of M&S Technologies Despite the successful examples described above, M&S technologies are not yet deeply ingrained in most corporations or industrial sectors. On the basis of a literature review and the experience of its own members, the committee identified a number of barriers, both technological and nontechnological, to the widespread, systemic use of M&S. These barriers include the lack of reusability of existing successful applications, the lack of model reliability and robustness, limitations on integration of systems, and barriers caused by management and process structures. Lack of Reusability Most successful M&S applications have been solutions to specific problems at the level of a single project or a single part. Few applications of M&S at higher levels, such as supply chain integration, have been successful. The applications that have succeeded at higher levels have involved a single product line or a single process, such as continuous materials processing. No examples of successful enterprise-level M&S exist, although there is a trend toward making M&S a part of continuous scheduling, production analysis, and troubleshooting (Gould, 20011. Because of their specificity, it is difficult to integrate existing product solutions into larger systems or to reuse M&S elements in solving new problems. In part, this is due to limitations in the use of computer-aided design (CAD) software. For example, unless all parts are designed using the same CAD software, data sets from several product parts cannot be merged into an overall system design. One solution would be to require all designers to use the same software, but this is not optimal because different

50 MODELING AND SIMULA TION IN A1ANUFAC TURING software packages work best for modeling different types of systems. In addition, because CAD designs are geometric and static, it is not possible to simulate parts or systems under dynamic use conditions. A better understanding of the fundamental physics underlying product performance and manufacturing processes could improve the specificity problem, but such an understanding is lacking. The design of the Boeing 777 aircraft is an example of the restriction regarding simulation under use conditions. A 1997 NRC report discussed this problem as follows: While the Boeing 777 experience is exciting for the VE [virtual enterprise], we should recognize just how limited the existing CAD tools are. They deal only with static solid modeling and static interconnection, and not~r at least not systematically with dynamics, nonlinearities, or heterogeneity. The virtual parts in the CATIA [computer-aided three-dimensional interactive application] system are simply three-dimensional solids with no dynamics and none of the dynamic attributes of the physical parts. For example, all the electronics and hydraulics had to be separately simulated, and while these too benefited from CAD tools, they were not integrated with the three-dimensional solid modeling tools. A complete working physical prototype of the internal dynamics of the vehicle was still constructed, a so-called "iron-bird" including essentially everything in the full 777. While there was finite element modeling of static stresses and loads, all dynamical modeling of actual flight, including aerodynamics and structures, was done with "conventional" CFD [computational fluid dynamics] and flight simulation, again with essentially no connection to the three-dimensional solid modeling. Thus while each of these separate modeling efforts benefited from the separate CAD tools available in their specialized domains, this is far from the highly integrated VE environment that is envisioned for the future, and is indeed far from even some of the popular images of the current practice. Thus while a deeper understanding of the 777 does nothing to reduce our respect for the enormous achievements in advancing VE technology or dampen enthusiasm for the trends the 777 represents, it does make clear the even greater challenges that lie ahead. (NRC, 1997b, p. 138) Lack of Model Reliability and Robusiness Increased acceptance and use of models and simulations in manufacturing and defense systems acquisition will depend on increasing the credibility of the models (Lucas, 1997~. Increasing credibility depends on performing appropriate verification, validation, and testing activities throughout the simulation life cycle (Balci, 1998; Robinson, 19991;

M&S IN COMMERCIAL MANUFACTURING 51 examining the engineering processes used to develop the simulation (Ketcham and Muessig, 20001; and understanding the intended use of the simulation (Muessig et al., 20009. Further development of these practices and of how to integrate them with model development is needed (Balci, 19983. Although some tools exist to support the activities that lead to credibility, knowledge of the use of these tools and the related techniques may not be as widespread as it should be (Pace and Glasgow, 1999~. More research is needed to increase the automation of verification, validation, and testing (Balci 1998~. Some modeling methods are less robust than desired; for example, the results of finite element modeling can differ if different meshes are used (Xu and Liao, 20011. Theoretical and practical development is required to improve the reliability and robustness of models. Development is needed as well in dealing with model data uncertainty (Doyle, 1997; Tolk, 1999) and in quantifying the effect uncertainty has on the validity of models (Pace, 2002~. Lack of System Integration Capabilities Systems engineering is the flow-down process of determining needs, exploring concepts for product systems that fulfill those needs, selecting a concept, developing a design, and setting product specifications. The integration of systems, such as weapons containing software and hardware that are both complex, is hindered by the limitations of systems engineering. For example, it is not possible to directly model the actual outcome of a system in response to its inputs (Sage and Olson, 2001~. Rather, the processes that the system will use to produce outputs can be modeled and then the system can be simulated using a variety of inputs to characterize the output behaviors with respect to the inputs. Systems engineering is limited by the fact that the individual parts of a system, as well as subsystems, influence each other. They adapt to their environment and in so doing change the environment of other parts and subsystems. Only M&S can shed light on this process, but exploration of system behavior through simulation response to random inputs is time-consuming. Existing Management and Process Structures Existing management and process structures are outdated and therefore represent barriers to the widespread use of M&S technologies in manufacturing. Designers are skilled tradespeople who produce and release detailed part drawings, usually with the aid of CAD and CAM software tools. Degreed engineers have an impressive array of M&S tools, known as computer-aided engineering (CAE), available to analyze designs. These tools are often bypassed, however, because analysis takes time and

52 MODELING AND SIMULATION IN MANUFACTURING designers are rated on the number of drawings released rather than on designs that are certified to meet product requirements. Designs are therefore open pushed forward before analysis is complete, and CAE analysis and simulation of product reliability remains divorced from the critical design path (Versprille, 2001~. Project engineers are still rated on the speed at which they can produce and test prototypes (the "build and break" philosophy). Prototype construction therefore begins early in the product development cycle, before up-front modeling and simulation are able to provide guidance. Since the modeling and simulation of an entire product from concept to disposal crosses the boundaries of many disciplines, systemic use of M&S in manufacturing faces large cultural resistance. In addition, although the "build-test-fix" product development cycle is recognized as being inefficient, particularly for large and complex projects, it is still in wide use. Systemic use of M&S requires substantial up-front investment in personnel, training, and software tools. Change is hindered by the significant investment needed to develop the infrastructure necessary for incorporating M&S. In today's business climate, return on investment is evaluated quarterly, and it is difficult to justify the overhead dollars needed to build substantial M&S capabilities. In addition, many corporations are organized into business units, manufacturing units, and support units, each seeking to look like a profit center. The enterprise-level thinking needed to achieve pervasive M&S use even within a product line, much less at the enterprise level itself, is difficult to achieve. INTEGRATED MANUFACTURING TECHNOLOGY INITIATIVE The Integrated Manufacturing Technology Initiative (IMTI)' was launched in 1998 to develop a research and development (R&D) agenda for integrated manufacturing technology in the 21 st century. In this context, "integrated manufacturing" was defined as the effective integration of production, design, supply, and marketing functions to enable improved control, management, and planning for the enterprise. The R&D agenda that was developed addressed key technology goals cutting across all manufacturing sectors and recognized M&S as a critical enabler to support future manufacturing. Indeed, the IMTI report concluded that no ' The initiative, formerly known as the Integrated Manufacturing Technology Roadmapping Initiative, was sponsored by the National Institute of Standards and Technology, the U.S. Department of Energy, the National Science Foundation, and the Defense Advanced Research Projects Agency.

M&S IN COMMERCIAL MANUFACTURING 53 other technology offers more potential for improving products, perfecting processes, reducing design-to-manufacturing cycle time, and reducing product realization costs. The IMTI road map for M&S distinguishes between product and process applications of M&S. Product applications include the following functions: representation of the physical attributes of a product, the effectiveness with which the product performs its advertised functions, cost and affordability, producibility, and requirements related to different phases of the product life cycle. Process applications include the following functions: the material operations performed in manufacturing processes, such as preparation, treatment, forming, removal and addition; the assembly, disassembly, and reassembly of components to form the overall product; the testing and evaluation of product quality; and packaging and remanufacture. The first two columns of Table 3-1, "IMTI Vision for Product Functions," and of Table 3-2, "IMTI Vision for Process Functions," summarize IMTI conclusions regarding the current state of practice and the ideal state of product and process functions, respectively. The study committee developed the material in the remaining two columns regarding real-world limitations on each function and the requirements needed to achieve the ideal state. The limitations place realistic constraints on what can be achieved using M&S. The requirements point to R&D needed to put the prerequisites in place before the desired capabilities can be attained. The committee also partitioned the aspects of M&S addressed in Tables 3-1 and 3-2 into two categories those relating to "in the small" and "in the large" considerations. Modeling and simulation "in the small" refers to aspects of M&S that concern one or, at most, a limited number of modelks) addressed in isolation from the range of all other models. For example, development of a product model and concern for its validation are an "in the small" aspect. On the other hand, "in the large" considerations address problems and issues that cover M&S technologies across the board. For example, integration of models into a common framework is "in the large" concern. As indicated in Table 3-1, the IMTI vision for a future ideal state of M&S use in product design applications includes models that capture all product attributes; interoperability between product and performance models; more accurate cost estimating; manufacturing process requirements included in an integrated design system; all life-cycle considerations included in the product model; and a situation in which analysis leads design, rather than supporting it. Limitations on this vision include those on bandwidth, computation speed, memory, and other communication and computation resources. R&D is required in the areas of model standards and integration; modularity between different M&S

54 MODELING AND SIMULA TION IN MANUFACTURING components; continuity of modeling information across life-cycle phases and between manufacturing facility and site of product use; development of improved search methodologies; and advances in parametric modeling, variational analysis, and probabilistic design. As indicated in Table 3-2, the ideal future state of M&S process applications would include production processes generated from design and enterprise models; reliable models for materials and materials development; micro to macro continuum modeling; automated optimization of complex process models; quality engineered into every manufacturing process via virtual testing; packaging integrated into product and process design; modeling for disassembly, remanufacture, and reuse integrated into product life-cycle model; integration of stochastic and deterministic models to optimize manufacturing processes; and controller simulations that evolve into optimum operations controllers. Real-world limitations to the achievement of the ideal state shown in Table 3-2 include limitations on model content and available knowledge. R&D required to reach this state includes continuity of modeling information across life-cycle phases, standards for product models, improved interoperability, improved composability, use of families of multi-resolution models, integrated verification and validation, placing M&S tools and systems under knowledge-based control, and a universal framework for model construction. Knowledge management refers to a deliberate approach to recognizing knowledge as a resource to be managed in a corporate environment (House and Bell, 2001~. Its advent is an important development for M&S in the enterprise context, since models are an important form of corporate knowledge. Moreover, knowledge management can provide a broader framework in which M&S is fed knowledge from other sources and, in turn, generates new knowledge as an output. For example, knowledge management could help couple functionality that is specified at a high level of abstraction to detailed design. Basic research is needed here, since it could significantly reduce modeling time and ensure consistency in system acquisition.

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60 . MODELING AND SIMULATIONIN MANUFACTURING CONCLUSIONS On the basis of the barriers to widespread use of M&S in industry identified above and the analysis of the IMTI vision of future M&S product and process applications, this NRC committee identified the following needs for improvement in M&S technologies for product and manufacturing process design applications: . Increased capabilities to reuse successful product design applications for other problems or to integrate successful product design applications into larger systems; product model standards modularity of M&S components, and improved comparability; Improved integration of models; improved CAD software that enables use of product models in performance simulations of dynamic-use conditions; improved interoperability; Improved model validation and verification methods to increase reliability and robustness to uncertainty of product models; integrated verification and validation of models and simulations; Improved parametric modeling, variational analysis, and probabilistic design to increase use of M&S analysis in design process; Universal framework for model construction that incorporates both stochastic and deterministic models to optimize manufacturing parameters. The committee identified needs for improvement in M&S technologies for process applications, including the following: Improved capabilities for integrating systems, such as improved methods for understanding systems behavior and improved integration of performance modeling and effectiveness simulations with product modeling and engineering simulations; . Continuity of models across life-cycle phases; · Improved heuristic search methods to decrease simulation times and to support an integrated design system of business, product, and process models; · Knowledge-based control of M&S environments to improve testing and evaluation.

M&S IN COMMERCIAL MANUFACTURING TABLE 3-3 M&S Needs for Commercial Manufacturing 61 Category of Need . Product and manufacturing Specific Needs process design Process applications Product development process Increased reuse capabilities Improved integration of models Improved model validation and verification Improved design modeling methods Universal framework for model construction Improved system integration Continuity of models across life cycle Improved heuristic search methods Improved testing and evaluation Encourage use of M&S in product design, testing, and evaluation Finally, the committee identified the need for nontechnical improvements in the product development process to encourage, rather than discourage, full use of M&S analysis capabilities in design and full use of M&S capabilities in product testing and evaluation (see Table 3-3~.

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The Committee on Modeling and Simulation Enhancements for 21st Century Manufacturing and Acquisition was formed by the NRC in response to a request from the Defense Modeling and Simulation Office (DMSO) of DOD. The committee was asked to (1) investigate next-generation evolutionary and revolutionary M&S capabilities that will support enhanced defense systems acquisition; (2) identify specific emerging design, testing, and manufacturing process technologies that can be enabled by advanced M&S capabilities; (3) relate these emerging technologies to long-term DOD requirements; (4) assess ongoing efforts to develop advanced M&S capabilities and identify gaps that must be filled to make the emerging technologies a reality; (5) identify lessons learned from industry; and (6) recommend specific government actions to expedite development and to enable maximum DOD and U.S. commercial benefit from these capabilities. To complete its task, the committee identified relevant trends and their impact on defense acquisition needs; current use and support for use of M&S within DOD; lessons learned from commercial manufacturing; three cross-cutting and especially challenging uses of M&S technologies; and the areas in which basic research is needed in M&S in order to achieve the desired goals for manufacturing and defense acquisition.

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