2
Framework for Virtual Design and Manufacturing

Product development is a complex process involving a multitude of tools and technologies as well as nontechnical issues. In the past, there was considerable optimism that technological advances would solve all engineering and manufacturing problems. Today we understand that the integration of technical and nontechnical approaches is necessary, especially where people with different skills and responsibilities need to reach accommodation in complex domains.

In this report, the term "virtual design and manufacturing" is used to describe the use of information technologies (such as databases, rapid network-driven communication, and modeling and simulation software) to aid in the creation of products and systems.1 "Manufacturing" refers broadly to all the activities required to conceive a product that will meet the needs of a customer, convert those needs into a producible design, deliver products to the customers, support products in the field, upgrade or repair them as needed, and eventually retire and recycle them. This broad definition provides the opportunity to fully exploit the emerging virtual technologies to their full potential.

To give an example of the scope of manufacturing activities, out of a total of about 250,000 employees worldwide the Ford Motor Company has more than 30,000 engineers and skilled designers involved in the design of its products and manufacturing systems. Bringing a new car from concept to production can take 48 months and cost upward of $3 billion. In the process, a company like Ford must make use of many computer-powered tools to determine what customers want and whether its engineering and manufacturing processes will do the job.

This chapter briefly describes the steps in this process in a generic way and identifies the virtual manufacturing tools in use. It also predicts the potential for performing more of the steps virtually, that is, by substituting simulations for physical prototypes, and distance communication for face-to-face meetings. Particular steps needed in the mechanical parts and electronics industries are described separately where they differ substantially from a generic template.

It is unlikely that every step in such a complex process as design will ever be completely virtual because many critical trade-offs and decisions must be made based on experience and judgment. But it is likely that computer-based tools could aid even these unpredictable steps. To accomplish this, it is also necessary to take account of the nontechnical aspects of manufacturing, such as program management and managerial methods and incentives, which are necessary in order to make the best use of new design technologies.2

1  

"Virtual" is defined broadly here to include any method that involves computing, electronic data, or communication.

2  

Drew Winter, "Shrinking Product Development Time," Ward's Auto World, June 1, 2003. Available at: http://www.wardsauto.com/ar/auto_shrinking_product_development/. Accessed March 2003.



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 11
Retooling Manufacturing: Bridging Design, Materials, and Production 2 Framework for Virtual Design and Manufacturing Product development is a complex process involving a multitude of tools and technologies as well as nontechnical issues. In the past, there was considerable optimism that technological advances would solve all engineering and manufacturing problems. Today we understand that the integration of technical and nontechnical approaches is necessary, especially where people with different skills and responsibilities need to reach accommodation in complex domains. In this report, the term "virtual design and manufacturing" is used to describe the use of information technologies (such as databases, rapid network-driven communication, and modeling and simulation software) to aid in the creation of products and systems.1 "Manufacturing" refers broadly to all the activities required to conceive a product that will meet the needs of a customer, convert those needs into a producible design, deliver products to the customers, support products in the field, upgrade or repair them as needed, and eventually retire and recycle them. This broad definition provides the opportunity to fully exploit the emerging virtual technologies to their full potential. To give an example of the scope of manufacturing activities, out of a total of about 250,000 employees worldwide the Ford Motor Company has more than 30,000 engineers and skilled designers involved in the design of its products and manufacturing systems. Bringing a new car from concept to production can take 48 months and cost upward of $3 billion. In the process, a company like Ford must make use of many computer-powered tools to determine what customers want and whether its engineering and manufacturing processes will do the job. This chapter briefly describes the steps in this process in a generic way and identifies the virtual manufacturing tools in use. It also predicts the potential for performing more of the steps virtually, that is, by substituting simulations for physical prototypes, and distance communication for face-to-face meetings. Particular steps needed in the mechanical parts and electronics industries are described separately where they differ substantially from a generic template. It is unlikely that every step in such a complex process as design will ever be completely virtual because many critical trade-offs and decisions must be made based on experience and judgment. But it is likely that computer-based tools could aid even these unpredictable steps. To accomplish this, it is also necessary to take account of the nontechnical aspects of manufacturing, such as program management and managerial methods and incentives, which are necessary in order to make the best use of new design technologies.2 1   "Virtual" is defined broadly here to include any method that involves computing, electronic data, or communication. 2   Drew Winter, "Shrinking Product Development Time," Ward's Auto World, June 1, 2003. Available at: http://www.wardsauto.com/ar/auto_shrinking_product_development/. Accessed March 2003.

OCR for page 11
Retooling Manufacturing: Bridging Design, Materials, and Production FIGURE 2-1 Simplified diagram of activities in product development. This diagram denotes the main activities in the life cycle of a product from conception to use and retirement, shown as a time sequence with feedback at various stages. Along the bottom are examples of computer-based tools that are used to varying degrees in each stage. Note that while these steps are shown as occurring serially, significant overlap is possible. PROCESSES AND TOOLS COMMON TO MANY INDUSTRIES Figure 2-1 presents the basic steps in developing a new product or service.3 Along with these steps are shown a few of the computer-based tools that are in use, both commonly and in the most advanced companies and government laboratories. The basic steps are as follows:4 Determine the customer's needs. This often involves negotiations and reality checks, which can be aided by simulations and other computer-based tools. Design products and services, including: Convert the customer's needs into engineering specifications, including requirements for production speed and accuracy. Engineering and manufacturing models and simulations are used routinely in this and the following steps to verify performance, predict failure modes, and match production plans and equipment to requirements. Specify the requirements for reliability, maintainability, and other customer use and life-cycle support requirements. Determine that the specifications can be met by manufacturing processes or suppliers; modify the design as necessary to be sure. Plan manufacturing operations and equipment. Launch the product into production. Monitor performance of the product in use and update designs. There is a growing similarity between DoD systems acquisition and commercial industry's methods of developing new products. In particular, where commercial industry seeks to 3   Even though services are developed via a process broadly similar to products, this report concentrates on products. 4   Karl Ulrich and Steven Eppinger, Product Design and Development, Third Edition, McGraw-Hill, New York, N.Y., 2004, p. 9.

OCR for page 11
Retooling Manufacturing: Bridging Design, Materials, and Production understand customer needs, the DoD seeks to understand potential threats, missions, and warfighting plans. Where commercial industry differs from past DoD methods is that commercial industry considers cost and cost–performance trade-offs much earlier in the product development process. The DoD's recent interest in this approach is evidenced by initiatives like cost as an independent variable (CAIV), and driven by increased awareness of affordability issues. Figure 2-2 goes into more detail about how a product and its processes are designed. This figure follows the motif of the "system engineering V," which is used by many companies to explain and manage their product development process.5 Time flows from left to right, while the level of detail increases downward, as does the level of decomposition of the product into systems, subsystems, and parts. Top-level requirements are broken down into requirements on subsystems and parts. Methods of determining whether these items will deliver their requirements are also designed at the same time. As each item is designed, it is compared to its requirements, and occasionally some redesign is necessary. As more items are completed, they are integrated, and more verification tests are performed. Again, some redesign may be needed. At the highest level, the complete product is subject to validation tests.6 Ideally, the lessons learned during this complex process, as well as data from the field, are recorded and applied to the next product. Modeling and simulation play large roles on both sides of the V. Both the product and the various production processes are designed and tested using computer models. Tests and prototypes produce data that are used to improve the design and the accuracy of the simulations. Data from users and repair activities (not shown) also contribute to learning and improvement of models, such as data on long-term durability and safety. As indicated by the colors in Figure 2-2, new software tools are needed (red) for many of the required product development activities. For activities where software tools are emerging (yellow) or are common (green), the tools need to be made interoperable to improve the integration of design and manufacturing. A number of activities that support product development and are listed across the bottom of the diagram also make use of computer models and simulations. The status of these tools and methods is discussed in detail in Chapter 3. It is important to understand that the required tools cover many nontechnical domains such as human resource management, program management, cost analysis, market analysis, and so on. Some, like immersion or virtual reality caves, are used to help customers decide what they really want and whether they have asked for self-consistent requirements. Others, like cost models, help customers decide how badly they want certain features or performance metrics. Elsewhere in this report it is noted how vital it is to define requirements carefully with the participation of the customer, so advances in tools of this type will be particularly important.7 The degree to which the process illustrated in Figure 2-2 is actually used varies from industry to industry, and from company to company within each industry. As industries become more confident in their ability to accurately simulate the behavior of their products, fewer physical prototypes will be needed for validating a product's design. The potential for elimination of prototypes also varies from industry to industry. In hardware systems, system complexity 5   Andrew Sage and William Rouse, Handbook of Systems Engineering and Management, John Wiley and Sons, New York, N.Y., 1999, p. 78. 6   "Verification" usually refers to tests to see that a product meets specifications. "Validation" seeks to determine that the customer is satisfied and that the correct specifications were in fact incorporated into the product. 7   Considerable debate surrounds the question of whether requirements should be complete and clear before product development begins. When a product's technologies are well understood and the market's needs are evolving slowly, then efficient and effective product development benefits from an up-front declaration of requirements. When the technology is explorative and the market is changing rapidly, requirements are hard to clarify. In this situation, a development process that can quickly adapt to changes is often preferred.

OCR for page 11
Retooling Manufacturing: Bridging Design, Materials, and Production FIGURE 2-2 Flow diagram of product–process development. This diagram seeks to capture series and parallel activities at several levels of detail over time during the development of a product. Some of the required activities are listed along the arms of the V while others, not associated with particular phases of the process, are listed across the bottom. Software tools are not available (red) for many of the required product development activities. For other activities, software tools may be emerging (yellow) or common (green) but are not interoperable or are used inefficiently. leads to uncertainties in materials properties and processes and can contribute to unexpected behavior. Prototypes may be needed to detect some of these uncertain events. Regulatory agencies often require safety tests prior to the production and sale of certain products (e.g., automobiles and aircraft). Microprocessors can be completely designed in software using design rules, once the production processes have been verified on test chips that have the required device sizes, materials, and line widths and spacing. Verification of these processes still requires hardware. In software development, prototypes are used to test the new software against customers' expectations. Thus, even if programming aids eliminate bugs, there will still be a need for prototypes. In some industries, development of prototypes and computer simulations go hand in hand. In aircraft jet engine design, simulations are used to make conceptual, preliminary, and detailed designs of fans, compressors, combustors, and turbines. Each of these components is built in prototype form and tested, as is the final engine. These tests not only determine whether the engine meets its requirements but also provide essential information for updating the

OCR for page 11
Retooling Manufacturing: Bridging Design, Materials, and Production simulations for use on the next engine.8 Further, Thomke argues that every experiment, whether it is a physical prototype or a computer simulation, has the potential to provide learning and knowledge as long as the opportunity is taken.9 Thus, in the future, one should expect that simulation and experimentation would continue to be partners in product development. The main differences between prototypes and simulations are as follows: Prototypes provide the ability to detect issues that are not contained in the models or simulations. Simulations can provide information earlier in the design process. Simulations reduce the marginal cost of experimentation to the point where thorough exploration of the design options becomes economically feasible. The main drawback in using simulations instead of prototypes is that simulations are likely to be less accurate, something that must be traded off against early availability of the information. Even so, accurate prototype results are often available much too late to be of any use in a tightly scheduled development project. Thus, a judicious combination of simulations and prototypes for validation and verification is the most effective approach. Models and simulations are also used to help design and operate the design processes themselves. Virtual methods include dynamic project management simulations, engineering resource and scheduling allocation algorithms, and methods for tracking requirements and their achievement. Software is also used to manage the huge amounts of data associated with design of a product and its processes. It is estimated that for every geometric feature on a mechanical part that is made, there are upwards of 1000 geometric features on manufacturing equipment and supporting apparatus.10 Bill of materials systems are used to manage the data. A typical automobile has about 10,000 parts containing as many as 10 geometric features each. A Boeing 777 has more than 100,000 part numbers. Thus the amount of data needed to represent just the mechanical parts is huge. In addition there are miles of wire and pipes in aircraft and ships, all of which are represented by layout diagrams, circuit analyses, parts lists, and so on. All of these must be represented in databases so that the systems can be simulated and their production can be planned. At present most of these databases interoperate only on nontechnical data such as part numbers, and even these can be inconsistent. There is no common data architecture that can hold and exchange technical information such as part shapes, bills of materials, product configurations, functional requirements, physical behavior, and much else that is required for deep exploitation of virtual manufacturing. Specific opportunities for bridging design and manufacturing occur at many places in the process illustrated in Figure 2-2. At the highest levels, the design must accommodate available processes and methods used by the manufacturing prime contractor and its suppliers. Product planners need to assess available factories to determine if they have the capacity and flexibility to meet future needs. Tests and validation procedures need to be in place or designed to ensure that the product will perform as required. At lower levels of product decomposition, individual parts and assemblies must be designed so that they can be produced efficiently, economically, and within tolerances. Fabrication and assembly processes must be designed to 8   Geoff Kirk, Chief Design Engineer, Commercial Engines, Rolls Royce, "Every Engine Attribute Has Its Model," presentation at University of Cambridge, U.K., July 10, 2003. 9   Stefan Thomke, Experimentation Matters: Unlocking the Potential of New Technologies for Innovation, Harvard Business School Press, Boston, Mass., 2003. 10   William Powers, VP of Research, Ford Motor Company, Keynote speech to Japan–USA Symposium on Flexible Automation, Boston, Mass., July 7, 1996.

OCR for page 11
Retooling Manufacturing: Bridging Design, Materials, and Production meet the requirements for cost, speed, and capability. It commonly occurs that desired requirements cannot be met in a timely or economic manner with existing processes and facilities. For this reason, requirements often must be revised. Understanding how to arrive at a suitable compromise is very difficult, especially because it involves managerial, organizational, and economic consequences. It is also essential to be able to discover the need for revision early in the product development process. Otherwise, very costly design or manufacturing changes will be needed, delaying the deployment of the product and increasing its cost. Accomplishing bridging requires exploring a huge space of interacting design and manufacturing options.11 Virtual tools are the only way of supporting a thorough exploration. Thus virtual tools play important or essential roles in conceptualizing products, conducting the design, planning the production, ensuring manufacturability, and carrying out production, deployment, and field management of the product. PRODUCT DEVELOPMENT, MANUFACTURE, AND LIFE-CYCLE SUPPORT ACTIVITIES Table 2-1 lists a number of activities involved in creating, producing, and supporting a product (expanding on the activities shown in Figure 2-2). While details may differ, most of these steps are carried out in every industry, even including those industries whose outputs are services rather than artifacts. The steps cover both engineering and managerial activities. The table comments on the way the step is or has been done nonvirtually and how it might be done using computing or electronic data or communication. To support ongoing activities of engineering, computer-aided design systems and allied analysis systems can look at stress, fluid flow, heat transfer, mechanical motions, electronic phenomena, and so on. Examples include: an aircraft that is analyzed to see whether the landing gear will move smoothly into and out of the storage bay; an automobile that is virtually crash tested; a helicopter blade that is analyzed for adverse fatigue; and a microprocessor that is analyzed to determine how much heat it will generate and whether information can be transferred fast enough between its computing elements. In addition to virtual tools to help design the product functionally, there are ways to evaluate the designs from other points of view. One of the most important methods is design for manufacture or assembly. This type of evaluation helps engineers to see where trouble might arise during production and can help them simplify the design. Close cooperation with manufacturing and assembly experts is needed to ensure proper use of these tools. Other tools help predict failure modes of the product in use as well as issues that can arise during manufacturing. While many tools exist, experienced people generally conduct most of this type of activity manually. In addition, existing tools are mostly stand-alone and thus prevent essential integration and management of complex interactions between them. 11   Elsewhere in this report, this space is referred to as a "design space" or a "trade space."

OCR for page 11
Retooling Manufacturing: Bridging Design, Materials, and Production TABLE 2-1 Activities Involved in Creating, Producing, and Supporting a Product Step or Process Non-Virtual Methods Virtual Methods Obtain customer needs, including performance, cost, and schedule expectations Interviews, observations Web questionnaires, very realistic simulations combined with self-design Develop performance requirements Interviews, observations Requirements-tracking software combined with tools for tracking interactions Expand requirements to include such things as reliability, flexibility, and expectations regarding upgrades Interviews, review of past product needs Data mining, lessons-learned databases Develop concepts Sketches on paper, brainstorming Digital sketches, data searches, cognitive aids, videoconferences, knowledge-based tools Generate functional and physical decompositions to meet performance and capabilities requirements Sketches, notes, brainstorming, technology surveys, interviews Decomposition simulations, links to technology data, links to interaction data; architecture evaluation systems Assign quantitative specifications to top-level requirements Calculations from requirements; existing design histories Computer simulations of system and component behavior; simulations of user environment Assign targets to distributed requirements such as cost, weight, reliability, safety, and durability Existing stand-alone calculations, past field data, guesses Preliminary cost models, technology histories and roadmaps, tabulated field data Identify top-level risks: maturity of the technology, performance, cost, schedule Past field data, data on past similar products, discussions with experts Risk models based on data Assess in-house and vendor design, modeling, testing, manufacturing, and assembly capabilities Internal audits, use of ISO 9XXX protocols Real-time data on machines, processes, statistical process control, process capabilities and costs Decide what will be made in-house and what will be outsourced Internal audits Strategic and tactical models Identify critical vendor–partners and long lead items Discussions with experts, past project data None Generate program plan with tasks, schedule, information exchanges, design reviews Gantt charts, precedence diagrams, existing project templates Task and behavior interaction models that predict possible rework and schedule delays

OCR for page 11
Retooling Manufacturing: Bridging Design, Materials, and Production Step or Process Non-Virtual Methods Virtual Methods Flow top-level requirements down to subfunctions and subsystems Analysis by experts Detailed multifunctional models of technical behavior Generate derived requirements defined as consequences of top-level decisions but not requested by customers Analysis by domain experts, subsystem engineering None Identify risks at subsystem levels and below Analysis by domain experts None Generate verification and validation plans Analysis by domain experts None Do detailed design of components and subsystems Drawings CAD plus functional performance simulations, tolerance analysis software Determine that detail design specifications can be met by available and economical processes Discussions between domain experts in engineering and manufacturing Simulations, process algorithms, cost analysis and comparison algorithms, process capability data Identify and evaluate suppliers, get and evaluate bids Request qualifications, past experience Use virtual data exchange, online bidding and negotiation Generate manufacturing, assembly, and test plans Use of manually collected data from past projects, standard templates, vendor capabilities, and domain experts Simulations and cost-estimating systems, discrete-event simulation Verify and validate component and subsystem performance Multiple tests, including accelerated life prototypes Cross-functional factory simulations, stress analysis software, heat simulations Design manufacturing and assembly systems to make, assemble, and test each part and assembly Use experts and domain specialist suppliers to physically make, assemble, and test each part and assembly Use simulations of materials processing, material handling, assembly, human operators Obtain and train employees Drawing from existing staff, recruitment, direct training Use models to choose the right people, and simulations and videos to train them Integrate product subsystems and verify performance Testing of subsystems, prototype assemblies, mockups 3D solids CADCAM plus CFD, computer analysis and simulation Install and validate manufacturing and assembly systems Installation and validation done on-site and reworked until they are correct Simulation and validation tools to check correctness and safety

OCR for page 11
Retooling Manufacturing: Bridging Design, Materials, and Production Step or Process Non-Virtual Methods Virtual Methods Integrate product systems and validate that customer needs have been met Testing of product, identification of problems, discussions and decision making with customer Use tools for decision making, utility balancing, budget projections, time estimates Begin production, find problems, and fix them Production by engineers and vendors on site Data acquisition, comparison of simulations and actual operations of systems and machines Operate and improve manufacturing, logistics, assembly processes, and systems Application of lean manufacturing principles by supervisors, manufacturing engineers, and operators Full online monitoring and analysis of processes, measurements, and test results Field product, gather user and repair data, manage product operation, and monitor health Read warranty reports, query repair staff, construct lessons-learned databases Automated monitoring and statistical analyses, remote sensing and diagnosis, remote repair Manage product upgrades Read warranty reports, query repair staff, construct lessons-learned databases Automated product registry Manage recall, safety upgrades, and retirement of products Mandated by law for some products and is done manually None SPECIFIC ACTIVITIES IN MECHANICAL PARTS INDUSTRIES The mechanical parts industries make diverse products with multiple modes of energy, including mechanical motions, combustion, fluid pressure and flow, and so on. Thus the term "mechanical parts" is used for convenience rather than to limit the phenomena involved. In fact, it is the multiplicity of phenomena that makes simulation of these products difficult.12 In many cases the state of the art is a set of individual simulations whose interpretation involves human expertise to combine the separate results. The kinds of things simulated include the following phenomena: Mechanical vibration, noise, and acoustics of machinery, including interior cabin noise in aircraft and automobiles Fluid flow in compressors, pumps, and other aerodynamic surfaces, to determine mechanical and thermodynamic efficiency Fluid noise, such as wind rushing over the exterior of an automobile or fluid flowing in pipes in a submarine Optical ray tracing in telescopes, gun and missile sights, and cameras Kinematics of mechanisms such as car engines, aircraft landing gear, telescope mounts, 12   Elsewhere in this report, such multiple phenomena, including electrical, electromagnetic, and other phenomena, as well as the disciplines that deal with them, are referred to as "multiple domains."

OCR for page 11
Retooling Manufacturing: Bridging Design, Materials, and Production and suspensions of trucks and tanks Stress and strain, including prediction of sources of cracks and other fatigue phenomena Production processes, including solidification, deformation, machining, and joining Motions of production equipment such as robots and assembly setup, to determine feasibility of geometry and timing Motions of logistical equipment such as forklifts and conveyors that transport materials in factories, to determine production capacity Motions and loads on people while doing physical work, to determine timing and avoid injuries, or while operating the product, to study ergonomics The committee agrees that the most accurate and definitive simulations are those that involve only geometry. However, some mixed phenomena simulations are also remarkably accurate. For example, the fuel consumption of a jet engine can be predicted within about 2 percent using simulations that involve mechanical, aerodynamic, and combustion phenomena.13 The crashworthiness of a car can be well predicted for frontal collisions. These simulations predict crushing patterns of the structure as well as the path taken by the engine as the front crushes. The point at which the wing of the 777 broke under test to destruction was predicted to the extent that the failure load, location of failure, and kind of failure all were correct.14 But many of these simulations are purposely built by experts and are honed over many years, making them quite expensive and accessible only to large companies. What is needed is a set of robust, verified, and validated simulation codes, accessible to nonexpert users. Specialty codes exist for the various aspects of the simulations listed above. A significant improvement in design could be achieved if each of these codes could use a common database describing product geometry and other essential data. Longer range, what is needed is consistent engineering representations of a variety of physical phenomena so that different simulations do not have to be used for each phenomenon separately. Only then will fully functional simulations of multiphenomena systems be possible. Furthermore, models of production processes today encompass what happens in a restricted area of a factory. Broader models of entire factories are made less often, and models of entire supply chains are rarer still. Commercial software provides some facilities for managing existing supply chains and for passing orders and payments back and forth, but these are more adapted to supply chain operation than to design. SPECIFIC ACTIVITIES IN ELECTRONICS PARTS INDUSTRIES Electronics parts industries cover the spectrum from such discrete devices as capacitors and resistors through integrated semiconductor devices and up to such complete systems as microprocessors. Modeling, simulation, and sensing requirements therefore span a broad spectrum of activities across multiple levels. These include a wide array of techniques for modeling the performance of individual semiconductor devices as well as simulations of entire systems. Today's products could not be designed without these simulations and design aids, but there is additional potential for significant interaction between some technical domains. Opportunities arise in the following areas: 13   Jon Niemeyer and Daniel Whitney, "Risk Reduction of Jet Engine Product Development Using Technology Readiness Metrics," ASME Design Engineering Technical Conference, paper no. DETC2002/DTM 34000, September 29–October 2, 2002. 14   Karl Sabbagh, 21st Century Jet: The Making of an Airplane, Pan MacMillan Australia, Sydney, N.S.W., 1995.

OCR for page 11
Retooling Manufacturing: Bridging Design, Materials, and Production Materials—prediction of physical properties of materials and their resulting electrical properties Semiconductor wafer fabrication—crystal growth, cutting/sawing operations, grinding, polishing, cleaning Oxidation processes—oxidation furnaces, wet/dry oxidation Deposition processes—physical vapor deposition, chemical vapor deposition, sputtering Lithography—equipment, photoresist characteristics Etching processes—chemical/wet etching, plasma/dry etching, reactive ion etching Diffusion—chemical/vapor, ion implantation, doped oxide Interconnect—mechanical, electromagnetic, thermal, die attach/wire bonding Circuit level modeling—active, passive, and parasitic circuit elements Package level—mechanical, electrical, thermal, radio frequency, digital Board level—reflow process, screen printing, component placement, routing, layout, layers, substrates (e.g., organic, flex, ceramic, glass), component and board test System level—factory scheduling and resource management, acoustics, safety, radiation, network, yield, supply chain, system test MODELING AND SENSING Simulations will always be limited by the input data they use. Let us consider this in the context of production processes that transform raw materials into another form. Examples include: casting, where chemical composition is set by alloying ingredients in the liquid state and form is set by solidification in a mold; deformation processes such as forging and sheet metal forming, where a combination of thermal and mechanical forces shape an initial blank; and machining, where tools remove material to produce a final shape. Simulation of each of these processes requires detailed models to predict materials' response to thermal and mechanical loads. Further, the process simulations also require models for the transfer of heat and mechanical forces across the interface between the part and tooling. The quality of the simulation results depends on the quality of these input data. In most cases, the interfacial properties are not well enough understood to be completely reliable. Modelers generally lump all unknown variables into "interfacial transfer coefficients," which are meant to characterize the transport processes. It is important to understand that simulations will never be able to completely capture these interface characteristics without external data. For example, both interfacial heat transfer and interfacial friction properties depend on the detailed distribution of asperities on the contacting surfaces, surface contamination, and a variety of other surface properties that change from part to part, and perhaps moment to moment, in real production processes. Simulations can be used effectively in such an environment to assess the sensitivity of the design to variations in parameters whose values are uncertain. Further, they can be used to guide the design process into those regions of the design space where the sensitivity is low. This process can be formalized mathematically, and the codes can be used to produce an optimal design, where such sensitivities are minimized. The implementation of optimal design

OCR for page 11
Retooling Manufacturing: Bridging Design, Materials, and Production methods early in the design process represents a significant opportunity to improve design methods using simulations. Such case studies are presented in Chapter 3. In most production parts, however, the final product will still depend strongly on the interfacial processes. Sensors can be deployed in prototypes (or in production) to provide measurements that can be used with the aid of simulations to characterize those properties that are uncertain. The simulation results can be used in turn to control the process. For example, interfacial heat transfer characteristics are very important in many solidification processes. The microstructure of the product depends on the local thermal history, which can depend in a very complicated way on the surface heat transfer characteristics. Since the interfacial characteristics cannot be completely predicted, temperature sensors embedded in the mold can be used to "tune" the simulation parameters. The data from such sensors can also be used in conjunction with modeling to provide process control. In a similar way, temperature sensors can be embedded in machine tools to determine tool wear. The ability to use sensors to detect the process is still rather limited. Temperature and displacement can be measured rather easily using a variety of well-established techniques. Sensors that measure the condition of a part, such as internal defects and cracks, would greatly improve the reliability of parts in service.