2
Integrated Product and Process Design
Information age manufacturing begins with information age design. The design process for products and the processes by which they are produced involve compiling and understanding the products’ requirements, converting the requirements into engineering specifications, and producing plans that marshal the materials, equipment, and people needed to make and deliver the products.
Central to the 21st century design environment will be product and process modeling techniques that specifically and unambiguously define product and process attributes. Such modeling techniques would thus enable designers to determine production requirements and communicate them to other designers and to individuals upstream (e.g., in marketing) and downstream (e.g., in production).1
Also, such modeling techniques would eliminate or minimize the need for physical prototypes and construction aids. Production of physical prototypes and aids for use in functional testing, tool construction, and related activities introduces more lead time, cost, and potential inaccuracies into the development process and can cause unnecessary iterations when design changes cause models and aids to get out of synchronization with the product. In programmable electronic products, such modeling allows the supporting software to be tested on early versions of the hardware, rather than waiting until hardware development is complete.2
New design challenges are presented by (and are enabling) new product trends, such as increasing complexity, shrinking size, growing numbers of parts, and increasing technological diversity. As a result, the amount of knowledge and data a designer must synthesize, compare, trade off, and optimize is rapidly becoming more than an individual can comprehend. It is already beyond human comprehension for some complex products, such as VLSI chips.3
Running through all of design and production are major issues of scale-up and complexity. Any research that is done must take scale and complexity into account and not expect that they will be included at a later stage of the development of any proffered solution to any aspect of these problems.
To enable the designer to overcome these challenges, the information age integrated product and process design environment must help the designer to link product design and manufacturing to an unprecedented extent with minimal use of physical prototypes or construction aids. Specific capabilities hardly possible today include the ability to
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Create a concept of a product and make extensive simulations of its behavior without specifying all of its details;
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Explore, trace, and compare the manufacturing cost, quality, and performance implications of design decisions without specifying the design in full detail;
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Obtain a full understanding of the product’s behavior modes, including major off-nominal variant behaviors that may seriously affect performance, product quality, environmental quality, or user safety;
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Express the desired functions of the product in a translatable and analyzable format and thus permit function descriptions and mapping of functional requirements onto engineering entities within the product, including decomposing functions into subfunctions and system or engineering entities into subentities;
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Identify the right manufacturing, assembly, and test processes for creating and verifying the elements of the product and matching them to the functional behavior specifications, and predict the expected variability of the resulting manufactured entities during design;
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Obtain current information characterizing manufacturing and assembly processes, including variation expectations, not only for individual process machines but also for entire production systems; and
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Achieve the above product definition depth through affordable computer assistance that is flexible enough to accommodate design innovation.
Creating a design environment with such functionality presents a challenge in itself, as well as a number of research opportunities. These opportunities are listed in Table 2.1 and are discussed in the remainder of this chapter.4
MANUFACTURING-SPECIFIC RESEARCH
Design by Function
Currently, a designer specifies products in terms of production-oriented parameters such as length of shafts or diameters of bearings. In the design environment envisioned for 2010, the designer will be able to specify products in terms of function and performance directly in function-relevant parameters, such as the load capacity and life of the bearing or the allowed vibration frequencies and minimum fatigue resistance of the shaft. Design by function is now possible only in a few domains, such as application-specific integrated circuits.5
Research is needed to address the following design-by-function needs:6
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Support of functional descriptions in rough conceptual terms;
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The ability to simulate meaningful behavior at the conceptual level;
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The ability to predict performance or production problems with conceptual-level information;
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Methods for decomposing functions (i.e., a top-level description of what a product should do) and subfunctions (the next level down) and mapping those subfunctions onto system and subsystem elements (i.e., deciding what physical parts of the product will accomplish them);7
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Methods for quickly converting functional descriptions into system space allocation and part geometry; and
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Methods for predicting production costs and possible problems.
TABLE 2.1 Product and Process Design
Subject Area |
Example of Research Needed |
Design by function |
Relation of geometry to function Functional simulation |
Product-process data model |
Data descriptions for many physical processes and entities in a unified form Descriptions of design interactions, analyses, and process steps integrated with product geometry and function descriptions |
Capture of nominal and variant behavior of products and processes in one model |
A mathematics of variation for performance modeling Descriptions of product function and variants directly related to descriptions of geometric or material variations |
Design methods and tools for groups of parts and systems |
Decomposition methods to break product concepts into subsystems Subassembly performance models and interface descriptions for joining subassemblies to each other Assembly planning |
Process description languages and models |
Set of process primitives from which process models can be built Languages with syntax checking for formal correctness and logical completeness of process descriptions |
Novel design considerations |
Easy, error-free configuration control at the selling or servicing stage Economical build-to-order in lot sizes as low as one Manufacturing of a robust final product from parts obtained from different sources |
Decision aids |
Data visualization Database searching using geometric features, performance criteria, or process descriptions Intelligent advisors |
Geometric reasoning |
Visualization tools |
Knowledge and information management |
Systems that capture corporate memory and knowledge Systems that support corporate learning Techniques for handling data legacy issues Systems that record design history and rationale |
Product-Process Data Model
Current data models capture only geometry. The envisioned design environment will support a “product-process data model” that captures function and relates it to geometry, manufacturing, and assembly processes, interactions with the user, and ultimate disposal or recycling. Specifically, the product-process data model will have the following capabilities:8
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Describe function, model variations, and families of the product;
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Describe information on which process models can work;
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Represent performance, geometry, and process requirements in ways that are readable by design tools and practitioners in the allied domains of process equipment design and shop floor planning and operations, as well as by designers in other companies or in other technical domains;
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Capture input as the product realization process proceeds so that the process can be improved; and
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Contain systematic ways of relating function to geometry; for example, it may be feature-based.9
Data models should be capable of representing the product or component from many different views at different stages of design, manufacture, and use. The product designer should be able to view its geometry, tolerances, assembly problems, and repair scenarios. The process designer should be able to study different fabrication methods and assembly sequences, comparing their cost, tolerances, and final quality. The production planner should be able to price different sources for material and place orders. The process engineer should be able to log process improvements or design changes so that the product designer can learn and do better. At present, no such data model exists, nor are there adequate methods for supporting these activities.
Ideally, the data model’s function and geometry will be mutually convertible from one to the other. Although such convertibility could be cost-prohibitive in some cases, it would reduce storage requirements, because compact functional descriptions could be stored and voluminous geometric descriptions could be generated from the functional descriptions when needed.
Capture of Nominal and Variant Behavior
In addition to capturing function and relating it to geometry, product descriptions and the process descriptions of the envisioned product-process data model will capture in a unified way both the nominal behavior of the product and the main off-nominal behaviors, or variants. Nothing like this is currently possible.
The need is illustrated by the example of tolerances. Currently, there is no single way of expressing product function specifications and limits that translate directly into the performance variations of the production equipment that will create the product. If the designer wants output power to be within ±x percent, he or she must express this as a requirement that some set of material or geometric properties lie within ±y percent of nominal values. The relationship between the power and the properties is usually difficult or impossible to establish conclusively, and whether a process can deliver the properties is often indeterminable as well. Consequently, it is difficult or impossible to determine whether the right set of processes and tolerances has been selected to deliver a specified range of performance variations.10
Design Methods and Tools for Groups of Parts and Systems
Overlapping the need for models to capture nominal and variant behavior is the need for methods or tools to handle groups of parts such as assemblies, subsystems, product families, made-to-order configurations, and selected combinations of parts that create different product models by virtue of which parts are selected.
Again, tolerance issues illustrate the need. Although the support for addressing tolerances for single parts is deficient, methods and tools to assist the designer in dealing with tolerance implications for assemblies are virtually nonexistent. Combinatorics and scale-up barriers defeat current approaches.11
The envisioned design environment will support design methods and computer tools adapted for the design and creation of groups of parts or systems, in addition to individual parts. Such methods and tools will enable the designer to divide a product into subassemblies, design optimal in-process test strategies during assembly, and identify assembly sequences that minimize cost, tolerance errors, and part damage during assembly. Also, the methods and tools will include standard design modules and methods that facilitate optimization of part or all of a product for cost and quality. Such optimization requires a deep understanding of specific components and features of the product. Because such understanding is often proprietary to component suppliers, research in this and similar areas of collaborative design must consider nontechnical issues such as intellectual property rights and intercompany data exchange.
Process Description
Critical to all manufacturing operations is the manufacturing process. The process performs the value-added operations to the product that is being produced. To design processes (even to consider product design as a process) and to enable process improvement, a precise way of describing processes is needed. The range of processes that needs to be described includes
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Business processes (e.g., converting a customer order into a list of the required parts, subassemblies, and documentation);
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Design processes (e.g., converting customer requirements into engineering specifications, converting specifications into subsystems, and allocating function to regions of space); and
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Production processes (e.g., moving materials, converting material properties or shapes, and verifying process results).
Current process descriptions generally are made of text that captures only a portion of the required information and are thus ambiguous and incomplete. The envisioned design environment will support a process description that enables the designer to characterize the performance of a process (the efficiency or time of a design process, the quality of a production shop) so that he or she can compare sources, select the right shop to make a particular item, name the right team to do a certain design, and select the right algorithm to do a certain calculation. The process description should be dynamically modifiable so that adjustments can be made as the product realization process proceeds and tolerances can be reduced as processes are improved. Such functionality will enable the process designer to ensure that the required results really will be obtained and will facilitate systematic process improvement.
Process Description Language
The envisioned design environment will support a language to express such process descriptions. This process description language must be translatable across technical domains and have a syntax that enables checking for formal correctness and logical completeness. Also, the language must be able to express not only nominal process behavior but also variant behavior.
Process Description Models
Process description models are critical for the local control and planning of manufacturing operations. Compact, accurate models of spatial and temporal process transformations are critical for both the planning and the control of manufacturing activities. Accordingly, the envisioned design environment will support process models that
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Contain the necessary detail for dynamic control of the individual operations as well as the information required to simulate the operation of the manufacturing system;
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Indicate the effects of perturbing the operational parameters, as well as the effect of complex interactions among processes;
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Indicate the effects of changing endogenous variables in a generic manner; and
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Are environment-independent and yet accommodate environmental specifics as model parameters.
To produce such models, research is needed on process model representation schemata (both aggregate and detailed) and on-line data collection.12
Novel Design Considerations
The envisioned design environment will support product design aspects that are not often associated with design at all, such as designing so that configuration control at the selling or servicing stage will be easy and error-free, build-to-order in lot sizes of one will be economical, or a robust final product can be made from parts obtained from different sources. Research is needed on tools and techniques to enable these new aspects.13
NON-MANUFACTURING-SPECIFIC RESEARCH
Decision Aids
A design decision has several impacts at once, some of which are beneficial and some of which are adverse. Therefore the envisioned design environment will support techniques to express comparisons and trade-offs vividly so that the designer can assess the impact of a wide range of design decisions on the product’s cost, time, or quality.
To produce such techniques, research is needed on decision tools that draw upon the product-process data model and performance simulations of the product being designed, as well as process models and various data on costs and tolerances of different processes. These tools will sort data and models on the basis of criteria supplied by the designer to aid in making comparisons between alternate designs and processes.14
Geometric Reasoning
A generic intellectual activity required by mechanical design is geometric reasoning. A major difference between VLSI design and mechanical design is the degree to which three-dimensional geometric reasoning is fundamental to even the simplest mechanical designs.15 Today, the design process relies on talented individuals to do this reasoning, and that may always happen. But the envisioned design environment will support improved visualization tools or other design aids that will help make this process faster and efficiently achievable by a broader range of people.
Knowledge and Information Management
Basic to design are many issues of data management and of data themselves. The envisioned design environment will include a number of data management methods and tools. First, at the simplest level, the design environment will include ways to capture corporate memory and knowledge so that successors of current designers can tell what knowledge was used, what competitive methods were used, what errors were made, and on what factors success was based. Second, the design environment will have data management techniques that enable corporate learning and consequent improvement of processes. Third, the design environment will have to handle data legacy issues, such as converting data from one computer-aided design (CAD) system to another and preserving old data for decades or more so that they can still be read, edited, and processed. Today, such data are either lost, kept on paper, or accessed in a limited way by old hardware kept on hand for the purpose.16
A fourth, deeper data management issue, one strongly affected by issues of scale-up, is that of recording design history and rationale. Every design is a historical web of decisions that grow out of each other and depend on each other. Revision, whether for correcting an error, absorbing a new outside circumstance, or improving manufacturability, requires unraveling the web to a certain degree. The design selected, the web of decisions leading to it, and “roads not taken” indicate the corporate state of belief at the time the decisions were made and thus form a historic context. The envisioned design environment will therefore provide for recording this context, possibly in the product data model, so that it can be compared with current states of belief as a result of accumulated analyses or new inputs.