Allen C. Ward
University of Michigan
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Research in Engineering Design | 1994
Tzyy-Shuh Chang; Allen C. Ward; Jinkoo Lee; Edwin H. Jacox
Simultaneous engineering processes involve multifunctional teams; team members simultaneously make decisions about many parts of the product-production system and aspects of the product life cycle. This paper argues that such simultaneous distributed decisions should be based on communications about sets of possibilities rather than single solutions. By extending Taguchis parameter design concepts, we develop a robust and distributed decision-making procedure based on such communications. The procedure shows how a member of a design team can make appropriate decisions based on incomplete information from the other members of the team. More specifically, it (1) treats variations among the designs considered by other members of the design team asconceptual noise; (2) shows how to incorporate such noises into decisions that are robust against these variations; (3) describes a method for using the same data to provide preference information back to the other team members; and (4) provides a procedure for determining whether to release theconceptually robust design or to wait for further decisions by others. The method is demonstrated by part of a distributed design process for a rotary CNC milling machine. While Taguchis approach is used as a starting point because it is widely known, these results can be generalized to use other robust decision techniques.
Ai Edam Artificial Intelligence for Engineering Design, Analysis and Manufacturing | 1999
H. Van Dyke Parunak; Allen C. Ward; John A. Sauter
MarCon (Market-based Constraints) applies market-based control to distributed constraint problems. It offers a new approach to distributing constraint problems that avoids challenges faced by current approaches in some problem domains, and it provides a systematic method for applying markets to a wide array of problems. Constraint agents interact with one another via the variable agents in which they have a common interest, using expressions of their preferences over sets of assignments. Each variable integrates this information from the constraints interested in it and provides feedback that enables the constraints to shrink their sets of assignments until they converge on a solution. MarCon originated in a system for supporting human product designers, and its mechanisms are particularly useful for applications integrating human and machine intelligence to explore implicit constraints. MarCon has been tested in the domain of mechanical design, in which its set-narrowing process is particularly useful.
Research in Engineering Design | 1995
Tzyy-Shuh Chang; Allen C. Ward
This paper develops a robust and distributed decision-making procedure for mathematically modeling and computationally supporting simultaneous decision-making by members of an engineering team. The procedure (1) treats variations in the design posed by other members of the design team asconceptual noise; (2) incorporates such noise factors into conceptually robust decision-making; (3) provides preference information to other team members on the variables they control; and (4) determines whether to execute the conceptually robust decision or to wait for further design certainty. While Changet al. (1994) extended Taguchis approach to such simultaneous decision-making, this paper uses a continuous formulation and discusses the foundations of the procedure in greater detail. The method is demonstrated by a simple distributed design process for a DC motor, and the results are compared with those obtained for the same problem using sequential decision strategies in Krishnanet al. (1991).
Journal of Manufacturing Science and Engineering-transactions of The Asme | 1999
Jinkoo Lee; S. Jack Hu; Allen C. Ward
Fixtures are used to position and hold parts for a series of assembly operations. In automotive body assembly, these fixtures conventionally have been dedicated, therefore they must be replaced whenever there are model changes in an auto body assembly plant. In recent years, however, the automotive industry has been changing from high volume to small-to-medium volume production per model with an increasing number of models because customer tastes are diversifying. To cope with this change, auto companies need to be capable of producing a variety of models in small-to-medium volume, and they rely on flexible assembly lines and flexible fixtures. These flexible fixtures use robots as programmable fixture elements so that they can be reprogrammed for different stamped sheet metal parts. When designing flexible fixtures, fixture designers need to be concerned with fixture workspaces for a set of different stampings. However, existing fixture design methods address the fixturing of one stamping only. This paper presents a system that fixture designers can use to synthesize flexible fixture workspaces for a set of different stampings. Based on circular workspaces for flexible fixture robots, this system finds optimal workspace sizes and centers on a fixture base plate with a graphical display for visual checking. This system is simple to use and produces results quickly.
Ai Edam Artificial Intelligence for Engineering Design, Analysis and Manufacturing | 1995
William W. Finch; Allen C. Ward
This paper extends previously developed generalized set propagation operations to work over relationships among an arbitrary number of variables, thereby expanding the domain of engineering design problems the theory can address. It then narrows its scope to a class of functions and sets useful to designers solving engineering problems: monotonic algebraic functions and closed intervals of real numbers, proving formulas for computing the operations under these conditions. The work is aimed at the automated optimal design of electro-mechanical systems from catalogs of parts; an electronic example illustrates.
Ai Edam Artificial Intelligence for Engineering Design, Analysis and Manufacturing | 1995
R. Chen; Allen C. Ward
This paper defines, develops algorithms for, and illustrates the utility in design of a class of mathematical operations. These accept as inputs a system of linear constraint equations, Ax = b, an interval matrix of values for the coefficients, A, and an interval vector of values for either x or b. They return a set of values for the domain of the other vector, in the sense that all combinations of the output vector values set and values for A, when inserted into the constraint equation, correspond to values for the input vector that lie within the input interval. These operations have been mostly overlooked by the interval matrix arithmetic community, but are mathematically interesting and useful in the design, for example, of structures.
Ai Edam Artificial Intelligence for Engineering Design, Analysis and Manufacturing | 1995
R. Chen; Allen C. Ward
This paper defines, develops algorithms for, and illustrates the design use of a class of mathematical operations. These operations accept as inputs a system of linear constraint equations, Ax = b, an interval matrix of values for the coefficients A, and an interval vector of values for either x or b. They return a set of values for the other variable that is sufficient in this sense. Suppose that x is an interval of input vectors, and A an interval matrix. Then, one Sufficient-Points operation returns a set of vectors b such that for each b in b, the set of x values that can be produced by inserting all the values of A into Ax = b is a superset of the input vector x. These operations have been partly overlooked by the interval matrix mathematics community, but are mathematically interesting and useful in the design, for example, of circuits.
Ai Edam Artificial Intelligence for Engineering Design, Analysis and Manufacturing | 1997
Walid Habib; Allen C. Ward
This paper defines a number of general operations that accept arbitrary sets of values for two variables and general relations among three variables and generate a variety of third sets that are useful in design. Although the operations are defined without respect to mathematical or engineering domain, computing these operations depends on the specific mathematical domain, and algorithms are available for only a few domains. Appropriate software could make this complexity transparent to the designer, allowing the same conceptual operations to be used in many contexts. The paper proves a number of useful characteristics of the operations and offers examples of their potential use in design.
Ai Edam Artificial Intelligence for Engineering Design, Analysis and Manufacturing | 1997
Walid Habib; Allen C. Ward
This paper defines, for use in design, rules for propagating “distribution constraints” through relationships such as algebraic or vector equations. Distribution constraints are predicate logic statements about the values that physical system parameters may assume. The propagation rules take into account “variation source causality”: information about when and how the values are assigned during the design, manufacturing, and operation of the system.
Ai Edam Artificial Intelligence for Engineering Design, Analysis and Manufacturing | 1994
William P. Birmingham; Allen C. Ward
Articial Intelligence for Engineering, Design, Analysis and Manufacturing / Volume 8 / Issue 01 / December 1994, pp 76 76 DOI: 10.1017/S0890060400000470, Published online: 27 February 2009 Link to this article: http://journals.cambridge.org/abstract_S0890060400000470 How to cite this article: William Birmingham and Al Ward (1994). Special Issue on Innovative Approaches to Concurrent Engineering. Articial Intelligence for Engineering, Design, Analysis and Manufacturing, 8, pp 76-76 doi:10.1017/S0890060400000470 Request Permissions : Click here