Dept. of Computer Sci., Florida State University, Tallahassee, FL 32306-4019. Barbara DuBrosky ... Gary Zenz. FSU College of Business. Chuck Zhang. Dept. of ...
Decision-Making with Incomplete Information in an Integrated Product and Process Development Enterprize { A Management Decision Tool for Cost Modeling and A ordability Applications { DMI 952 5991
,
Ladislav Kohout
Dept. of Computer Sci., Florida State University, Tallahassee, FL 32306-4019
Barbara DuBrosky
Pratt & Whitney, P.O.Box 109600, West Palm Beach FL 33410-9600
Ben Wang
Dept. of Industrial Eng., FAMU-FSU College of Engineering
Gary Zenz
FSU College of Business
Chuck Zhang
Dept. of Industrial Eng., FAMU-FSU College of Engineering
Abstract
Assuring and maintaining a competitive position in the aerospace market requires inclusion of afas a major component in all design and business decision-making. Our approach takes into account not only the technological design and production concepts and data, but also the psychological and linguistic constructs utilized by human participants. The computational tools that we use for this purpose are fuzzy relations, BK-relational products and fast fuzzy relational algorithms. Fuzzy mathematics provides a framework for dealing with incomplete and/or con icting information, constraints and consequences. Conceptual integration is achieved by Activity structures and Value analysis methods. This paper describes the work that has been done on the DMI 952 599 grant in the period 1st October 1995 { 30th August 1996. fordability
Total manufacturing and marketing system is formed by groups of interacting and cooperating participants (of both human and technological artifact kind) that can be viewed as a distributed intelligent system. This de nes our approach to the problem of a ordability. Our approach takes into account not only the technological design and production concepts and data, statistical methods for quality monitoring and control, but also the psychological and linguistic constructs utilized by human participants. The emphasis of our approach is on the methods suitable for rms that are at the leading edge of high technology. These companies face a formidable problem, being forced to make technological and business decisions based on incomplete, uncertain information about the product that is yet to be designed and manufactured. Work on this project started on October 1, 1996. During the rst year of this NSF-MOTI supported project we addressed the folowing objectives. Objective 1: Application of Fuzzy Relational Methods To develop methods for Knowledge elicitation and relational representation [1] of the substantive knowledge (concepts, linguistic descriptors, physically measurable parameters and interactions) that are relevant to the a ordability analysis and prediction and are applicable not only to technical but also to human and organisational subsystems of a total production system. Selecting a part of an engine we isolate (using repertory grids) technological attributes of this part that may be relevant to the cost. Once the relevant information on the attributes of a part is identi ed, it is expressed as a fuzzy relational structure [R2]. Testing the fuzzy relational structure for various relational properties allows us to discover dependencies, hierarchies, similarities, and equivalences of the attributes characterizing the part [R3]. Objective 2: Value Analysis We aimed at integrating the Value Analysis [2] and Activity Structures [1] methodologies, and investigated the ways of building relational models for processing generated by Value Analysis. Conceptual comparison of these two methodologies has shown that their integration is possible. The rst version of relational model 1
of Value Analysis activities using BK-relational products has been formulated. Objective 3: Problems of Engineering Design and their relationship to a ordability. The faculty and students of the Department of Industrial Engineering involved in the MOTI project have reviewed the information provided by Pratt & Whitney namely \process plans" and "cost factors/priorities". This team is developing a cost estimating tool using multi-attribute utility theory (MAUT) and fuzzy mathematics. The tool will be able to provide cost information of a product design (e.g. engine parts) given the design and manufacturing information (materials, process plan, etc.). Objective 4: To Compare Fuzzy and Probabilistic Methods of dealing with a ordability data. As fuzzy and probabilistic methods complement each other, our aim is to determine their compatibility, overlap and exclusivity. In particular, the investigation of the relationship of fuzzy possibilistic method to exploratory statistical analysis is emphasised. Guha [R1] is a method of exploratory statistical analysis. It provides methods for generating interesting hypotheses from experimental data by means of a computer. Interestingness of a hypothesis is determined by the properties relevant to a particular application. The BK-relational compositions and the theory of the checklist paradigm, on the other hand, are analysis methods that form the modelling and integrating backbone of this project [R3]. Each of these approaches adresses di erent issues of incomplete data analysis that are, however, conceptually complementary. The major impediment for combining these two mathematically well-de ned approaches was lack of a connecting mathematical theory. Such mathematical link has been, however, recently discovered [R1]. Objective 5: Knowledge Transfer to Industry. A series of seminars that explain the basic relational techniques [3] as well as developed in this project is being developed.
Publications resulting from DMI 952 5991 Project
[R1] P. Hajek and L.J. Kohout. Fuzzy implications and generalized quanti ers. Internat. Journal of Uncertainty, Fuzziness and Knowledge Based Systems, 4(3):225{233, 1996. [Also partially supported by the National Research Council COBASE grant for collaborative projects with former East European contries.] [R2] L.J. Kohout and E. Kim. Relational algorithms for theoretical and empirical evaluation of systems of fuzzy connectives. In D. Kraft, editor, Proc. of IEEE Internat. Conf. on Fuzzy Systems, IEEE, New York, 1996, in press. [R3] E. Kim, L.J. Kohout, B. Dubrosky and W. Bandler. Use of fuzzy relations for a ordability decisions in high technology. In Proc. AIENG 96 Internat. Conf. on AI in Engineering, September 1996, in press. [R4] E. Kim and L.J. Kohout. Generalized morphisms: A tool for evaluation of adequacy of logic connectives used in symbolic and soft computing. In 1st On-Line Workshop on Soft Computing (August 19-30, 1996). The Society of Fuzzy Theory and Systems (SOFT), 1996. [The paper will also appear in the Proceedings of the Workshop]. [R5] B. Dubrosky, L.J. Kohout, R.M. Walker, E. Kim, and H.P. Wang. Use of fuzzy relations for advanced technology cost modeling and a ordability decisions. In Proc. 35th AIAA Aerospace Sciences Meeting and Exhibit (Reno, Nevada, January 6-9,1997). AIAA, January 1997, accepted for publication.
References
[1] L.J. Kohout et.al. Knowledge-Based Systems for Multiple Environments. Ashgate Publ. Co., Brook eld, Vermont 05036. [2] G. Zenz. Purchasing and the Material Matrix. J. Wiley, 1993. [3] L.J. Kohout. A Tutorial: Fuzzy Relations and Algorithms. Multidisciplinary Conf. Intelligent Systems: A Semiotic Perspective. NIST, Gaithersburg, MD (October 1996).
2
