Attribute Selection for Preference Functions in Engineering Design
Authors: Ali E. Abbas
Industrial Engineering is a broad multidisciplinary field with intersections and applications in numerous areas. When designing a product, it is important to determine the appropriate attributes of value and the preference function for which the product is optimized. This paper provides some guidelines on appropriate selection of attributes for preference and value functions for engineering design.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1127645Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 638
 R. A. Howard and A. E. Abbas. 2015. Foundations of Decision Analysis. Pearson. NY.
 von Neumann, J., O. Morgenstern. 1947. Theory of Games and Economic Behavior, 2nd ed. Princeton University, Princeton, NJ.
 L. Savage. 1951. The Theory of Statistical Decision. Journal of the American Statistical Association, 46, 253 pp 55-67.
 A. E. Abbas. 2016. Foundations of Multiattribute Utility. Cambridge University Press. In Press.
 J. E. Matheson and R. A. Howard. 1968. An introduction to decision analysis. In R. A. Howard, J. E. Matheson, eds. The Principles and Applications of Decision Analysis, Vol. I. Strategic Decisions Group, Menlo Park, CA, 1968. Reprinted from Matheson, J. E. and R. A. Howard. 1968. A report by the European Long Range Planning Service, Stanford Research Institute Report 362.
 G. A. Hazelrigg. 2012. Fundamentals of Decision Making for Engineering Design and Systems Engineering. Self-published. Arlington, VA.
 A. E. Abbas. 2003. Entropy Methods for univariate distributions in decision analysis. 22nd International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, 659(1), pp 339-349.
 A. E. Abbas and J. Aczél. 2010 The Role of Some Functional Equations in Decision Analysis. Decision Analysis 7(2), 215-228.
 A. E. Abbas. 2003. An Entropy Approach for Utility Assignment in Decision Analysis. 22nd International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, 659(1), pp 328-338.
 A. E. Abbas, D.V. Budescu, H. Yu, R. Haggerty. 2008. A Comparison of Two Probability Encoding Methods: Fixed Probability vs. Fixed Variable Values. Decision Analysis 5(4):190-202.
 R. L. Keeney. 1976. Group preference axiomatization with cardinal utility. Management Science, 23, 140-143.
 R. L. Keeney. 2013. Foundations for group decision analysis. Decision Analysis, 10, 103-120.
 R. Wilson. 1968. The Theory of Syndicates, Econometrica, 36(1), 119-32.
 A.E Abbas, J.E Matheson, and R.F Bordley. 2009. Effective utility functions induced by organizational target‐based incentives. Managerial and Decision Economics 30 (4), 235-251.
 A. E. Abbas and J. E. Matheson. 2005. Normative target-based decision making. Managerial and Decision Economics, 26(6): 373-385.
 A. E. Abbas and J. E. Matheson. 2010. Normative decision making with multiattribute performance targets. Journal of Multicriteria Decision Analysis, 16 (3, 4), 67–78.
 A. E. Abbas, L. Yang, R. Zapata, and T, Schmitz. 2008. Application of decision analysis to milling profit maximization: An introduction. Int. J. Materials and Product Technology, Vol. 35 (1/2), 64-88. Special Issue on Intelligent Machining.
 J. Karandikar, A. E. Abbas, and T. Schmitz, T., 2014, Tool Life Prediction using Bayesian Updating, Part 1: Milling Tool Life Model using a Discrete Grid Method, Precision Engineering 38(1), 9-17.
 J. Karandikar, A. E. Abbas, and T. Schmitz. 2014, Tool Life Prediction using Bayesian Updating, Part 2: Turning Tool Life using a Markov Chain Monte Carlo Approach, Precision Engineering, 38(1), 18-27.
 A. E. Abbas . 2013. Normative Persepctives on Engineering Systems Design. 2013. IEEE Systems Conference (SysCon), pp 37-42, Orlando, Fl.
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