Bayesian inference for the demand of engineering products

Ali E. Abbas, George A. Hazelrigg, Mahmood Alkindi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Within the context of a profit making firm, the job of a design engineer is to choose design parameters and product attributes that maximize the expected utility of profit. To do this effectively, the engineer needs to have an estimate of the demand for the product as a function of its price and its attributes. The firm may conduct a survey to elicit consumer preferences for the product at a given price and would like to update their belief about demand given the survey data. The purpose of this paper is to present a Bayesian methodology for demand estimation that meets this need. The estimation process begins with a prior probability distribution of demand at a given price. Using Bayesian analysis, we show how to update demand for the product given various pieces of information such as market analysis, polls and a variety of other methods. We also discuss situations where consumers can demand multiple units of the product at the given price.

Original languageEnglish
Title of host publicationASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012
Pages785-792
Number of pages8
Volume7
DOIs
Publication statusPublished - 2012
EventASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012 - Chicago, IL, United States
Duration: Aug 12 2012Aug 12 2012

Other

OtherASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012
CountryUnited States
CityChicago, IL
Period8/12/128/12/12

Fingerprint

Bayesian inference
Profitability
Engineering
Engineers
Probability distributions
Profit
Update
Attribute
Prior Probability
Expected Utility
Survey Data
Product Design
Bayesian Analysis
Prior distribution
Parameter Design
Probability Distribution
Choose
Maximise
Demand
Unit

ASJC Scopus subject areas

  • Modelling and Simulation
  • Mechanical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

Cite this

Abbas, A. E., Hazelrigg, G. A., & Alkindi, M. (2012). Bayesian inference for the demand of engineering products. In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012 (Vol. 7, pp. 785-792) https://doi.org/10.1115/DETC2012-70153

Bayesian inference for the demand of engineering products. / Abbas, Ali E.; Hazelrigg, George A.; Alkindi, Mahmood.

ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012. Vol. 7 2012. p. 785-792.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abbas, AE, Hazelrigg, GA & Alkindi, M 2012, Bayesian inference for the demand of engineering products. in ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012. vol. 7, pp. 785-792, ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012, Chicago, IL, United States, 8/12/12. https://doi.org/10.1115/DETC2012-70153
Abbas AE, Hazelrigg GA, Alkindi M. Bayesian inference for the demand of engineering products. In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012. Vol. 7. 2012. p. 785-792 https://doi.org/10.1115/DETC2012-70153
Abbas, Ali E. ; Hazelrigg, George A. ; Alkindi, Mahmood. / Bayesian inference for the demand of engineering products. ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2012. Vol. 7 2012. pp. 785-792
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