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Focused factories: a Bayesian framework for estimating non-product related investment

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  • Gang Wang
  • Ratna Babu Chinnam
  • Ibrahim Dogan
  • Yan Jia
  • Melvin Houston
  • James Ockers

Abstract

Focused factories are one of the new manufacturing trends for automotive suppliers. A key requirement for these suppliers is the ability to accurately estimate both product and non-product related investment in these facilities to quote profitable business. We propose a systematic Bayesian framework to estimate non-product related investment in focused factories. Our approach incorporates uncertainty in the activity-based costing method and applies Monte Carlo simulation process to generate distributions of investment for the cost centres, and for the different project phases in setting up a facility. A Bayesian-updating procedure is introduced to improve parameter estimations as new information becomes available with experience in setting up these facilities. Our approach is deployed at a leading global automotive tier-one supplier, Visteon Corporation. The efficacy of the Visteon-focused factory cost model is validated using subject matter experts as well as by comparing the model results with estimates from the typical current process.

Suggested Citation

  • Gang Wang & Ratna Babu Chinnam & Ibrahim Dogan & Yan Jia & Melvin Houston & James Ockers, 2015. "Focused factories: a Bayesian framework for estimating non-product related investment," International Journal of Production Research, Taylor & Francis Journals, vol. 53(13), pages 3917-3933, July.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:13:p:3917-3933
    DOI: 10.1080/00207543.2014.975373
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