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Reliable flow in stochastic supply networks servicing pre- and after-sales markets

Published online by Cambridge University Press:  04 May 2017

Shabnam Rezapour ,
Janet K. Allen  and
Farrokh Mistree
Shabnam Rezapour
Affiliation:
Gallogly College of Engineering, School of Industrial & Systems Engineering, University of Oklahoma, Norman, Oklahoma, USA
Janet K. Allen*
Affiliation:
Gallogly College of Engineering, School of Industrial & Systems Engineering, University of Oklahoma, Norman, Oklahoma, USA
Farrokh Mistree
Affiliation:
Gallogly College of Engineering, School of Aerospace & Mechanical Engineering, University of Oklahoma, Norman, Oklahoma, USA
*
Reprint requests to: Janet K. Allen, Gallogly College of Engineering, School of Industrial & Systems Engineering, University of Oklahoma, 202 West Boyd Street, Norman, OK 73019-0631, USA. E-mail: [email protected]
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Abstract

In this paper we consider a company including both a forward supply chain producing and supplying products to markets and an after-sales supply chain providing spare parts to fulfill its after-sales commitments. Uncertainty in estimating product demand in the premarkets and spare parts demands in the after-sales markets and qualified outputs of production facilities throughout these two chains are considered in this problem. Stochastic qualified outputs of these facilities are due to their imperfect productions systems. We show that uncertainties propagate and qualified flow depreciates by moving material, components, and products from upstream to the downstream of these supply chains, and these phenomena should be quantified to determine the service levels of this company in the pre- and after-sales markets. At the end, we propose a mathematical model determining the best marketing strategies for this company (i.e., price, warranty length, and service levels) in the markets and their preserving reliable flow dynamics throughout the chains’ networks. Finally, the model is tested on a test problem defined in engine industry and some managerial insights are provided by analyzing the results.

Keywords

After-Sales Services; Reliability; Supply Network Planning; Uncertainty Propagation
Type
Special Issue Articles
Information
AI EDAM , Volume 31 , Special Issue 2: Uncertainty Quantification for Engineering Design , May 2017 , pp. 120 - 142
Copyright
Copyright © Cambridge University Press 2017 

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