Model-based production cost estimation to support bid processes: an automotive case study

Andrea Borenich*, Peter Greistorfer, Marc Reimann

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

In the automobile supplier industry companies frequently need to make bids, typically based on cost estimates for the production process, to obtain incoming orders. The production process is executed in several main stages, which are linked by intra-plant logistics. To model different scenarios, we consider two separate organizational approaches towards cost estimation. In the first one, all the main stages are optimized via a central authority. The second approach models a decentralized decision making process, as it is currently used in practice. Moreover, we analyze different coordination mechanisms to improve the decentralized approach. To capture the uncertainty during the bid process, associated with key parameters like demand, capacity consumption and cost, we formulate a stochastic version of the model, capturing different risk preferences to compare risk-neutral and risk-averse decision making. The resulting MILPs are solved with CPLEX and results for an illustrative example based on a real data set are presented.

Original languageEnglish
Pages (from-to)841–868
Number of pages28
JournalCentral European Journal of Operations Research
Volume28
Issue number3
Early online date7 Feb 2019
DOIs
Publication statusPublished - 1 Sep 2020
Externally publishedYes

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