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

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...

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Bibliographic Details
Published in:Central European journal of operations research 2020-09, Vol.28 (3), p.841-868
Main Authors: Borenich, Andrea, Greistorfer, Peter, Reimann, Marc
Format: Article
Language:English
Subjects:
Automobile industry
Automotive engineering
Business and Management
Case studies
Cost estimates
Decision making
Economic aspects
Logistics
Mathematical models
Operations research
Operations Research/Decision Theory
Original Paper
Parameter uncertainty
Process parameters
Risk
Transportation equipment industry
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Summary: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.
ISSN:1435-246X
1613-9178
DOI:10.1007/s10100-019-00608-1