A Stochastic Approach for Product Costing in Manufacturing Processes

Paulo Afonso, Vishad Vyas, Ana Antunes, Sérgio Silva and Boris P. J. Bret
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Paulo Afonso: Centro Algoritmi, University of Minho, 4710-057 Braga, Portugal
Vishad Vyas: Centro Algoritmi, University of Minho, 4710-057 Braga, Portugal
Ana Antunes: Centro Algoritmi, University of Minho, 4710-057 Braga, Portugal
Sérgio Silva: Bosch Car Multimedia Portugal, S.A., 4705-285 Braga, Portugal
Boris P. J. Bret: Bosch Car Multimedia Portugal, S.A., 4705-285 Braga, Portugal

Mathematics, 2021, vol. 9, issue 18, 1-23

Abstract: Nowadays, manufacturing companies are characterized by complex systems with multiple products being manufactured in multiple assembly lines. In such situations, traditional costing systems based on deterministic cost models cannot be used. This paper focuses on developing a stochastic approach to costing systems that considers the variability in the process cycle time of the different workstations in the assembly line. This approach provides a range of values for the product costs, allowing for a better perception of the risk associated to these costs instead of providing a single value of the cost. The confidence interval for the mean and the use of quartiles one and three as lower and upper estimates are proposed to include variability and risk in costing systems. The analysis of outliers and some statistical tests are included in the proposed approach, which was applied in a tier 1 company in the automotive industry. The probability distribution of the possible range of values for the bottleneck’s cycle time showcase all the possible values of product cost considering the process variability and uncertainty. A stochastic cost model allows a better analysis of the margins and optimization opportunities as well as investment appraisal and quotation activities.

Keywords: stochastic models; costing systems; variability; uncertainty; risk (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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