TY - JOUR

T1 - Decision models for capacity planning in a regeneration environment

AU - Eickemeyer, Steffen C.

AU - Herde, Felix

AU - Irudayaraj, Pratik

AU - Nyhuis, Peter

N1 - Funding information: The authors would like to thank the DFG research organisation for providing funding for this research project within the scope of the CRC 871 programme.

PY - 2014/6/13

Y1 - 2014/6/13

N2 - This paper presents an approach to capacity planning and coordination for the regeneration of complex investment goods. In order to capture the specifics of the regeneration environment, Bayesian networks are utilised to improve the accuracy of the workload forecast and mathematical models are proposed for the long-, medium- and short-term capacity planning and coordination. The long- and medium-term models maximise the total profit through the optimum determination of the quantity of goods to be regenerated in-house or at the sites of external vendors, the number of regenerated goods to be stored and the extent to which penalties should be tolerated for delayed regeneration orders. The short-term model determines the optimal allocation of human and machine resources to different orders. The models are validated through the use of real-world data supplied by an industrial partner. Sensitivity analyses are conducted in order to gain insights into the model. The application of the models leads to significant improvements for the industry partner due to the reduction in regeneration costs as a result of implementing varying plant capacities over the course of a year.

AB - This paper presents an approach to capacity planning and coordination for the regeneration of complex investment goods. In order to capture the specifics of the regeneration environment, Bayesian networks are utilised to improve the accuracy of the workload forecast and mathematical models are proposed for the long-, medium- and short-term capacity planning and coordination. The long- and medium-term models maximise the total profit through the optimum determination of the quantity of goods to be regenerated in-house or at the sites of external vendors, the number of regenerated goods to be stored and the extent to which penalties should be tolerated for delayed regeneration orders. The short-term model determines the optimal allocation of human and machine resources to different orders. The models are validated through the use of real-world data supplied by an industrial partner. Sensitivity analyses are conducted in order to gain insights into the model. The application of the models leads to significant improvements for the industry partner due to the reduction in regeneration costs as a result of implementing varying plant capacities over the course of a year.

KW - capacity planning

KW - mixed-integer linear programming

KW - MRO

UR - http://www.scopus.com/inward/record.url?scp=84908564062&partnerID=8YFLogxK

U2 - 10.1080/00207543.2014.923122

DO - 10.1080/00207543.2014.923122

M3 - Article

AN - SCOPUS:84908564062

VL - 52

SP - 7007

EP - 7026

JO - International Journal of Production Research

JF - International Journal of Production Research

SN - 0020-7543

IS - 23

ER -