TY - JOUR
T1 - Capacity planning and production scheduling integration
T2 - improving operational efficiency via detailed modelling
AU - Yao, Xufeng
AU - Almatooq, Nourah
AU - Askin, Ronald G.
AU - Gruber, Greg
N1 - Funding Information:
This research was supported in part by grant GAC2408 from General Motors Holdings LLC.
Publisher Copyright:
© 2022 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2022
Y1 - 2022
N2 - Successful capacity planning and production scheduling is built on the understanding of market opportunities and the costs of capacity, production, sourcing, inventory, and distribution over the planning horizon. Increasingly, companies attempt to integrate capacity planning and production scheduling to improve upon the commonly used sequential decision process, but most related research works fail to capture the granularity of actual operational decisions and therefore may overlook potential cost-saving opportunities. The contributions of this study include: (1) a detailed integrated capacity and production scheduling model with multiple discrete and continuous options for varying short and medium-term capacity, (2) a heuristic algorithm that exploits the problem structure to solve the nonlinear mixed integer problem, (3) an evaluation of the value of the integrated model relative to traditional practice and its sensitivity to parameters, (4) a review of past contributions to integrated planning, particularly focused on IJPR, and (5) a case study originated from a world-class automobile manufacturer illustrating how the model can be applied and confirming its value relative to hierarchical and less detailed modelling approaches.
AB - Successful capacity planning and production scheduling is built on the understanding of market opportunities and the costs of capacity, production, sourcing, inventory, and distribution over the planning horizon. Increasingly, companies attempt to integrate capacity planning and production scheduling to improve upon the commonly used sequential decision process, but most related research works fail to capture the granularity of actual operational decisions and therefore may overlook potential cost-saving opportunities. The contributions of this study include: (1) a detailed integrated capacity and production scheduling model with multiple discrete and continuous options for varying short and medium-term capacity, (2) a heuristic algorithm that exploits the problem structure to solve the nonlinear mixed integer problem, (3) an evaluation of the value of the integrated model relative to traditional practice and its sensitivity to parameters, (4) a review of past contributions to integrated planning, particularly focused on IJPR, and (5) a case study originated from a world-class automobile manufacturer illustrating how the model can be applied and confirming its value relative to hierarchical and less detailed modelling approaches.
KW - Production modelling
KW - capacity planning
KW - integration
KW - math programming
KW - scheduling
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U2 - 10.1080/00207543.2022.2028031
DO - 10.1080/00207543.2022.2028031
M3 - Article
AN - SCOPUS:85124768963
SN - 0020-7543
VL - 60
SP - 7239
EP - 7261
JO - International Journal of Production Research
JF - International Journal of Production Research
IS - 24
ER -