TY - GEN
T1 - Systems Dynamic Modeling
T2 - 2019 Winter Simulation Conference, WSC 2019
AU - Peck, William J.
AU - Finke, Daniel A.
N1 - Funding Information:
This material is based on work funded by the Office of Naval Research through the Naval Sea Systems Command (NAVSEA) under Contract No. N000024-12-D-6404, Delivery Order 18F8317. The opinions, findings, conclusions, and recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the Naval Sea Systems Command. Nor do they reflect the views of the Office of Naval Research or our collaborators at the Naval Air Systems Command.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - Using Systems Dynamic Modeling, we propose a novel formulation that considers workers as a decision variable with other parameters that are beholden to known, but random demand. Previous applications within the literature focus on estimating manpower to meet production demand for a particular process. We extend that work by including system constraints that are more realistically represent the problem under consideration. The proposed model was used to find configurations of workers, shifts, and work stations that achieve a minimized deviation between output and demand while maintaining a near constant workforce. The system under consideration is a manufacturing environment and the model posits the production of certain product lines that are each composed of a series of disparate operations. The model was tested using real production data and the results show that Systems Dynamic Modeling is an effective method in estimating the long-run resource requirements for the variable demand profiles.
AB - Using Systems Dynamic Modeling, we propose a novel formulation that considers workers as a decision variable with other parameters that are beholden to known, but random demand. Previous applications within the literature focus on estimating manpower to meet production demand for a particular process. We extend that work by including system constraints that are more realistically represent the problem under consideration. The proposed model was used to find configurations of workers, shifts, and work stations that achieve a minimized deviation between output and demand while maintaining a near constant workforce. The system under consideration is a manufacturing environment and the model posits the production of certain product lines that are each composed of a series of disparate operations. The model was tested using real production data and the results show that Systems Dynamic Modeling is an effective method in estimating the long-run resource requirements for the variable demand profiles.
UR - http://www.scopus.com/inward/record.url?scp=85081127729&partnerID=8YFLogxK
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U2 - 10.1109/WSC40007.2019.9004685
DO - 10.1109/WSC40007.2019.9004685
M3 - Conference contribution
AN - SCOPUS:85081127729
T3 - Proceedings - Winter Simulation Conference
SP - 2606
EP - 2616
BT - 2019 Winter Simulation Conference, WSC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 8 December 2019 through 11 December 2019
ER -