Resource Simulation of Machining Processes and Operator Optimization : A Generic Model

University essay from Mälardalens universitet/Akademin för innovation, design och teknik

Abstract: Purpose – The purpose is to present a Generic Model that considers the machining process's resource simulation into account as well as the operator variables. The operator variables are associated with the operations they carry out, the time required, and the ideal number of operators. This Generic Model will serve as a framework for future initiatives for industry and academia, by including resource simulation for machining operations. Design/Methodology/Approach - The simulation model addresses the optimal resource allocation to support efficient machine utilization. The resource in this simulation model is composed of human operators, working across several machining operations of similar specifications, with all of the machines arranged in parallel. The resulting simulation model presented in this thesis is generic in its organization. Findings - The developed Generic Model incorporates material-flow and logistics, tool-ware and machine failure, product-tool interdependence, and other related factors pertaining to the operator task allocation and the number of operators. Further, the optimization of process resources has been presented through results obtained pertaining to machine utilization, productivity and operator distance travelled. Research implications - Several industries are working towards overcoming the challenges pertaining to the resource allocation in the manufacturing process and the requirement for optimizing. As a result, simulation provides a less expensive option for making resource allocation decisions and testing the chosen options. The presented Generic Model will serve as a framework for future initiatives including resource simulation and allocation for machining operations and operators. Originality/Value- The model presented in this thesis, will therefore allow production planners and managers to allocate the necessary resources and observe the outcomes before they are implemented on the shop floor. The Generic Model adds value by allowing for future adjustments in model resources and parameters based on system requirements.

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