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Incorporating Worker Heterogeneity in Flexible Flow Shop Environment

Authors: Kubra OZPACACI; Seyma BEKLI; Betul KAYISOGLU;

Incorporating Worker Heterogeneity in Flexible Flow Shop Environment

Abstract

We study the flexible flow shop scheduling problem with the heterogeneous worker assignment. Inmany real-life manufacturing systems with flow shop environments, one of the fundamental schedulingchallenges that needs to be addressed is job sequences across multiple workers. In addition, the manufacturingsystem may require workers to have different skills at various stages during their assignment. Therefore, workeravailability at each stage may vary during the scheduling horizon. Unlike traditional flexible flow shopscheduling problem, where homogeneous workers are assumed, we consider workers with different skill levels,capabilities, and capacities. We present a mixed integer linear programming model to find the optimal sequenceof job assignments, guaranteeing that jobs follow their predefined operation sequence while assigning workerswith various skill sets in a flexible flow shop environment. The proposed model is tested at a batterymanufacturing company. By analyzing the solution, we confirm its capability to represent the problemaccurately. The proposed model offers a systematic scheduling approach for a flexible flow shop environmentwith a heterogeneous workforce and can be implemented in other industries.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold