Productivity Improvement through Job Shop Scheduling Problem (The Case Study of Akaki Basic Metal Industry)

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Addis Ababa University


Productivity is the measure of how efficiently inputs are converted into outputs in the manufacturing industries. Metal manufacturing industries want to produce large quantities of productivities in shorter make-spans in order to stay and compete in the global market. So, Job shop scheduling problem is an important approach in the field of the scheduling problem to improve productivity and optimize the make-span. Due to this reason, Akaki Basic Metal Industry (ABMI) has faced a problem to determine the proper allocation of jobs on the machines that can optimize the make-span and productivity improvement. Therefore, the purpose of this study is to minimize the make-span and improve the productivity of the ABMI machine shop using shifting bottleneck and local search algorithms. To undertake this research, primary and secondary data were used for seven jobs(products) with six workstations that arrived during the research period. Finally, the findings of the study using shifting bottleneck and local search algorithms showed that the make-span is reduced from 470 to 442minutes by a 5.96% improvement. The productivity also improved by 7.54% per machine/ shift improvement.



Productivity, JSSP, Make-span, DASH, Local search