Jurnal Rekayasa Sistem Industri (Oct 2021)

Penjadwalan Produksi Job shop Mesin Majemuk Menggunakan Algoritma Non Delay untuk Meminimalkan Makespan

  • Adhie Tri Wahyudi,
  • Bagus Ismail Adhi Wicaksana,
  • Maresta Andriani

DOI
https://doi.org/10.26593/jrsi.v10i2.4666.183-190
Journal volume & issue
Vol. 10, no. 2
pp. 183 – 190

Abstract

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Scheduling is an important factor in both manufacturing and service industry environments. Scheduling is a resource allocation arrangement for completing tasks that involve work, resources and time. With the scheduling, all work can be completed according to priority and can minimize processing time, so that makespan is minimal. In addition, it can reduce idle machines and reduce the inventory of semi-finished goods. Maryati Small Micro and Medium Enterprises (IKM) is a business that is engaged in the manufacture of clothing that produces various types of products such as baby clothes, teenage clothes to adults. So far, IKM Maryati is in the process of machine scheduling by determining the order of Job execution based on the longest to shortest total Job processing time. Scheduling with this method creates problems for the company, as evidenced by the accumulation of semi-finished goods at several work-stations. Another problem is when orders arrive at a certain period with a large variety and number of products, causing Job completion that exceeds the target time (due-date). The size of the makespan causes the production time to increase, so the company is late to start production of orders in the following month. In this study, the Non-delay algorithm is used to solve the problems that arise in IKM Maryati. The result obtained is the scheduling using the existing method by IKM Maryati which produces 44 days makespan value. Meanwhile, by applying the Non-delay compound engine algorithm, it produces a makespan of 42 days. This shows that the compound machine Non-delay Algorithm method can minimize the makespan value in IKM Maryati. There is an efficiency of 4.55% in both time and cost variables.

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