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Arrasyid, Ayata
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Control & Systems Engineering Industrial & Manufacturing Engineering

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Optimisasi Non Linear Programming Multivariat pada Perencanaan Produksi Industri Manufaktur Baja Lapis Seng (BjLS) Ats-Tsauri, Muhammad Ibrahim; Arrasyid, Ayata; Wiyatno, Tri Ngudi
JURNAL TEKNIK INDUSTRI Vol. 3 No. 1 (2022): JURNAL TEKNIK INDUSTRI : MEI 2022
Publisher : DPPM UNIVERSITAS PELITA BANGSA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (683.147 KB) | DOI: 10.37366/JUTIN0301.1625

Abstract

The main objective of this study was to examine the potential of production planning process optimization in Zinc Plated Steel (BjLS) manufacturing industry through Non Linear Programming (NLP) simulation. The manufacturing industry in the steel sub -sector is one of the strategic industries as it is a pillar of national development. Global competition requires companies to continuously improve the efficiency of their production activities, which is heavily influenced by the production planning process. With good production planning, it is hoped that the company can optimize the use of limited resources to achieve the company's goals. This study found that the most appropriate optimization to the real situation of the BjLS manufacturing industry is multivariate NLP with constraints on production volume, production time, raw material supply and budget to purchase raw materials. This research can also provide input on the production mix that best suits the company’s resources.
Co-Authors Ats-Tsauri, Muhammad Ibrahim Tri Ngudi Wiyatno