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All Journal Journal of Research and Technology Idarotuna : Jurnal of Administrative Science
Hamim, Moh. Ismail
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Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Engineering Environmental Science Industrial & Manufacturing Engineering Social Sciences

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ANALISIS PENGENDALIAN KUALITAS PRODUKSI BOGIE BARBER S2HD9C MENGGUNAKAN METODE LEAN SIX SIGMA DI PT BARATA INDONESIA (PERSERO) GRESIK Suparno; Hamim, Moh. Ismail; Prasetiawan, Heru
Journal of Research and Technology Vol. 2 No. 2 (2016): JRT Volume 2 No 2 Des 2016
Publisher : 2477 - 6165

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (643.138 KB) | DOI: 10.55732/jrt.v2i2.235

Abstract

This study aimed to analyze the quality control and waste that occurs in side frame S2HD9C production using lean six sigma method with DMAIC approach in PT Barata Indonesia (Persero) Gresik. Side frame S2HD9C is a part of bogie barber S2HD9C products. This study focused on six sigma phase on defect analysis and sigma performance, while lean six sigma phase focused on the analysis of waste and sigma performance. The data used in this study are two types: primary and secondary data, qualitative and quantitative. Primary data were obtained from field observations, while secondary data obtained from the study of the document. This study conducted with the approach of DMAIC (define, measure, analyze, improve, control). After the analysis at six sigma stage, it is known that there are 5 types of defects that occur in January to April 2016, they are trapped gas defect 58.18%, broken core defect 21.82%, sand dropdefect 12.73%, brake mold defect 5.46% and misplace core defect 1.82%. And sigma value achievement level of each defect are as follows: trapped gas defect 1235.71 DPMO = 4.52σ, broken core defect 463.392 DPMO = 4.81σ, sand drop defect 270.312 DPMO = 4.96σ, brake mold defect 115.848 DPMO = 5.18σ and misplace core defect 38.616 DPMO = 5.45σ. In lean six sigma stage, it is known that there are 4 types of waste, they are: waste defect product, waste waiting time (delay), waste transportation, and waste excess process. Here are achievement values of each waste: waste defect product 6890 DPMO = 3.96σ and value capability process 1.31 = 3.94σ, waste waiting time (delay) value capability process 1 = 3σ, waste transportation value capability process 1.31 = 3.94σ and waste excess process 1499.75 DPMO = 4.47σ.Keywords: DPMO, Defects, Lean six sigma, Waste.
Peran Pengendalian Persediaan Bahan Baku dengan Pendekatan Bullwhip Effect dalam Supply Chain Narto, Narto; Hamim, Moh. Ismail; HM, Gatot Basuki; Junianto, Dwi; Mahsun, Moch
Idarotuna : Journal of Administrative Science Vol. 5 No. 2 (2024): November
Publisher : Program Study Office Adminstrative of Akademi Komunitas Teknologi Syarifuddin Lumajang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54471/idarotuna.v5i2.106

Abstract

The demand for broiler chicken meat has increased over the past few decades due to changes in consumption patterns. This condition has led to information distortion and a significant rise in broiler chicken meat demand. CV HMS, as a distributor, faces fluctuating customer demand, which results in a bullwhip effect, making it difficult for the company to control raw material inventory. To address this phenomenon, raw material inventory control is required using forecasting techniques to estimate future demand and avoid delays in customer deliveries. The objective of this study is to identify the most appropriate forecasting method and determine the bullwhip effect values before and after applying the selected forecasting method. This enables the company to avoid stock shortages or surpluses of broiler chickens, ultimately supporting supply chain efficiency. The analysis results indicate that the most suitable forecasting method is single exponential smoothing with an α value of 0.9, which shows a reduction in the bullwhip effect value from 1.05 to 0.99. By employing accurate forecasting techniques and effectively measuring the bullwhip effect, the company can develop strategies for raw material inventory control.
Co-Authors Dwi Junianto HM, Gatot Basuki Moch. Mahsun Narto Narto, Narto Prasetiawan, Heru Suparno