Analisis Produk Cacat Menggunakan Metode Statistical Process Control Di PT Sinar Alam Permai

Pratama, Antonius Hari (2019) Analisis Produk Cacat Menggunakan Metode Statistical Process Control Di PT Sinar Alam Permai. Working Paper. Perpustakaan Universitas Katolik Musi Charitas. (Unpublished)

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Abstract

PT Sinar Alam Permai is a company that produces cooking oil. The brands of cooking oil produced are Fortune, Sania, Sovia, and Siip. In making production, the products produced are not always good, there are also defective products in them. During October the defective products produced were 6,252 pcs of the total production amount of 10,008,784 pcs. The causes of disability are analyzed using the SPC method (Statistical Process Control) to control the number of defective products. After calculating, obtained defective products produced are uncontrolled. Product causes factors The first problem is that people who chat and joke while working, the second factor is material that is not feasible, because it increases scratches, factors that increase the engine delay treatment, the factor in question is a method that causes the SOP to not run properly, and consideration factors i.e. environment caused by irregular machine layout. Responding to the losses suffered by the company reached IDR 75,024,000 in one month. To regulate the number of products in the production process, the proposal given is employee control, good material handling, maintenance and repair of machines, giving approval to employees that have been made, and redesigning the machine layout.

Item Type: Monograph (Working Paper)
Additional Information: Kerja Praktik Lengkap dapat dibaca pada Komputer Katalog di Ruang Sirkulasi Perpustakaan UKMC Kampus Bangau.
Uncontrolled Keywords: Cooking oil, defective products, statistical process control.
Subjects: Q Science > Q Science (General)
Divisions: Report on Practical Work > Industrial Engineering Study Program
Depositing User: Perpustakaan Unika Musi Charitas
Date Deposited: 29 Jan 2019 02:21
Last Modified: 04 Nov 2021 03:22
URI: http://eprints.ukmc.ac.id/id/eprint/1979

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