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PENGENDALIAN KUALITAS PRODUK GALON AIR MINERAL 19 L DENGAN PENDEKATAN SIX SIGMA

JKIE (Journal Knowledge Industrial Engineering)

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Title PENGENDALIAN KUALITAS PRODUK GALON AIR MINERAL 19 L DENGAN PENDEKATAN SIX SIGMA
 
Creator Arif, Afrizal
Wahid, Abdul
 
Subject Gallon
Quality Control
Six Sigma
 
Description The problem faced by the company is the lack of product quality control that is used to reduce the number of defective products during the production process. Six sigma is a statistical-based quality improvement method, where the principle of this method is continuous improvement using statistical tools and problem solving tools. In this study, researchers applied the Six Sigma method which can be considered by the company as a product quality control method. In the measure stage through the calculation of the average product mismatch, it is known that the products that experience the largest defect rate of the company are black dirty, with an average value of 0.0285 and a sigma value of 3.2. In the next stage, the analyze phase through calculations using pareto diagrams, it is known that the dominant type of product defect is black dirty (65%) and the rest is dirty die head (2%) anamdel mouth (1%) bottom folded (1%). At the same stage through calculations using cause and effect diagrams, it is known that the factors that sequentially cause the product defects are 5 factors, namely human, material, method, machine and environment. The proposed improvements made by researchers into consideration in making improvements that can be useful to reduce the number of defective products or reject on gallon products.
 
Publisher Department of Industrial Engineering - Universitas Yudharta Pasuruan
 
Date 2019-04-30
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier https://jurnal.yudharta.ac.id/v2/index.php/jkie/article/view/2052
10.35891/jkie.v6i1.2052
 
Source 2541-4461
2460-0113
10.35891/jkie.v6i1
 
Language eng
 
Relation https://jurnal.yudharta.ac.id/v2/index.php/jkie/article/view/2052/1519
 
Rights Copyright (c) 2019 JKIE (Journal Knowledge Industrial Engineering)
http://creativecommons.org/licenses/by-sa/4.0