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Riska Maulida
Sultan Agung Islamic University
Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Quality Control Analysis of 20s Polyester Yarn on Winding Machines With Statistical Quality Control (SQC) and Failure Mode and Effect Analysis (FMEA) Methods (Case Study : PT. Kabana Textile Industries) Riska Maulida; Andre Sugiyono
Journal of Applied Science and Technology Vol 3, No 01 (2023): Januari 2023
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/jast.3.01.%p

Abstract

PT. Kabana Textile Industries is a textile company which is located at Jl. Raya Pait KM. 10 Pekalongan, Central Java. The problem that occurs is that in January to September 2021 for the quality of the 20s polyester yarn roll on this winding machine there are a number of defects that exceed the standard limit of 5%, which is 5.28%. So it is necessary to control the quality of the 20s polyester yarn roll on the winding machine. Statistical Quality Control (SQC) method is used to identify the most dominant type of defect and the root cause of the problem. While the Failure Mode and Effect Analysis (FMEA) method is used to identify failures that can occur and get suggestions for improvement. The most dominant types of defects are Stitch defects of 44.67% and Swelled Packages of 36.07%. It is known that the highest RPN value for Stitch defects is 245 due to machine factors, namely the inappropriate/varied tension is overcome with a good tension set (8-12% for single thread strength and 15% for double thread). Meanwhile, Swelled Package defects caused by machine factors, namely low voltage, can be overcome by replacing bobbins that are not slack. This improvement proposal was implemented in November 2021 and the number of defects decreased to 4.53%, the stitch defect type was 43.97% and the swelled package was 29.36%, which means it is already below the disability limit and the RPN value is 140.
Co-Authors Andre Sugiyono