Journal Industrial Servicess
Vol 7, No 1 (2021): Oktober 2021

Usulan perbaikan kualitas produk benang combed dengan metode statistik peta kendali x dan r

Yoga Nur Ashasry (Teknik Industri, Fakultas Teknik, Universitas Singaperbangsa Karawang)
Kusnadi Kusnadi (Teknik Industri, Fakultas Teknik, Universitas Singaperbangsa Karawang)
Asep Erik Nugraha (Teknik Industri, Fakultas Teknik, Universitas Singaperbangsa Karawang)
Hamdani Hamdani (Teknik Industri, Fakultas Teknik, Universitas Singaperbangsa Karawang)

Article Info

Publish Date
09 Nov 2021


PT. ILT is a company engaged in the production of spinning yarn. There are various types of yarn produced by PT. One of ILT's yarns is Combed 40s (CM 40/1). The purpose of this study was to evaluate the product quality of combed 40s yarn, so that improvements can be made. The data used in this study is in the form of direct testing results in the company. Data processing is carried out using control charts X and R to determine whether the production results are in accordance with the standard or not. Measurements were made on 4 criteria, namely thread number (Ne), twist (TPI), strength, and unevenness. The results obtained are known that all measurement criteria are within the control limits on the X and R control charts. Meanwhile, the comparative analysis of measurement results with company standards is known that existing standards are still too loose. This causes the quality of the resulting product is still not optimal. Therefore, it is necessary to revise the standards for each criterion. It aims to improve the quality of the products produced by increasing awareness of employee performance.

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Journal Info





Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation


Jurnal Industrial Servicess merupakan wadah bagi peneliti untuk publikasi jurnal hasil penelitian yang ruang lingkupnya melingkupi: Logistics & Supply Chain Management Operations Research Quality, Reliability, and Maintenance Management Data Mining & Artificial Intelligence Production Planning & ...