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All Journal Sistemasi: Jurnal Sistem Informasi JURNAL Al-AZHAR INDONESIA SERI SAINS DAN TEKNOLOGI Journal La Multiapp Jurnal Pengbdian Teknik Mesin Advance Sustainable Science, Engineering and Technology (ASSET)
Rochmoeljati, Rochmoeljati
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Aerospace Engineering Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Public Health

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Journal : Journal La Multiapp

 1 
Analysis of Yarn Materials Defects in the Warping Process using Fault Tree Analysis with Improvement Proposals 5W1H Based on the 5W1H Method Rafida, Halimas Nafi; Rochmoeljati, Rochmoeljati
Journal La Multiapp Vol. 6 No. 5 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v6i5.2211

Abstract

Quality control is a critical aspect of the textile industry, essential for maintaining product consistency. However, defects in yarn materials continue to persist, particularly during the warping process. This study investigates yarn defects at PT X using the Fault Tree Analysis (FTA) method, identifying 15 root causes and proposing corrective measures based on the 5W1H approach. The research specifically addresses defects in Tetoron Rayon (TR) yarn Ne 30, with a focus on Cross Defects, Defective Rolls, and Nglokor Rolls. The FTA method offers a structured approach to failure analysis, while the 5W1H method is employed to derive strategic corrective actions. The findings demonstrate that the probability of defect occurrence varies between the Direct and Sectional Warping processes. Cross Defects occur with probabilities of 0.1333% and 0.126%, Defective Rolls with probabilities of 0.159% and 0.243%, and Nglokor Rolls with probabilities of 1% and 0.171%, respectively. The analysis identifies 15 primary root causes contributing to these defects, which include machine-related failures, human error, and material inconsistencies. Based on these findings, the study recommends the implementation of preventive maintenance schedules, operator training programs, and a more rigorous adherence to standard operating procedures (SOPs). The proposed improvements are expected to optimize the warping process and enhance the overall quality of the product.
Waste Analysis In CPO Production Using Lean Six Sigma Nababan, Yohanes; Rochmoeljati, Rochmoeljati
Journal La Multiapp Vol. 6 No. 6 (2025): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

PT XYZ is a manufacturing company engaged in the production of Crude Palm Oil (CPO). In its production process, a significant amount of waste due to product defects is still found. This can be seen from the production parameters recorded from January to June 2024. Based on 137 samples taken over six months, 132 samples did not meet the company's established standards across four parameters. This study aims to determine the types of waste occurring in the CPO production process, assess the sigma level, provide waste reduction recommendations, and minimize non-value-added activities. The study uses the Lean Six Sigma method. It begins by identifying waste in the CPO production process, with the most dominant forms being defects, overproduction, and waiting. The sigma level of the CPO production process at PT XYZ was found to be 2.20, with a DPMO (Defects Per Million Opportunities) of 240,277.8, which falls into the "good" category based on the average performance of the palm oil industry in Indonesia. Further analysis was conducted to identify the root causes of defects using a fishbone diagram. Improvement proposals were developed using the Failure Mode and Effect Analysis (FMEA) tool. With the design of Process Activity Mapping (PAM) and Big Picture Mapping, the lead time was successfully reduced from 807.22 minutes to 728.88 minutes.
Co-Authors Amelia, Avril Firda Arier, Tivani Nava Faris R, Mohamad Fatihul F, Ahmad Marcella, Sania Nababan, Yohanes Nugraha, Isna Qothrunnada, Alisa Rafida, Halimas Nafi Rahmadianto, Raihan Rebeka P, Adhe Shafa, Aura Diva sholeha, fitriatus Sinaga, Boriski Sumiati Sumiati Widyawati, Diana Windra R, Harys