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All Journal International Journal of Management Science and Information Technology (IJMSIT)
Tita Puspita
Universitas Jenderal Achmad Yani
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

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Maintenance Management Analysis to Improve the Effectiveness of Single Needle Sewing Machines at PT Alendros Global Production Tita Puspita; Rini Mulyani Sari
International Journal of Management Science and Information Technology Vol. 6 No. 2 (2026): July - December 2026
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijmsit.v6i2.8280

Abstract

The operational efficiency of production machinery is essential for improving productivity and competitiveness in garment manufacturing. PT Alendros Global Production faces operational challenges in Single Needle sewing machines, including high downtime, declining production targets, and increasing defect rates. This study evaluates maintenance management, measures machine efficiency using Overall Equipment Effectiveness (OEE)—an indicator combining equipment availability, operating performance, and product quality—identifies major production losses using the Six Big Losses framework, and develops improvement strategies based on Total Productive Maintenance (TPM) principles. A qualitative case study supported by quantitative operational data was conducted using observations, structured interviews, company documents, and operational records from July to December 2025. The findings indicate that maintenance activities remain predominantly reactive, characterized by delayed preventive maintenance, fragmented records, and ineffective spare parts inventory control. These weaknesses resulted in average downtime of 22.80% and an OEE score of 57.63%, below the 85% World Class benchmark. The Six Big Losses analysis identified sudden mechanical breakdowns and spare parts delays as the main sources of equipment losses. Recommended improvements include strengthening preventive maintenance, implementing autonomous maintenance training for operators, establishing safety stock levels, digitizing maintenance records, and improving production–maintenance communication. These measures provide a practical framework for reducing downtime, stabilizing machine performance, minimizing defects, and improving production efficiency.
Co-Authors Rini Mulyani Sari