Kajian Total Productive Maintenance terhadap Perbaikan Mesin Injeksi #096 untuk Produksi Plastik di PT XYZ

Abstract

Mesin Injeksi #096 di PT XYZ menunjukkan efektivitas yang rendah, ditandai oleh nilai OEE monitoring perusahaan yang masih berada di bawah target internal sebesar 80%, sementara perusahaan belum pernah melakukan evaluasi OEE secara komprehensif untuk mengetahui penyebab dominan rendahnya efektivitas tersebut. Penelitian ini bertujuan mengevaluasi efektivitas Mesin Injeksi #096 di PT XYZ serta merancang usulan perbaikan berdasarkan Total Productive Maintenance (TPM). Metode yang digunakan meliputi perhitungan OEE, analisis Six Big Losses, Diagram Pareto, dan 5 Whys Analysis. Hasil penelitian menunjukkan bahwa nilai OEE mesin sebesar 70,15%, masih berada di bawah target perusahaan sebesar 80%, dengan komponen Availability sebesar 77,22% sebagai nilai terendah akibat tingginya downtime. Equipment failure (52,02%) merupakan penyumbang terbesar terhadap kerugian produksi, diikuti oleh defect loss (22,88%), sedangkan permasalahan terkait kualitas diidentifikasi sebagai penyebab utama unplanned downtime. Berdasarkan temuan tersebut, usulan perbaikan berupa One Point Lesson dirancang untuk meningkatkan efektivitas inspeksi rutin serta mendukung deteksi dini terhadap kondisi abnormal mesin.

Injection Machine #096 at PT XYZ shows low effectiveness, as reflected in the company's OEE monitoring value, which remains below the 80% internal target, even though the company had never conducted a comprehensive OEE evaluation to identify the dominant causes. This study evaluates the effectiveness of Injection Machine #096 at PT XYZ and proposes improvements based on Total Productive Maintenance (TPM). The research applied OEE, Six Big Losses analysis, Pareto Diagram, and 5 Whys Analysis. The machine achieved an OEE of 70.15%, below the company's target of 80%, with Availability (77.22%) identified as the weakest component due to excessive downtime. Equipment failure (52.02%) was the largest contributor to production losses, followed by defect loss (22.88%), while quality-related issues were identified as the primary cause of unplanned downtime. To address these issues, One Point Lessons were proposed to improve routine inspections and facilitate early detection of abnormal machine conditions.