Pengembangan Sistem Monitoring Untuk Peningkatan Produktivitas Pada Industri Manufaktur Akrilik

Lestari, Ayu Nur (2026) Pengembangan Sistem Monitoring Untuk Peningkatan Produktivitas Pada Industri Manufaktur Akrilik. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Penelitian ini membahas pengembangan sistem monitoring otomatis pada proses pemotongan akrilik PMMA tebal 3 mm menggunakan mesin laser cutting dalam proses produksi berbasis job order. Pada kondisi awal bulan Juli - bulan September 2025, proses masih bersifat reaktif karena pemantauan dilakukan secara manual, belum tersedia work standard dan SOP yang baku, serta deteksi abnormalitas sering terlambat. Akibatnya, gangguan proses berupa overheating dan downtime sering terjadi, lead time penyelesaian job order tidak stabil, serta defect dan rework meningkat.Tujuannya untuk meningkatkan kestabilan proses dan kematangan sistem manufaktur menuju kondisi yang lebih terstandarisasi melalui pendekatan Kaizen dan Lean Manufacturing maturity level. Metode penelitian mengadopsi kerangka 7 Kaizen Step Toyota Motor Manufacturing Indonesia (TMMI) melalui observasi langsung, wawancara operator dan teknisi, serta pengumpulan data performa mesin. Hasil analisis Pareto overheating dan downtime merupakan gangguan dominan, sehingga perbaikan difokuskan pada pengendalian suhu proses dan percepatan respon operator terhadap kondisi tidak normal. Perbaikan dilakukan dengan mengembangkan sistem monitoring berbasis Internet of Things (IoT) yang terintegrasi dengan Andon warning system. Sistem ini memantau suhu Heat Affected Zone (HAZ) secara real time, menampilkan status mesin dalam zona aman-waspada-bahaya-emergency, serta memberikan peringatan visual dan alarm suara saat suhu mendekati batas abnormal. Dengan adanya peringatan dini tersebut, operator dapat segera melakukan tindakan korektif seperti menyesuaikan parameter proses dan menghentikan sementara proses sebelum suhu meningkat menjadi overheating atau menyebabkan downtime. Selain itu, disusun SOP dan standar respon Andon agar penanganan gangguan seragam antar shift. Hasil implementasi bulan Oktober - bulan November 2025 menunjukkan total durasi downtime turun dari 214 menit menjadi 17 menit, frekuensi overheating turun dari 18 kejadian menjadi 5 kejadian, defect rate turun dari 1,51% menjadi 0,41% atau turun 72,8%, dan lead time job order turun dari 78,11 menit menjadi 22 menit. Temuan ini menunjukkan peningkatan kestabilan proses menuju fase transisi Lean level 2 - level 3 manufaktur.
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This study focuses on the development of an automated monitoring system for cutting 3 mm PMMA acrylic sheets using a laser cutting machine in a job-order production environment. During the initial condition July - September 2025, the process was largely reactive due to manual monitoring, the absence of standardized work and formal SOPs, and delayed detection of process abnormalities. As a result, frequent overheating and machine downtime occurred, job-order lead time became unstable, and defect and rework levels increased.Improve process stability and manufacturing maturity toward a more standardized condition by applying the Kaizen approach and Lean Manufacturing maturity level. The methodology adopted the 7 Kaizen Step framework from Toyota Motor Manufacturing Indonesia (TMMIN), including direct observation, interviews with operators and technicians, and the collection of machine performance data. Pareto analysis identified overheating and downtime as the dominant disturbances; therefore, the improvement focused on thermal process control and accelerating operator response to abnormal conditions. The improvement was implemented by developing an Internet of Things (IoT) based monitoring system integrated with an Andon warning system. The system monitors Heat Affected Zone (HAZ) temperature in real time, displays machine status through safe–warning–danger–emergency zones, and provides visual alerts and audible alarms when the temperature approaches abnormal thresholds. With this early warning mechanism, operators can immediately perform corrective actions, such as adjusting process parameters and temporarily stopping the cutting process before the temperature escalates into overheating or causes downtime. In addition, SOPs and standardized Andon response procedures were established to ensure consistent handling of abnormalities across shifts. The implementation results October - November 2025 show that total downtime duration decreased from 214 minutes to 17 minutes, overheating frequency decreased from 18 to 5 incidents, defect rate decreased from 1.51% to 0.41%, 72.8% reduction, and job order lead time decreased from 78.11 minutes to 22 minutes. These findings indicate improved process stability and a transition toward Lean Manufacturing maturity level 2 - level 3.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Defect, Downtime, Internet of Things (IoT), Kaizen, Lean level manufaktur, Lean Manufaktur Defect, Downtime, Internet of Things (IoT), Kaizen Step, Level System Manufacture, Lean Manufacturing
Subjects:	T Technology > TS Manufactures > TS183 Manufacturing processes. Lean manufacturing.
Divisions:	Faculty of Industrial Technology and Systems Engineering (INDSYS) > Industrial Engineering > 26101-(S2) Master Thesis
Depositing User:	Ayu Nur Lestari
Date Deposited:	22 Jan 2026 10:02
Last Modified:	22 Jan 2026 10:02
URI:	http://repository.its.ac.id/id/eprint/130131

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