Penelitian ini akan membahas perusahaan kimia yang memproduksi Pythalic Anhydride (PA) di Indonesia. Perusahaan ini memiliki kapasitas 70.000 Metric Ton Per Year (MTPY). Selama 2017, total waktu produksi adalah 6.699,8 jam atau rata-rata 23 hari. Namun, dibandingkan dengan kapasitas produksi, perusahaan hanya dapat memenuhi permintaan dalam waktu 20 hari tiap bulannya. Waktu produksi minimum diperlukan untuk mencapai layanan pelanggan yang optimal dan biaya minimum. Perbedaan antara kapasitas dan kondisi yang ada disebabkan oleh penutupan pabrik. Penutupan pabrik disebabkan oleh kehabisan persediaan material dan kerusakan mesin. Frekuensi penutupan pabrik relatif tinggi. Selama 2014 hingga 2017, pabrik ditutup 48 kali dengan MTTF 3,1 hari dan MTTR 23 jam. Analisis reliability, availability, dan maintainability (RAM analysis) dilakukan untuk mengatasi masalah ini. Secara khusus, penelitian ini akan fokus pada pengembangan skenario dengan melakukan percobaan pada persediaan penyangga suku cadang untuk mengurangi waktu produksi dan meningkatkan availabilitas. Pendekatan simulasi digunakan dalam penelitian ini untuk memodelkan perilaku stokastik. Berdasarkan hasil percobaan, waktu produksi berkurang 232,7 jam dan availabilitas menjadi 0,8996. Analisis keuntungan dan biaya dapat dilakukan pada penelitian selanjutnya untuk mendapatkan solusi optimal.
A maintenance strategy is an important factor in the production activities of the process industry. Since the process industry consists of many components, the failure mode is relatively complex. This paper observes one of the petrochemical companies in Indonesia which produces Pythalic Anhydride. The company is able to produce in 20.69 days every month. In reality, during 2017, the company produced 23 days every month on average. Production, known as the calendar day, which cannot achieve the target can affect customer service level. This research focuses on evaluating availability in order to minimize Mean Time to Repair (MTTR). One of the best strategies is to control the spare part inventory policy so that the spare part must be available when an equipment downtime occurs. We will use two modeling techniques to solve the problem: (a) reliability block diagram will be used to model the failure mode and (b) the simulation model will be used to model the entire system, including random variables and variable inter-dependency. After conducting scenario analysis by varying some parameters, the availability increased to 91.8% and average calendar days decreased to 22.64 days per month.
Manufacturing technology becomes more complex as customer demand increases. Most manufacturing companies consist of multi-state manufacturing networks. Therefore, the reliability and availability parameters become an important issue to satisfy customer demand. Unavailability can result in reducing throughput because of decreasing operational production time. To resolve this problem, the buffer inventory can minimize the occurrence of material starving and production blocking during the equipment downtime. This paper will focus on experimenting with buffer inventory levels and the capacity of a multi-state manufacturing network to increase the production throughput on a company that has 70,000 tons per year of capacity. However, due to the unavailability problem, the existing system capacity decreases to 62,175 tons per year. The simulation model is used to improve throughput by modeling the failure interruption and the buffer inventory logics during the production process.
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