DETAIL KOLEKSI

Perancangan model optimalisasi kinerja pengolahan limbah pendingin dengan pendekatan System Dynamics (Studi Kasus : seksi machining – plant pegangsaan PT Astra Honda Motor)


Oleh : Rusman Kosasih

Info Katalog

Subyek : Waste minimization;Manufacturing processes - Environmental aspects

Penerbit : FTI - Usakti

Kota Terbit : Jakarta

Tahun Terbit : 2016

Pembimbing 1 : Tri Wulandari SD

Pembimbing 2 : Iveline Anne Marie

Kata Kunci : environmental management, waste cooling, waste installation, optimization model, system dynamics, pe


File Repositori
No. Nama File Ukuran (KB) Status
1. 2016_TS_MTI_163141001_Halaman-Judul.pdf 3873.76
2. 2016_TS_MTI_163141001_Lembar-Pengesahan.pdf 855.2
3. 2016_TS_MTI_163141001_Bab-1_Pendahuluan.pdf 5513.76
4. 2016_TS_MTI_163141001_Bab-2_Tinjauan-Pustaka.pdf 8101.38
5. 2016_TS_MTI_163141001_Bab-3_Metodologi-Penelitian.pdf 2596.6
6. 2016_TS_MTI_163141001_Bab-4_Analisis-Sistem.pdf 5955.3
7. 2016_TS_MTI_163141001_Bab-5_Pemodelan-Sistem.pdf 9179.82
8. 2016_TS_MTI_163141001_Bab-6_Kesimpulan-dan-Saran.pdf 588.95
9. 2016_TS_MTI_163141001_Daftar-Pustaka.pdf 958.79
10. 2016_TS_MTI_163141001_Lampiran.pdf 1878.78

P Pengelolaan lingkungan kini telah menjadi isu yang sangat penting dalam kegiatan industri. Banyak peraturan pemerintah telah dibuat untuk memastikan bahwa semua kondisi lingkungan yang terkait dengan kegiatan industri, tetap aman dan terkendali. Penelitian ini bertujuan untuk merancang model optimalisasi kinerja instalasi pengolahan limbah Pendingin dengan pendekatan System dynamics. Indikator kinerja pengolahan limbah Pendingin adalah minimalisasi volume limbah B3 dan efisiensi pemakaian Pendingin barn, Tahapan penelitian dilakukan dengan rnelakukan studi analisa sistem,membuat desain Causal loop Diagram, membuat desain model optimalisasi kinerja berdasarkan pendekatan system dynamics. Verifikasi model dilakukan dengan membandingkan apakah variabel model dapat mencerminkan variabel yang ada dalam kondisi proses nyata. Validasi model dilakukan dengan membandingkan basil model dengan kinerja aktual. Beberapa strategi alternatif pengolahan dan kebijakan diharapkan dapat mengantisipasi fluktuasi produksi di masa depan dengan tetap menjaga standar kualitas dan kinerja Instalasi pengolahan limbah. Hasil perancangan model yang telah dibuat adalah Model Optimalisasi Kinerja limbah Pendingin dengan input nilai Pendingin yang hilang Konsentrasi Hocut — Persentase Pencapaian pengolahan limbah Pendingin, Proses : 25 Auxiliary Formula. Output : limbah di WWT — Biaya Hocut bare. Menggunakan Software Powersim Studio 10 Express. Rancangan model optimalisasi telah di validasi dengan metode MAPE dengan nilai MAPE 1,53% (kondisi pengolahan limbah pesimis), nilai MAPE 3,02% (kondisi pengolahan limbah optimis) dan nilai MAPE 0,83% (kondisi pengolahan limbah moderate). Standar nilai OK MAPE < 5%, ini menunjukkan bahwa model sangat mewakili kondisi lapangan. Simulasi model untuk alternatif strategi mendapatkan potensi penghematan biaya pemakaian Hocut yang cukup besar diperoleh dari selisih pemakaian selama 10 tahun (2016 — 2025) yaitu 30 M (pengolahan limbah pesimis) — 4,4 M (pengolahan limbah optimis) = 25,6 M (85% hemat biaya). Selain itu hasil Simulasi juga mendapatkan potensi minimalisasi limbah B3 selama 10 tahun (2016 — 2025) yaitu 7,2 juta liter (pengolahan limbah pesimis) — 0,97 juta (pengolahan limbah optimis) ---- 6,2 juta liter (86 % limbah menurun)

E Environmental management has now become a very important issue in industrial activities. Many government regulations have been made to ensure that all environmental conditions associated with industrial activities remain safe and under control. This study aims to design a model for optimizing the performance of a cooling waste treatment plant with a System dynamics approach. The performance indicators of refrigeration waste treatment are the minimization of the volume of B3 waste and the efficiency of the use of new chillers. The research stages are carried out by conducting a system analysis study, designing a Causal Loop Diagram, and designing a performance optimization model based on a system dynamics approach. Model verification is done by comparing whether the model variables can reflect the variables that exist in real process conditions. Model validation is done by comparing the model results with actual performance. Several alternative processing strategies and policies are expected to anticipate future production fluctuations while maintaining the quality and performance standards of the waste treatment plant. The result of the model design that has been made is the Waste Cooling Performance Optimization Model with the input value of the Coolant missing Hocut Concentration — Percentage of Achievement of Refrigeration waste treatment, Process: 25 Auxiliary Formula. Output : waste in WWT — Bare Hocut Cost. Using Powersim Studio 10 Express Software. The optimization model design has been validated using the MAPE method with a MAPE value of 1.53% (pessimistic waste treatment conditions), a MAPE value of 3.02% (optimistic waste treatment conditions) and a MAPE value of 0.83% (moderate waste treatment conditions). The standard OK MAPE value < 5%, this indicates that the model is very representative of field conditions. The model simulation for alternative strategies obtains a significant potential for cost savings using Hocut obtained from the difference in usage for 10 years (2016 - 2025) which is 30 M (pessimistic waste treatment) - 4.4 M (optimistic waste treatment) = 25.6 M ( 85% cost-effective). In addition, the simulation results also get the potential for minimizing B3 waste for 10 years (2016 — 2025) which is 7.2 million liters (pessimistic waste treatment) — 0.97 million (optimistic waste treatment) ---- 6.2 million liters (86 % waste decreaEnvironmental management has now become a very important issue in industrial activities. Many government regulations have been made to ensure that all environmental conditions associated with industrial activities remain safe and under control. This study aims to design a model for optimizing the performance of a cooling waste treatment plant with a System dynamics approach. The performance indicators of refrigeration waste treatment are the minimization of the volume of B3 waste and the efficiency of the use of new chillers. The research stages are carried out by conducting a system analysis study, designing a Causal Loop Diagram, and designing a performance optimization model based on a system dynamics approach. Model verification is done by comparing whether the model variables can reflect the variables that exist in real process conditions. Model validation is done by comparing the model results with actual performance. Several alternative processing strategies and policies are expected to anticipate future production fluctuations while maintaining the quality and performance standards of the waste treatment plant. The result of the model design that has been made is the Waste Cooling Performance Optimization Model with the input value of the Coolant missing Hocut Concentration — Percentage of Achievement of Refrigeration waste treatment, Process: 25 Auxiliary Formula. Output : waste in WWT — Bare Hocut Cost. Using Powersim Studio 10 Express Software. The optimization model design has been validated using the MAPE method with a MAPE value of 1.53% (pessimistic waste treatment conditions), a MAPE value of 3.02% (optimistic waste treatment conditions) and a MAPE value of 0.83% (moderate waste treatment conditions). The standard OK MAPE value < 5%, this indicates that the model is very representative of field conditions. The model simulation for alternative strategies obtains a significant potential for cost savings using Hocut obtained from the difference in usage for 10 years (2016 - 2025) which is 30 M (pessimistic waste treatment) - 4.4 M (optimistic waste treatment) = 25.6 M ( 85% cost-effective). In addition, the simulation results also get the potential for minimizing B3 waste for 10 years (2016 — 2025) which is 7.2 million liters (pessimistic waste treatment) — 0.97 million (optimistic waste treatment) ---- 6.2 million liters (86 % waste decreased)sed) Keywords: Environmental management, Waste Cooling, Waste installation, Optimization model, System dynamics, Performance Indicators.

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