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All Journal International Journal of Advances in Applied Sciences Jurnal Teknik Industri TEKNIK J@TI (TEKNIK INDUSTRI) Bulletin of Electrical Engineering and Informatics SPEKTRUM INDUSTRI Agrointek Jurnal Optimasi Sistem Industri International Journal of Advances in Intelligent Informatics Jurnal Ilmiah Teknik Industri Jurnal Litbang Industri Indonesian Journal of Science and Technology Jurnal Sistem dan Manajemen Industri PROZIMA (Productivity, Optimization and Manufacturing System Engineering) Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri KACANEGARA Jurnal Pengabdian pada Masyarakat JPPM (Jurnal Pengabdian dan Pemberdayaan Masyarakat) Jurnal Ilmiah Teknik Industri Studi Kasus Inovasi Ekonomi Yumary: Jurnal Pengabdian kepada Masyarakat Industrial and Domestic Waste Management Jurnal Litbang Industri Pelita: Jurnal Pengabdian kepada Masyarakat Jurnal Pengabdian Kepada Masyarakat Spektrum Industri
Dana Marsetya Utama
(SINTA ID: 5991174), Universitas Muhammadiyah Malang
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Journal : Jurnal Sistem dan Manajemen Industri

 1 
Model Economic Production Quantity dengan Rework Process dan Batasan Gudang Utama, Dana Marsetiya; Wardani, Dwi Pramudia; Halifah, Syukron Taufiqurrohman; Pradikta, Dimas Caesario
Jurnal Sistem dan Manajemen Industri Vol. 3 No. 1 (2019)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (420.813 KB) | DOI: 10.30656/jsmi.v3i1.1017

Abstract

Rework products and warehouse capacity are common problems experienced by companies in the production process. Several Economic Production Quantity (EPQ) models were developed to minimize the costs of purchasing raw materials. This study aims to develop an Economic Production Quantity (EPQ) model with rework processes and warehouse constraints, assuming that the product is not perfect and can rework. The proposed model considers several cost components, including setup, holding, production, rework, and warehouse. The two proposed models are EPQ models with reworks and warehouse costs, and EPQ models with reworks and warehouse constraints. Based on several tests conducted, it obtains that the increase in the value of the maximum inventory amount did not have an impact on the production costs and the cost of the rework process. Based on several numerical experiments, the total cost of the rework process and production costs do not change to the maximum inventory value.
Model Economic Production Quantity dengan Rework Process dan Batasan Gudang Dana Marsetiya Utama; Dwi Pramudia Wardani; Syukron Taufiqurrohman Halifah; Dimas Caesario Pradikta
Jurnal Sistem dan Manajemen Industri Vol. 3 No. 1 (2019)
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (420.813 KB) | DOI: 10.30656/jsmi.v3i1.1017

Abstract

Rework products and warehouse capacity are common problems experienced by companies in the production process. Several Economic Production Quantity (EPQ) models were developed to minimize the costs of purchasing raw materials. This study aims to develop an Economic Production Quantity (EPQ) model with rework processes and warehouse constraints, assuming that the product is not perfect and can rework. The proposed model considers several cost components, including setup, holding, production, rework, and warehouse. The two proposed models are EPQ models with reworks and warehouse costs, and EPQ models with reworks and warehouse constraints. Based on several tests conducted, it obtains that the increase in the value of the maximum inventory amount did not have an impact on the production costs and the cost of the rework process. Based on several numerical experiments, the total cost of the rework process and production costs do not change to the maximum inventory value.
A modified Aquila optimizer algorithm for optimization energy-efficient no-idle permutation flow shop scheduling problem Dana Marsetiya Utama; Nabilah Sanafa
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 2 (2023): December
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i2.6446

Abstract

Increasing energy consumption has faced challenges and pressures for modern manufacturing operations. The production sector accounts for half of the world's total energy consumption. Reducing idle machine time by em­ploying No-Idle Permutation Flow Shop Scheduling (NIPFSP) is one of the best decisions for reducing energy consumption. This article modifies one of the energy consumption-solving algorithms, the Aquila Optimizer (AO) algo­rithm. This research contributes by 1) proposing novel AO procedures for solving energy consumption problems with NIPFSP and 2) expanding the literature on metaheuristic algorithms that can solve energy consumption problems with NIPFSP. To analyze whether the AO algorithm is optimal, we compared by using the Grey Wolf Optimizer (GWO) algorithm. It com­pares these two algorithms to tackle the problem of energy consumption by testing four distinct problems. Comparison of the AO and GWO algorithm is thirty times for each case for each population and iteration. The outcome of comparing the two algorithms is using a t-test on independent samples and ECR. In all case studies, the results demonstrate that the AO algorithm has a lower energy consumption value than GWO. The AO algorithm is there­fore recommended for minimizing energy consumption because it can produce more optimal results than the comparison algorithm.
Economic production quantity model involving repair, waste disposal, electricity tariff, and emissions tax Utama, Dana Marsetiya; Lubis, Imtiaz Habib
Jurnal Sistem dan Manajemen Industri Vol. 8 No. 2 (2024): December
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v8i2.8961

Abstract

This research aims to develop a new model for a comprehensive Economic Production Quantity (EPQ) by considering repair processes, waste disposal, electricity tariffs, and emission taxes to optimize inventory management decisions in two shops. The first shop is responsible for providing new manufacturing and remanufacturing products required by the second shop, which focuses on inventorying finished products to meet demand. The main objective of the proposed Model is to minimize total cost. The Model is formulated as Integer Non-Linear Programming (INLP) to represent the complexity of production and inventory decisions. This study applies a Genetic Algorithm (GA) approach run using Microsoft Excel software with the Solver feature To optimize the solution of the proposed Model. Sensitivity analysis shows that while increases in electricity tariffs and emissions taxes significantly increase the total costs incurred by firms, these factors do not directly reduce total energy consumption or carbon emissions. Instead, increased costs generally result in smaller optimal production batch sizes, which does not necessarily translate into reduced energy use, as operational energy requirements remain constant. Our findings emphasize the delicate balance between cost components and energy use, highlighting that increased electricity costs and emissions do not directly lead to overall cost savings or improved energy efficiency.
A modified Aquila optimizer algorithm for optimization energy-efficient no-idle permutation flow shop scheduling problem Utama, Dana Marsetiya; Sanafa, Nabilah
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 2 (2023): December
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i2.6446

Abstract

Increasing energy consumption has faced challenges and pressures for modern manufacturing operations. The production sector accounts for half of the world's total energy consumption. Reducing idle machine time by em­ploying No-Idle Permutation Flow Shop Scheduling (NIPFSP) is one of the best decisions for reducing energy consumption. This article modifies one of the energy consumption-solving algorithms, the Aquila Optimizer (AO) algo­rithm. This research contributes by 1) proposing novel AO procedures for solving energy consumption problems with NIPFSP and 2) expanding the literature on metaheuristic algorithms that can solve energy consumption problems with NIPFSP. To analyze whether the AO algorithm is optimal, we compared by using the Grey Wolf Optimizer (GWO) algorithm. It com­pares these two algorithms to tackle the problem of energy consumption by testing four distinct problems. Comparison of the AO and GWO algorithm is thirty times for each case for each population and iteration. The outcome of comparing the two algorithms is using a t-test on independent samples and ECR. In all case studies, the results demonstrate that the AO algorithm has a lower energy consumption value than GWO. The AO algorithm is there­fore recommended for minimizing energy consumption because it can produce more optimal results than the comparison algorithm.
Co-Authors Abiddin, Moh Zainal Ahfa, Hikam Antasyard Ahmad Rusdiansyah Alba, Nidaul Anindya Apritha Putri Annisa Kesy Garside Ardiansyah, Leo Rizki Asrofi, Mochammad Samsul Ayu An Putri Salima Azis Fredy Mulya Bahru Widjonarko Bahtiar, Ardi Agustia Baiq Nurul Izzah Farida Bayu Nur Hidayat Bianca Maharani Boer, Meidina Kalse Cantika Febrita Cynthia Novel Al-Imron D Farista Dewi Maharani Diami, Berlinda Amalia Dian Setiya Widodo Dimas Caesario Pradikta Djirimu, Hanum Salsabila Dwi Asmara Putri, Yolanda Dwi Pramudia Wardani Farida Nur Kumala Fathiha Raudhatul Jannah Febrianto Susastro Febrianto Susastro, Febrianto FERRY YULIANTO FERRY YULIANTO, FERRY Firdaus, Muhammad Hafid, Ibnu Halifah, Syukron Taufiqurrohman Harto, Setyo Heri Mujayin Kholik Heri Santoso Hikam Antasyard Ahfa Husen, Moh. Ikhlasul Amallynda Ikhlasul Amallynda Ilyas Masudin Ilyas Mas’udin Imam Santoso Inggit Sekar Ningrum Jabari, Ahmed Nedal Abid Al Kareem Kholifa, Bunga Milenia Nur Leilani Salsabilah, Aisyah Lubis, Imtiaz Habib M. Faisal Ibrahim M.M Putri Mardhiyyah, Yunita Siti Mas’udin, Ilyas Maulana, Abel Alqurni Maulana, Sri Kurnia Dwi Budi Meidina Kalse Boer Meiliza Dresanala Mochammad Samsul Asrofi Moh Zainal Abiddin Moh. Husen Muhammad Aghniya Baihaqi Muhammad Faisal Ibrahim Muhammad Faisal Ibrahim Muhammad Faisal Ibrahim, Muhammad Faisal Muhammad Firdaus Nabilah Sanafa Nafis, Dzakia Nasution, Riven Nidaul Alba Ningrum, Inggit Sekar Nur Fitriana Pradikta, Dimas Caesario Primayesti, Meri Dines Putri, Anindya Apritha Putri, Artha Bripka Rahmat Wisnu Wardana Ramadhani, Taufik Akbar Randle, Oluwarotimi Ricca Andhini Octaria Risma, Yolanda Mega Rista Anggriani Riven Nasution Rizal Dian Azmi Safitri, Wa Ode Nadhilah Salsabila, Nadhea Aurelie Salsabilah, Aisyah Leilani Sanafa, Nabilah Selvia Rubiyanti Setyo Harto Shanty Kusuma Dewi Sri Kurnia Dwi Budi Maulana Syukron Taufiqurrohman Halifah Teguh Baroto Thoriq Akbar Zein Tyas Yuli Rosiani Ulfa Fitriani Ulfa Fitriani Umamy, Sabila Zahra Veronika Indah Mawarti Veronika Indah Mawarti, Veronika Indah Vritta Amroini Wahyudi Wahyu Wicaksono Wardani, Dwi Pramudia Warkoyo Widodo, Dian Setiya Wike A. P. Dania Yasa, Arnelia Dwi Yolanda Mega Risma Yusuf Hendrawan Zein, Thoriq Akbar