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All Journal Jurnal Optimasi Sistem Industri International Journal of Mechanical Engineering Technologies and Applications (MECHTA)
Ihsan, Muhammad Alif
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Automotive Engineering Control & Systems Engineering Decision Sciences, Operations Research & Management Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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INTEGRATION OF TAGUCHI AND PROMETHEE FOR CNC MILLING MACHINING PARAMETER OPTIMIZATION ON AA6061 Ihsan, Muhammad Alif; Sumantri, Yeni; Irawan, Yudy Surya
International Journal of Mechanical Engineering Technologies and Applications Vol. 5 No. 1 (2024)
Publisher : Mechanical Engineering Department, Engineering Faculty, Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/MECHTA.2024.005.01.10

Abstract

In the manufacturing industry, machining has developed quite rapidly from the use of conventional machines to unconventional machines. Unconventional machines that are often used today are optimize computer numerically controlled (CNC), the use of CNC in the manufacturing industry provides many benefits in product quality and productivity. One of them is CNC milling, this type is one of the main machines on the production floor. Machining optimization becomes the main goal to achieve the ideal response in order to produce products with good and consistent quality and productivity. Surface quality leads to surface roughness, while productivity leads to material removal rate. This study aims to optimize CNC milling machining parameters on AA6061 with Taguchi experimental design and preference ranking organization method for enrichment evaluation (PROMETHEE) method. Machining was controlled using wet machining conditions to maintain temperature during machining. Experiments were conducted nine times with three factors and levels. These factors included spindle speed, feed rate, and depth of cut.  The result of this research is the ideal value of the combination of surface roughness and material burning rate which is 0.565 (experiment 3). This best experiment is influenced by spindle speed 2600 rpm, feed rate 65 mm/min, and depth of cut 2.5 mm. Feed rate has the largest contribution in influencing the response which is 43.23%, followed by depth of cut 25.24%, and spindle speed 15.91%.
REFERENCE OVERVIEW ON DESIGN AND SIMULATION OF GREEN SUPPLY CHAIN MANAGEMENT Ihsan, Muhammad Alif; Risonarta, Victor Yuardi
International Journal of Mechanical Engineering Technologies and Applications Vol. 4 No. 2 (2023)
Publisher : Mechanical Engineering Department, Engineering Faculty, Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/MECHTA.2023.004.02.7

Abstract

The issue of decreasing air quality index due to supply chain transportation is one of the problems that must be addressed by the manufacturing sector. Green supply chain management (GSCM) can be a solution to address environmental issues in the supply chain. The GSCM is an integrated view that incorporates environmental considerations into the conventional supply chain, ranging from supplier selection, product design, material selection, manufacturing processes, packaging, and distribution. The correct implementation of GSCM can address both environmental and performance issues, e.g. decreasing both energy consumption and air pollution. The GSCM consists of green design, green manufacturing, green logistics, disassembly, and remanufacturing. To address the GSCM issues, the simulation is also discussed in this work. Meanwhile, this work suggests more policies for recycling, remanufacturing, and reuse of obsolete manufacturing products to support GSCM in developing nations.
REFERENCE OVERVIEW ON DESIGN AND SIMULATION OF GREEN SUPPLY CHAIN MANAGEMENT Ihsan, Muhammad Alif; Risonarta, Victor Yuardi
International Journal of Mechanical Engineering Technologies and Applications Vol. 4 No. 2 (2023)
Publisher : Mechanical Engineering Department, Engineering Faculty, Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/MECHTA.2023.004.02.7

Abstract

The issue of decreasing air quality index due to supply chain transportation is one of the problems that must be addressed by the manufacturing sector. Green supply chain management (GSCM) can be a solution to address environmental issues in the supply chain. The GSCM is an integrated view that incorporates environmental considerations into the conventional supply chain, ranging from supplier selection, product design, material selection, manufacturing processes, packaging, and distribution. The correct implementation of GSCM can address both environmental and performance issues, e.g. decreasing both energy consumption and air pollution. The GSCM consists of green design, green manufacturing, green logistics, disassembly, and remanufacturing. To address the GSCM issues, the simulation is also discussed in this work. Meanwhile, this work suggests more policies for recycling, remanufacturing, and reuse of obsolete manufacturing products to support GSCM in developing nations.
INTEGRATION OF TAGUCHI AND PROMETHEE FOR CNC MILLING MACHINING PARAMETER OPTIMIZATION ON AA6061 Ihsan, Muhammad Alif; Sumantri, Yeni; Irawan, Yudy Surya
International Journal of Mechanical Engineering Technologies and Applications Vol. 5 No. 1 (2024)
Publisher : Mechanical Engineering Department, Engineering Faculty, Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/MECHTA.2024.005.01.10

Abstract

In the manufacturing industry, machining has developed quite rapidly from the use of conventional machines to unconventional machines. Unconventional machines that are often used today are optimize computer numerically controlled (CNC), the use of CNC in the manufacturing industry provides many benefits in product quality and productivity. One of them is CNC milling, this type is one of the main machines on the production floor. Machining optimization becomes the main goal to achieve the ideal response in order to produce products with good and consistent quality and productivity. Surface quality leads to surface roughness, while productivity leads to material removal rate. This study aims to optimize CNC milling machining parameters on AA6061 with Taguchi experimental design and preference ranking organization method for enrichment evaluation (PROMETHEE) method. Machining was controlled using wet machining conditions to maintain temperature during machining. Experiments were conducted nine times with three factors and levels. These factors included spindle speed, feed rate, and depth of cut.  The result of this research is the ideal value of the combination of surface roughness and material burning rate which is 0.565 (experiment 3). This best experiment is influenced by spindle speed 2600 rpm, feed rate 65 mm/min, and depth of cut 2.5 mm. Feed rate has the largest contribution in influencing the response which is 43.23%, followed by depth of cut 25.24%, and spindle speed 15.91%.
Integration of Analytic Network Process and PROMETHEE in Supplier Performance Evaluation Ihsan, Muhammad Alif; Garside, Annisa Kesy; Wardana, Rahmad Wisnu
Jurnal Optimasi Sistem Industri Vol. 21 No. 1 (2022): Published in April 2022
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/josi.v21.n1.p46-54.2022

Abstract

Supplier performance evaluation is one of the important factors in the supply chain because it is one of the company's strategies for increasing customer satisfaction and also maintaining the company's services in meeting consumer demand. This study proposes the integration of the Analytic Network Process (ANP) and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) to evaluate supplier performance. The integration of the two methods is proposed to obtain more complex assessment results because the combination of the two methods considers various criteria derived from ANP and various preferences from PROMETHEE, so both methods are very good to use instead of using just ANP or PROMETHEE or other methods. ANP exhibit more complex relationships between criteria and levels in the decision hierarchy, while PROMETHEE provides decision-makers with flexible and straightforward outranking to analyze multi-criteria problems. In this study, ANP is used to weight the criteria, and PROMETHEE is used to rank suppliers in evaluating supplier performance. Integrating these two methods provides more objective and accurate results in multi-criteria decision-making. The proposed method is validated by solving an industrial case of supplier evaluation problem using the real data from the skewer industry. Finally, some useful implications for managerial decision-making are discussed.
Co-Authors Annisa Kesy Garside Rahmad Wisnu Wardana Yeni Sumantri Yudy Surya Irawan