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INDONESIA
Jurnal Optimasi Sistem Industri
Published by Universitas Andalas
ISSN : 20884842     EISSN : 24428795     DOI : -
Core Subject : Science, Engineering,
Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Mechanical Engineering
Jurnal Optimasi Sistem Industri (JOSI) is a peer-reviewed journal that is published periodically (April and October) by the Department of Industrial Engineering, Faculty of Engineering, Universitas Andalas, Padang.
Arjuna Subject : -
Articles 6 Documents
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Search results for , issue "Vol. 21 No. 2 (2022): Published in October 2022" : 6 Documents clear
Total Tardiness Minimization in a Single-Machine with Periodical Resource Constraints Bruno Prata; Levi Ribeiro de Abreu; Marcelo Seido Nagano
Jurnal Optimasi Sistem Industri Vol. 21 No. 2 (2022): Published in October 2022
Publisher : The Industrial Engineering Department of Engineering Faculty at Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (616.904 KB) | DOI: 10.25077/josi.v21.n2.p97-105.2022

Abstract

In this paper we introduce a variant of the single machine considering resource restriction per period. The objective function to be minimized is the total tardiness. We proposed an integer linear programming modeling based on a bin packing formulation. In view of the NP-hardness of the introduced variant, heuristic algorithms are required to find high-quality solutions within an admissible computation times. In this sense, we present a new hybrid matheuristic called Relax-and-Fix with Variable Fixing Search (RFVFS). This innovative solution approach combines the relax-and-fix algorithm and a strategy for the fixation of decision variables based on the concept of the variable neighborhood search metaheuristic. As statistical indicators to evaluate the solution procedures under comparison, we employ the Average Relative Deviation Index (ARDI) and the Success Rate (SR). We performed extensive computational experimentation with a testbed composed by 450 proposed test problems. Considering the results for the number of jobs, the RFVFS returned ARDI and SR values of 35.6% and 41.3%, respectively. Our proposal outperformed the best solution approach available for a closely-related problem with statistical significance.
Evaluation of Driving Comparative Life Cycle Cost Assessment of Conventional and Electric Motorcycles in Indonesia: Monte Carlo Analysis Yuniaristanto; Lsa Aldira Hafidza; Wahyudi Sutopo; Muhammad Hisjam
Jurnal Optimasi Sistem Industri Vol. 21 No. 2 (2022): Published in October 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.n2.p55-65.2022

Abstract

The adoption of electric vehicles (EVs) is one of the solutions to reduce emission problems. Vehicle cost analysis is one of the keys to seizing the Indonesian market. As a consumer, it is not only the purchase price that needs to be considered, but the life cycle costs throughout ownership also need to be considered in the purchase. This study discusses the life cycle cost (LCC) of EVs in Indonesia, especially electric motorcycles (EMs), which will be compared with conventional motorcycles (CMs). In particular, this study aims to encourage the government's target for ownership of 2.1 million EMs in Indonesia by 2025. The novelty of this research is to develop a more comprehensive LCC model by considering the costs in terms of tangible and intangible to compare the two types of motorcycles using Monte Carlo simulation. This simulation is used to coordinate the behavioral uncertainty of motorcycle users. As a result, the value of an EM is more economical than CM for various users. The average value percentage of EMs is lower than CMs by 45% (IDR 30,6 million). In addition, several scenarios are also analyzed to maximize consumer welfare in Indonesia.
Predicting Human Reliability based on Individual’s Resting Period: Effect of Physical Workload Rate Caecilia Sri Wahyuning; Atiko, Saras
Jurnal Optimasi Sistem Industri Vol. 21 No. 2 (2022): Published in October 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.n2.p66-74.2022

Abstract

When a person is exposed to a prolonged workload, he/she enters a fatigue phase, the indication is the decline of cognitive performance that leading to human error. As an integral part of a system, human contributes to system reliability; therefore, it plays an important role in potential failure. Those, it is necessary to investigate how human reliability relates to physical workload rate, in order to predict maximum work duration to eliminate potential failure. A physical experiment involving 20 participants was conducted to generate medium workload, followed by Stroop test to observe selective attention and cognitive control as a form of cognitive performance. The physical workload was observed through energy expenditure and oxygen consumption during physical activity, and cognitive performance through response error time on the Stroop test. The usage of Weibull distribution was aimed to obtain reliabilities for each participant. There was a decline in reliability for all participants from one test to the other. Based on scale and form parameters, the prediction of resting time was based on mean time to human error (MTTHE), and from this experiment, varied MTTHE from each participant were obtained. The variation was created by differences in physical performance, cognitive capabilities, and other contributing factors such as environment and time of the implementation of the experiment. From this research, it was evident that human reliability can be utilized to predict potential failure in humans, which then implies a preventive action is necessitated to prevent failure from manifesting in the shape of taking a break/rest or reducing work rhythm. The application of human reliability in human resource management can be directed towards fatigue management and operator-related operational management.
Application of Genetic Algorithms to Solve MTSP Problems with Priority (Case Study at the Jakarta Street Lighting Service) Sugih Sudharma Tjandra; Fran Setiawan; Hanoum Salsabila
Jurnal Optimasi Sistem Industri Vol. 21 No. 2 (2022): Published in October 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.n2.p75-86.2022

Abstract

Transportation is one thing that is very important and is the highest cost in the supply chain. One way to reduce these costs is to optimize vehicle routes. The Multiple Traveling Salesman Problem (MTSP) and Capacitated Vehicle Routing Problem (CVRP) are models that have been extensively researched to optimize vehicle routes. In its development based on actual events in the real world, some priorities must be visited first in optimizing vehicle routes. Several studies on MTSP and CVRP models have been conducted with exact solutions and algorithms. In a real case in the Jakarta City Street Lighting Section, the problem of determining the route in three shifts is a crucial problem that must be resolved to increase worker productivity to improve services. Services in MCB (Miniature Circuit Breaker) installation and maintenance activities for general street lights and priority is given to light points that require replacement. Because, in this case, the delivery capacity is not taken into account, the priority of the lights visited is random, and the number of street light points is enormous, in this study, we use the MTSP method with priority and solve by a genetic algorithm assisted by the nearest neighbor algorithm. From the resolution of this problem, it was found that the travel time reduction was 32 % for shift 1, 24 % for shift 2, and 23 % for shift 3. Of course, this time reduction will impact worker productivity so that MCB installation can be done faster for all lights and replace a dead lamp.
Enhancement Material Removal Rate Optimization of Sinker EDM Process Parameters Using a Rectangular Graphite Electrode Sukarman; Sumanto; Acim Maulana; Dodi Mulyadi; Khoirudin; Siswanto; Ade Suhara; Safril
Jurnal Optimasi Sistem Industri Vol. 21 No. 2 (2022): Published in October 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.n2.p87-96.2022

Abstract

This article discusses the optimization of sinker electrical discharge machining (sinker EDM) processes using SPHC material that has been hardened. The sinker EDM method is widely employed, for example, in the production of moulds, dies, and automotive and aeronautical components. There is neither contact nor a cutting force between the electrode and the work material in sinker EDM. The disadvantage of the sinker EDM is its low material removal rate. This work aims to optimize the material removal rate (MRR) using graphene electrodes in a rectangular configuration. The SPHC material was selected to determine the optimum MRR model of the sinker EDM input parameter. The Taguchi experimental design was chosen. The Taguchi technique used three input parameters and three experimental levels. Pulse current (I), spark on time (Ton), and gap voltage were among the input parameters (Vg). The graphite rectangle was chosen as an electrode material. The input parameter effect was evaluated by S/N ratio analysis. The result showed that pulse current has the most significant impact on material removal rate in the initial study, followed by spark on time and gap voltage. All input parameters are directly proportional to the MRR. For optimal material removal rate, the third level of pulse current, spark on time, and gap voltage must be maintained. In addition, the proposed Taguchi optimization model could be applied to an existing workshop floor as a simple and practical electronic tool for predicting wear and future research.
Factors Affecting Millennials Purchase Intention and Sustainable Consumption of Organic Food Ni Made Dewi Ayu Murti
Jurnal Optimasi Sistem Industri Vol. 21 No. 2 (2022): Published in October 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.n2.p106-114.2022

Abstract

Organic food refers to the products produced in conventional way, without hazardous materials. Millennials are the generation most attractive to organic food market. This study aims to analyze whether factors such as environmental knowledge, environmental awareness, health awareness and social awareness affecting purchase intention and sustainable consumption of the millennials towards organic food. A questionnaire used to evaluate the relationships between the six constructs. The findings showed that 340 respondents have met requirements for analysis. The method used was Structural Equation Model (SEM). The research findings find out the main factors that influence purchase intention and sustainable consumption of the millennial generation towards organic food. This research is expected to help non-governmental organizations increase purchase intention and investigate factors that influence the sustainable consumption of organic food in the millennial generation. This research has implications for the organic food industry, especially organic food producers, namely by applying the packaging sustainability method to reduce waste in the environment.

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