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Journal of Engineering and Management in Industrial System
Published by Universitas Brawijaya
ISSN : 23383925     EISSN : 24776025     DOI : -
Core Subject : Engineering,
Industrial & Manufacturing Engineering
Journal of Engineering and Management in Industrial System is a peer reviewed journal. The journal publishes original papers at the forefront of industrial and system engineering research, covering theoretical modeling, inventory, logistics, optimizations methods, artificial intelligence, bioscience industry and their applications, etc.
Arjuna Subject : -
Articles 7 Documents
 1 
Search results for , issue "Vol 11, No 1 (2023)" : 7 Documents clear
A THEORETICAL ANALYSIS OF SYSTEM DYNAMICS METHODOLOGY ON INFRASTRUCTURE PROJECTS WITHIN THE ENERGY SECTOR Takalani Mashamba; Grace Mukondeleli Kanakana-Katumba; Rendani Wilson Maladzhi
JEMIS (Journal of Engineering & Management in Industrial System) Vol 11, No 1 (2023)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jemis.2023.011.01.1

Abstract

The energy sector is critical to a country's economic and social development. Due to economic growth in South Africa, the state-owned firm has witnessed a demand for power supply over the last 20 years. To alleviate the existing supply restriction, it is now implementing capital expansion build programs. The completion of this project has been delayed. Over the last two decades, there has been a lot of system-based study such as considerable research that uses system dynamics (SD) as an analytical and modelling approach. However, merely limited critical reviews have been conducted to provide understanding of SD application in infrastructure projects. We summarize and analyse current research on SD models in infrastructure construction projects in the energy sector in this study, which is based on a thorough systematic literature review. Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) approach was used to conduct a search and only 15 studies out of 130 were found to be relevant. According to the findings of the literature analysis, four main feedback structures from prior SD project dynamics models have been recognized as major trends. Design errors, rework and change management, performance and effectiveness, resource management, and project planning and control are some of the topics covered.
THE INFLUENCING FACTORS IN CLEANER PRODUCTION ADOPTION ON THE ALUMINIUM PROCESSING INDUSTRY Devi Agustina; Agus Dwi Wicaksono; Christia Meidiana
JEMIS (Journal of Engineering & Management in Industrial System) Vol 11, No 1 (2023)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jemis.2023.011.01.2

Abstract

Cleaner Production (CP) practices comprised environmental strategy perpetually applied in the production, processes, and services to bolster efficiency, safety, and environmental friendliness. Some factors are to be considered to achieve a cleaner production strategy: stakeholders establishment, surveys, utilization, and impact, as well as how the top management devote their practices towards cleaner production. Combining with the mindset of sustainable stocks and resources, this exercise of cleaner production provides advantages of minimum toxic wastes and residues. In this study, we prioritize this practice to be applied in the aluminum industry, of which cleaner production action has not yet been employed. Small and medium businesses now no longer have enough monetary assets to put money into cleaner production practices because they require high-cost investment. This study aimed to determine the factors that have an impact on the application of cleaner production. The method used is regression analysis. The regression analysis results showed that three variables were tested to be significant and had a Root Mean Square Error (RMSE) value of 3.05 which means good. Three variables that affected the implementation of cleaner production include measurement of fuel usage, efforts to improve production process efficiency, and waste reuse by product. From the calculation results, the coefficient of determination (R2) was 0.550 (the influence was quite strong). The results of this study can be used as a recommendation for the government to increase the implementation cleaner production in Jombang Regency.
ASSESSING CONTRIBUTORY FACTORS IN POTENTIAL HAZARD NATURAL GAS PIPELINE FAILURE Ahmad Hasnan; Zefry Darmawan; Ade Iskandar; Aswin Aswin; Diar Azzis Septian
JEMIS (Journal of Engineering & Management in Industrial System) Vol 11, No 1 (2023)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jemis.2023.011.01.3

Abstract

Increased energy demand in Indonesia is accompanied by increasing demand for natural gas, where in the next 50 years natural gas is predicted to be the number one energy source in Indonesia, pipeline is the cheapest way to distribute natural gas, in this way, length of pipeline infrastructure will increase year by year. it is still very much needed by both the household, industry, and power plants. The longer the pipeline, the risk of pipeline failure also increases, it is necessary to understand what factors have the most influence on pipeline failure, the method used is to create a factor matrix from a modified Muhlbauer, MICMAC is used to test the strength of the relationship between significant factors causing the potential hazard of pipeline failure. based on their influences and dependencies. The value of the dependency relationship between factors is determined from discussions with several pipeline experts in Indonesia, who work in related fields, the result is that there are three main factors that contribute major potential hazards, without being influenced by other factors, that is determining safety factors in the design process, depth pipeline and the existence of SOP in the pipeline system. One factor, namely depth, can be eliminated because there are government regulations requiring natural gas pipelines to be buried in the ground at a certain depth.
ELECTRIC VEHICLE ROUTING PROBLEM USING ADAPTIVE SIMULATED ANNEALING Prayoga Yudha Pamungkas; Rifdah Zahabiyah; Nadiah Ghina Shabrina
JEMIS (Journal of Engineering & Management in Industrial System) Vol 11, No 1 (2023)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jemis.2023.011.01.4

Abstract

Road transport is a major CO2 emission contributor globally. To tackle the challenge of reducing world carbon emissions, alternative technologies for the automobile industry are widely researched. The automotive industry has started to shift from Internal combustion engine (ICE) vehicles to electric vehicles (EVs), where EVs are the future of the automotive industry in terms of reducing greenhouse gas emissions and air pollution. EV manufacturers are continuously looking for opportunities to optimize the supply chain processes, aiming for supply chain resilience.  In this study, we present an Electric Vehicle Routing Problem (EVRP) to achieve the best decision, which is an extension of the traditional Vehicle routing problem (VRP) which in particular finding the shortest route for electric vehicles. The objective function is to find the best travel route that minimizes travel distance. Each route serves a set of customer nodes that starts and ends at a given depot node. We take battery capacity and charging stations as the constraints. In addition, the use of homogenous fleets and single depot are considered in this paper. A hybrid metaheuristic approach is used to find the best solution with the Adaptive Simulated Annealing algorithm. The use of adaptive in simulated annealing generates a higher probability of finding the best operators, which results in better solutions. A comparison of results from various metaheuristic methods is also presented in this paper to get the best method for the EVRP based on a benchmark dataset. This paper ends with recommendations for creating a routing plan that is resilient to disruptions to distribution.
ANALYSIS THE EFFECTIVENESS OF CNC TURNING MACHINES TYPE XTRA 420 USING THE OVERALL EQUIPMENT METHOD EFFECTIVENESS (OEE) Arifin Arifin; Ishardita Pambudi Tama; Yeni Sumantri
JEMIS (Journal of Engineering & Management in Industrial System) Vol 11, No 1 (2023)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jemis.2023.011.01.5

Abstract

The development of the manufacturing industry is increasing every year, of course this makes competition in the manufacturing industry increasingly stringent. This research was conducted at PT. Tjokro Bersaudara Gresik, focused on CNC Turning machines with the type CNC Lathe Machine XTRA 420, namely machines used to produce various types of automotive parts and based on data collected regarding the effectiveness of the machine, it shows that the machine has not fully worked effectively. This is indicated by the presence of downtime data, engine speed reduction data, and product data that does not meet specifications. To find out how good the effectiveness of a machine is, it can measure the OEE value of the machine.. It can be concluded that the effectiveness rate (OEE) of CNC Turning machines in the January-August 2022 period is between 54.16% to 59.91% with an average of 57.55% (still below the ideal OEE value of 85%) with a percentage six big losses of 42.45%.
ONLINE PARTIAL DISCHARGE MEASUREMENT FOR CONDITION-BASED MAINTENANCE OF HV POWER CABLES IN RAILWAY INFRASTRUCTURE Alfonsus Julanto Endharta; Jongwoon Kim; Yongseon Kim
JEMIS (Journal of Engineering & Management in Industrial System) Vol 11, No 1 (2023)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jemis.2023.011.01.6

Abstract

Partial discharge (PD) measurement as one of well-known method to evaluate the condition of high voltage (HV) power cables has been studied over many decades. Cable insulation failure could result in a power outage, which could then cause a loss of service in the transportation system and even dangerous events like fire accidents. It is of a great interest to railway infrastructure operators to monitor and identify the cable faults before any possible accident occurs. The paper focuses on the diagnostic problem to detect the HV cable fault based on the Phase Resolved Partial Discharge (PRPD) patterns. Classification models, such as Random Forest and Convolutional Neural Network, are considered to classify the pattern of PRPD based on the mostly occurring PD types in HV cables, such as corona, surface, and void patterns. Experiments are performed and the PRPD data from the experiments are collected. The optimal model is applied in the online monitoring program which will be used continuously to evaluate the cable condition and arrange the optimal schedule for maintenance. According to the analysis, both algorithm perform well in the PRPD pattern categorization, with accuracy up to 83.45%. This indicates that due to the more effective behavior, PD assessment with PD sensors is preferable.
STRATEGY FRAMEWORK DEVELOPMENT BASED ON BUSINESS COMMERCIAL INTEGRATING CO-CREATION PROCESS TO GUIDE PSS TRANSITION Kusumaningdyah, Widha; Himawan, Rakhmat; Ardianwiliandri, Raditya
JEMIS (Journal of Engineering & Management in Industrial System) Vol 11, No 1 (2023)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jemis.2023.011.01.7

Abstract

Product-Service System (PSS) is considered as a promising solution for manufacturing industry to address environmental and economic issues simultaneously. Despite the potential benefit, PSS uptake across industries is hardly found. This research aims to draw current state of manufacturing industry upon theoretical framework of PSS typology to get insights of the gap in between. The study exhibits PSS level assessment indicated by key character identified from the various literature of PSS typology. The study also introduces co-creation process as a strategy to increase system capability within PSS framework. Manufacturing companies are selected from various source of literature and article in PSS discussion to exercise PSS assessment. The evaluation of PSS current practice reveals that commercial based transaction (B2B and B2C) play a significant role to determine the suitable development strategy for PSS transition. Furthermore, the type of business commercial also determines the customer involvement level in co-creation process. A framework to guide PSS transition based on the business commercial is established, comprehends the type of value proposition, suitable business strategy, network configuration, and co-creation level.

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