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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 216 Documents
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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.
OPTIMIZATION OF FLEET UTILIZATION AND WAITING TIME IN SUPPLY CHAIN AGENT-BASED SIMULATION USING REINFORCEMENT LEARNING Tama, Ishardita Pambudi; Sujarwo, Sujarwo; Hardiningtyas, Dewi; Nugroho, Willy Satrio
JEMIS (Journal of Engineering & Management in Industrial System) Vol 12, No 1 (2024)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Inventory to transport transition was a critical operation that requires high efficiency in manufacturing. This study models the inventory transition of manufacturing plants in a supply chain network. The objective was to configure the minimum fleet utilization with fastest waiting time.  The configuration was performed using reinforcement learning assisted agent-based model (ABM) simulation. The ABM with fleet speed control have the best performance with average waiting time of 5.84 hours with lowest fleet utilization which surpasses other models. Lower fleet and waiting time provide rest periods for the driver. Therefore, performing speed control during transport improves human factor of the supply chain operation.
ANALYSIS OF PHYSIOLOGICAL ERGONOMICS FOR NIGHT SHIFT WORKERS CORRELATED WITH SLEEP QUALITY AND TIME TO RECOVERY Sugiono, Sugiono; Yuenyongchaiwat, Kornanong; Azlia, Wifqi; Lukodono, Rio Prasetyo; Putro, Wisnu Wijayanto; Sari, Sylvie Indah Kartika; Indrayadi, Bambang
JEMIS (Journal of Engineering & Management in Industrial System) Vol 11, No 2 (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.2023.011.02.5

Abstract

The worker’s recovery time from physical and mental workload is a crucial factor for office and factory management and it will effect on the working performance and design working system. The aim of this paper is to investigate the impact of physiological conditions on sleep quality and time to recovery for night shift electric steam power plant workers. The research is started with study literatures on physiology ergonomics, sleep quality measurement, human metabolism, expenditure energy graph and physical/mental workload. The research worked with 50 samples (age between 30 to 45 years old) who have duty to control the electric steam power plant on dynamic computer screen in the night shift. The Pittsburgh Sleep Quality Index (PSQI) questionnaire was used subjectively to measure the value of sleep quality on 19 self – rated questions that assessed various sleep quality – related factor over the previous month. To know the speed of Time to Recovery (TTR), every worker perform a treadmill load with constant speed of 5 Km/hour for 10 minutes. Heart rate changes before activity, during activity (treatment) and TTR are recorded and it be analysed the pattern of relationship conducting to PSQI score. According to the data analysis, the higher PSQI score the longer time consume by workers to recovery. Moreover, Pearson statistic test results found that there is a strong relationship between sleep quality (PSQI value) and TTR for workers with value of 0.853. In sort, improving the quality of sleep for night shift electric steam power plant workers can definitely improve work performance on a shorter rest time or healthier conditions of workers.
A FRAMEWORK FOR OBSERVATIONAL DATA-BASED RESPONSE SURFACE METHODOLOGY Hadiyat, Mochammad Arbi; Sopha, Bertha Maya; Wibowo, Budhi Sholeh
JEMIS (Journal of Engineering & Management in Industrial System) Vol 12, No 2 (2024): (in process)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Response Surface Methodology (RSM) is an integrated tool for optimization purposes based on an experiment; it consists of three stages of analysis, i.e., the design of experiment (DoE), causality modeling, and response optimization. The designed experiment ensures the researcher fully controls all factors that potentially influence the response and simultaneously fulfills the orthogonal assumption among factors. On the other side, conducting DoE for a continuous production process raises difficulties since it should be interrupted during experiment runs. Meanwhile, the rapid development of production data acquisition systems provides stored records or observational data with potentially useful information for supporting process optimization. This paper proposes an alternative framework for adopting observational data for RSM analysis. Referring to three stages of classic RSM and adopting the instance selection concept in the data mining context, the proposed framework aimed to achieve an observational data condition similar to an orthogonal D-optimal DoE based on criteria of Variance Inflation Factor (VIF) and determinant of matrix containing factor levels. It starts by applying a genetic algorithm for iteratively selecting an orthogonal subset of observational data and generating new actual experiment points to satisfy an orthogonality criterion. Then, a linear RSM model is fitted and continued by adding new experiment points. Then a standard numerical optimization method is applied to search among factor levels that optimize the response. A simulated data-based case study was taken in this paper, aiming to maximize a response of a production process with some pre-determined factors. The proposed framework has been implemented successfully, orthogonality of the data subset is achieved, and an optimal solution is found. Both criteria show the acceptable result and raise some improvement opportunities
A STUDY OF RESEARCH PAPER-BASED QUESTIONNAIRE DESIGN METHODS USING CO-OCCURRENCE NETWORKS Fujiyama, Kojiro; Masuda, Koji; Oktavianty, Oke; Haruyama, Shigeyuki
JEMIS (Journal of Engineering & Management in Industrial System) Vol 12, No 1 (2024)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The creation of questionnaire forms based on research papers has been done for various purposes. In previous studies, the surveyor intentionally created questions to be used in questionnaires based on secondary research and the knowledge of the researcher, and it is unclear what procedure was used to create the questions. Therefore, in this study, we examined and discussed methods of mechanically creating questions based on a review of research papers. As a result, we proposed a new method to create questions by mechanically combining words obtained from the article search, text mining of extracted articles, and co-occurrence word search. 
AN ANALYSIS : RELATIONSHIP BETWEEN WORKLOAD AND MENTAL HEALTH ON HEATHCARE WORKERS Salsabila, Zulfi Fathiya; Dharmastiti, Rini
JEMIS (Journal of Engineering & Management in Industrial System) Vol 12, No 1 (2024)
Publisher : Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Mental health is an important part in addition to physical health. Mental health problems are also faced by health workers due to the relatively high burden in their work. Based on the targets of the Sustainable Development Goals (SDGs), mental health is one of the areas of health and well-being. On the other hand, excessive workload is a source of fatigue, which is the root of burnout. The purpose of this study is to analyze the relationship between workload and mental health of health workers in a hospital. This study used a non-experimental method, namely cross sectional. Data were obtained from 49 respondents through a survey using an online questionnaire distributed by convenience sampling method. Respondents consisted of doctors (specialist and general), nurses, midwives, and pharmaceutical technical personnel. The workload questionnaire was adopted from the NASA-TLX, while mental health used the MBI-TBI. Relationship analysis was conducted using PLS-SEM using SmartPLS 4.0. The workload results obtained from this study were 65.87 or in the high category, with an allocation of very high workload of 27%, high as much as 53%, somewhat high 18%, and medium 2% of the total respondents. Factors related to mental load, physical load, and effort are the most dominant factors. The results for mental health obtained that emotional exhaustion in health workers is in the medium category (51%), personal achievement in the high category (80%), and for depersonalization in the high category (57%). The results of the correlation test between workload and the three factors on mental health found that workload has a significant relationship with the factors of emotional exhaustion and depersonalization (cynicism) with a probability of both <0.005, namely 0.000 and 0.001. The results of this study indicate that workload in health workers affects mental health, namely emotional exhaustion by 0.457 and depersonalization by 0.397. Thus, in order to maintain the mental health of health workers, intervention recommendations need to be made according to the results of this study.workload; mental health; healthcare workers, NASA-TLX; PLS-SEM
PLASTIC PACKAGING WASTE MANAGEMENT THROUGH FILLING MACHINE WITH AGILE REENGINEERING PROJECT MANAGEMENT APPROACH Patricia, Gracella; Muslim, Erlinda
JEMIS (Journal of Engineering & Management in Industrial System) Vol 11, No 2 (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.2023.011.02.1

Abstract

In Indonesia, the number of plastic wastes has reached 66 million tons per year in which 50% of them come from plastic packaging waste. Meanwhile, the recycling of plastic packaging waste only reaches 14%. Hence, it is highly urgent to be aware of plastic packaging waste management in order to tackle this issue. The research discussed the capability and potential of applying digitalization and automation to Smart Retail Technology which focuses on filling machines to manage plastic packaging waste management and increase the competitive advantage. This research uses two main approaches, namely Business Process Reengineering and Agile Project Management to recommend a new business process on ongoing project. The result of the study suggests the urgency to take advantage of the QR Code and Human Machine Interface to maximize the effectiveness and results of implementing the business process. By using simulation, this effort is expected to reach up to 334 consumers each day with up to 42.14% of machine utilization.

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