cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
-
Contact Email
-
Phone
-
Journal Mail Official
-
Editorial Address
-
Location
Kota malang,
Jawa timur
INDONESIA
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 364 Documents
 33   34   35   36   37 
ASSESSING CONTRIBUTORY FACTORS IN POTENTIAL HAZARD NATURAL GAS PIPELINE FAILURE Hasnan, Ahmad; Darmawan, Zefry; Iskandar, Ade; Aswin, Aswin; Septian, Diar Azzis
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.
ANALYSIS THE EFFECTIVENESS OF CNC TURNING MACHINES TYPE XTRA 420 USING THE OVERALL EQUIPMENT METHOD EFFECTIVENESS (OEE) Arifin, Arifin; Tama, Ishardita Pambudi; Sumantri, Yeni
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%.
ELECTRIC VEHICLE ROUTING PROBLEM USING ADAPTIVE SIMULATED ANNEALING Pamungkas, Prayoga Yudha; Zahabiyah, Rifdah; Shabrina, Nadiah Ghina
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.
ONLINE PARTIAL DISCHARGE MEASUREMENT FOR CONDITION-BASED MAINTENANCE OF HV POWER CABLES IN RAILWAY INFRASTRUCTURE Endharta, Alfonsus Julanto; Kim, Jongwoon; Kim, Yongseon
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.

Page 37 of 37 | Total Record : 364

 33   34   35   36   37 

Filter by Year

2013 2025


Reset
Filter By Issues
All Issue Vol. 13 No. 2 (2025) Vol. 13 No. 1 (2025) Vol. 12 No. 2 (2024) Vol 12, No 2 (2024): (in process) Vol 12, No 1 (2024) Vol. 12 No. 1 (2024) Vol 11, No 2 (2023) Vol. 11 No. 2 (2023) Vol. 11 No. 1 (2023) Vol 11, No 1 (2023) Vol 10, No 2 (2022) Vol. 10 No. 2 (2022) Vol 10, No 1 (2022) Vol. 9 No. 2 (2021) Vol 9, No 2 (2021) Vol 9, No 1 (2021) Vol. 9 No. 1 (2021) Vol. 8 No. 2 (2020) Vol 8, No 2 (2020) Vol 8, No 1 (2020) Vol. 8 No. 1 (2020) Vol. 7 No. 2 (2019) Vol 7, No 2 (2019) Vol. 7 No. 1 (2019) Vol 7, No 1 (2019) Vol 6, No 2 (2018) Vol. 6 No. 2 (2018) Vol. 6 No. 1 (2018) Vol 6, No 1 (2018) Vol. 5 No. 2 (2017) Vol 5, No 2 (2017) Vol. 5 No. 1 (2017) Vol 5, No 1 (2017) Vol 4, No 2 (2016) Vol. 4 No. 2 (2016) Vol 4, No 1 (2016) Vol. 4 No. 1 (2016) Vol. 3 No. 2 (2015) Vol 3, No 2 (2015) Vol. 3 No. 1 (2015) Vol 3, No 1 (2015) Vol 2, No 2 (2014) Vol 2, No 2 (2014) Vol. 2 No. 2 (2014) Vol. 2 No. 1 (2014) Vol 2, No 1 (2014) Vol 1, No 1 (2013) Vol. 1 No. 1 (2013) More Issue