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INDONESIA
Jurnal Sistem dan Manajemen Industri
ISSN : 25802887     EISSN : 25802895     DOI : -
Core Subject : Engineering,
This journal aims to publish the results of research in the field of Industrial Engineering is published twice a year, managed by the University of Serang Raya. The scope of Sciences covers Operations Research, Manufacturing System, Industrial Management, Ergonomics and Work System, Logistics and Supply Chain Management, and other scientific studies in accordance with scope field of Industrial Engineering research.
Arjuna Subject : -
Articles 256 Documents
Design and implementation of intelligent electronic component inspection based on PLC and vision system Ikatrinasari, Zulfa Fitri; Herlambang, Hendi; Kosasih, Kosasih
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 2 (2023): December
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i2.6511

Abstract

Customer demands for product quality are increasingly complex, requiring better inspection accuracy. It is not enough if done manually because it requires high costs and varying operator accuracy. Automatic vision inspect­ion was developed to check the product quality of terminal-type electronic components To solve this problem. Design intelligent inspection uses a conveyor driven by a stepper motor, a photosensor to calculate product distance, guides position to direct the product, a vision camera to detect product quality, cylinder ejection for product selection, and PLC as a control system. The process of detecting normal and abnormal product quality is carried out using computer logic control, then separating the ab­normal product into the reject box through the ejection cylinder. The machine speed is 60 pieces/minute. The system evaluation results are carried out on three parts of the system: the success rate on the vision camera is 100%, automatic product sorting through the cylinder ejection rate success is 100%, and the success rate for product positioning is 97.5%. This research provides a useful reference for developing intelligent automatic inspection technology in electronic components.
Optimizing lot sizing model for perishable bread products using genetic algorithm Asih, Hayati Mukti; Leuveano, Raden Achmad Chairdino; Dharmawan, Dhimas Arief
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 2 (2023): December
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i2.7172

Abstract

This research addresses order planning challenges related to perishable products, using bread products as a case study. The problem is how to effi­ci­ently manage the various bread products ordered by diverse customers, which requires distributors to determine the optimal number of products to order from suppliers. This study aims to formulate the problem as a lot-sizing model, considering various factors, including customer demand, in­ven­tory constraints, ordering capacity, return rate, and defect rate, to achieve a near or optimal solution, Therefore determining the optimal order quantity to reduce the total ordering cost becomes a challenge in this study. However, most lot sizing problems are combinatorial and difficult to solve. Thus, this study uses the Genetic Algorithm (GA) as the main method to solve the lot sizing model and determine the optimal number of bread products to order. With GA, experiments have been conducted by combining the values of population, crossover, mutation, and generation parameters to maximize the feasibility value that represents the minimal total cost. The results obtained from the application of GA demonstrate its effectiveness in generating near or optimal solutions while also showing fast computational performance. By utilizing GA, distributors can effectively minimize wastage arising from expired or perishable products while simultaneously meeting customer demand more efficiently. As such, this research makes a significant contri­bution to the development of more effective and intelligent decision-making strategies in the domain of perishable products in bread distribution.
Supply chain performance measurement incorporating green factors using the supply chain operations reference on a fertilizer company Solekha, Putri Jasmine; Qurtubi, Qurtubi; Haswika, Haswika; Setiawan, Danang
Jurnal Sistem dan Manajemen Industri Vol. 8 No. 1 (2024): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v8i1.7499

Abstract

The fertilizer industry plays a crucial role in assuring the food security of a nation, but it also faces significant environmental obstacles. These problems often contribute to decreased supply chain efficiency and overall industrial productivity. The industry's focus on profit maximization hinders adopting green supply chain strategies. This paper examines company q's adoption of green supply chain management (GSCM) practices. This study evaluates its performance using the green supply chain operations reference (Green SCOR) model, scoring 73.54 out of 100, classifying it as 'good.' However, there is room for improvement, especially concerning key performance indicators (KPIs). This paper identifies six KPIs that fall below satisfactory levels and offers specific recommendations for improvement. This study significantly contributes to the fertilizer industry by providing actionable insights for practitioners and advancing theoretical understanding by highlighting key overlooked indicators. Furthermore, this research also emphasizes the crucial role of government policies in stimulating the implementation of sustainable supply chain practices.
Fatigue analysis and design of a motorcycle online driver measurement tool using real-time sensors Soenandi, Iwan Aang; Oktavera, Isnia; Lusiana, Vera; Widodo, Lamto; Harsono, Budi
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 2 (2023): December
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i2.7500

Abstract

Work fatigue is an important aspect and is very influential in determining the level of accidents, especially motorbike accidents. According to WHO, almost 30% of all deaths due to road accidents involve two- and three-wheel­ed motorized vehicles, such as motorbikes, mopeds, scooters and electric bicycles (e-bikes), and the number continues to increase. Motor­cycles dominate road deaths in many low- and middle-income countries, where nine out of ten traffic accident deaths occur among motorcyclists, as in Indonesia. However, until now, in Indonesia, there has been no monitor­ing system capable of identifying fatigue in motorbike drivers in the transportation sector. This research aims to determine fatigue patterns based on driver working hours and create a sensor system to monitor fatigue measurements in real-time to reduce the number of accidents. The research began with processing questionnaire data with Pearson correlation, which showed a close relationship between driver fatigue and driving time and a close relationship between fatigue and increased heart rate and sweating levels. From calibration tests with an error of 3% and direct measurements of working conditions, it was found that two-wheeled vehicle driver fatigue occurs after 2-3 hours of work. With a measurement system using the Box Whiskers analysis method, respondents' working conditions can also be de­ter­mined, which are divided into 4 zones, namely zone 1 (initial condition or good condition), zone 2 a declining condition, zone 3 a tired condition and zone 4 is a resting condition. Hopefully, this research will identify fati­gue zones correctly and reduce the number of accidents because it can iden­tify tired drivers so they do not have to force themselves to continue working and driving their motorbikes. As a conclusion from this research, a measure­ment system using two sensors, such as ECG and GSR can identify work fatigue zones well and is expected to reduce the number of accidents due to work fatigue.
Reduced painting defects in the 4-wheeled vehicle industry on product type H-1 using the lean six sigma-DMAIC approach Zulkarnaen, Iskandar; Kurnia, Hibarkah; Saing, Bungaran; Apriyani, Apriyani; Nuryono, Arif
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 2 (2023): December
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i2.7512

Abstract

The current era provides challenges for several automotive industries to be able to compete and maintain the quality of their products. For four-wheeled auto­motive companies, satisfying customers regarding the visual appear­ance of the vehicle body is very important. However, internally, automotive companies still found many defects or failures in painting, amounting to 32.6%. Apart from that, rework also results in additional costs that the company must incur during the painting process. This study aims to clarify types of painting defects, analyze root causes, provide solutions, improve process capabilities, and in­crease the sigma level in the painting process in the four-wheeled vehicle industry. This study uses the Lean Six Sigma method, which is integrated into the DMAIC approach and other improve­ment tools. As a result, this study clarifies four critical defects in the orange peel defects of the painting section, craters, melting, and blur. This study has resulted in several corrective action solutions, including tightening supervision of the performance of painting section operators so that they are consistent and committed to working according to the Standard Operational Procedure (SOP) or work instructions that have been created. A competency matrix is used to evaluate operator performance, which is reported to super­iors and subordinates by the supervisory depart­ment. After carrying out corrective action, this study increased the process capability from 1.17 to 1.92. The higher the capability value, the higher the sigma level. This study also has increased the sigma level from 2.76 to 3.42, meaning an increase of 78%. .
Sistem Monitoring dan Pengendalian Cerdas Pembenihan Patin Berbasis Urban Farming Menggunakan Internet of Things (IoT) Amalia, Firda; Nasution, Syarifuddin
Jurnal Sistem dan Manajemen Industri Vol. 8 No. 1 (2024): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v8i1.7544

Abstract

AKA Farm is an urban agriculture-based silver catfish hatchery enterprise in Bogor Regency. AKA Farm has successfully met local demand for silver catfish fry production by utilizing limited space within vacant houses in Cihideung Ilir village. The comprehensive facilities, including electricity, wells, roads, and drainage channels, support the success of this operation. Challenges in the silver catfish hatchery are associated with low efficiency and responsiveness due to the complexity of the production process, resulting in suboptimal harvest outcomes. The primary contribution of this research lies in developing and implementing an innovative IoT-based monitoring and control system to address water quality conditions, as fluctu­ations in water temperature and pH significantly impact fish metabolism and survival. The main objective of this study is to improve efficiency and responsiveness in the hatchery process, aiming for optimal harvest out­comes. The integrated system utilizes the Blynk application for real-time moni­toring and control. Another advantage of the system is its automation; when the temperature and pH are not optimal, the actuators automatically optimize the aquarium conditions according to applicable standards. The actuators control heating lamps and release acidic or basic solutions. The system performs real-time and remote monitoring and control, reducing delays in responding to changes in the aquarium environment ultimately sub­stantially improving the survival and growth of silver catfish. Impli­cations of this research include assisting farmers in saving time and energy while increasing the productivity of silver catfish hatcheries. The study also reinforces the system's ability to create reliable water quality, supporting the well-being of silver catfish and ultimately enhancing performance in urban farming.
Economic production quantity model with defective items, imperfect rework process, and lost sales Aprilianti, Chusnul; Garside, Annisa Kesy; Khoidir, Amelia; Saputro, Thomy Eko
Jurnal Sistem dan Manajemen Industri Vol. 8 No. 1 (2024): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v8i1.7580

Abstract

This study proposes an economic production quantity (EPQ) model that comprehensively addresses scrap items, imperfect quality items, rework processes, and shortages. The model incorporates various types of defective items, including scrap, imperfect quality, and rework able items, and implements immediate rework processes upon the completion of regular production. Shortages are treated as lost sales, enhancing the accuracy of inventory cost estimations. Numerical experiments demonstrate the opti­mal­ity of production lot sizes and underscore the impact of production and demand rate adjustments on overall inventory costs. Sensitivity analysis further elucidates the influence of imperfect quality items on inventory costs. This EPQ model offers a comprehensive approach to efficient and effective finished product inventory management by integrating consider­ations for scrap items, imperfect quality items, and rework processes. Addi­tionally, a furniture manufacturing company case is presented to illustrate the practical application of the proposed model.
Analysis of lean-agile-resilient-green (LARG) implementation in the electric car industry in Indonesia Purba, Humiras Hardi; Jaqin, Choesnul; Aisyah, Siti; Nabilla, Mutiara
Jurnal Sistem dan Manajemen Industri Vol. 8 No. 1 (2024): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v8i1.7674

Abstract

Vehicle type approval (VTA) total registration of electronic vehicles in Indonesia for the accumulation period until August 2023 is 81,525 units with a composition of 4-wheeled vehicles 18,300 units. The use of electric vehicles is still a tiny portion compared to the motorized vehicle population in Indonesia, which will reach more than 146 million units in 2022. It is different from developments in Europe, the United States, and China, where more research into the use of electric vehicles is being carried out. The readiness of the automotive industry system to produce electric vehicles is absolutely necessary to achieve superior productivity levels. National auto­motive companies need to anticipate that changes in production systems will also change along with changes in processes and components in electric vehicles. In the next few years, world-class manufacturing production systems will refer to LARG (lean, agile, resilient, and green) aspects. Lean, agile, resilient, and environmentally friendly manufacturing industrial opera­tions are critical. This research aims to determine the level of appli­cation of LARG aspects in the electric vehicle automotive industry. The method used was exploratory, and a questionnaire was filled out with industry experts and analyzed using the analytical hierarchy process (AHP) and objective matrix (OMAX). The results of this study confirm that all aspects of LARG require improvement. Resilience (R) and green (G) have performance below 10 percent, so these two aspects are priorities for improvement by the electric car industry in Indonesia.
Intelligent optimisation for multi-objectives flexible manufacturing cells formation Purnomo, Muhammad Ridwan Andi; Widodo, Imam Djati; Zukhri, Zainudin
Jurnal Sistem dan Manajemen Industri Vol. 8 No. 1 (2024): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v8i1.7974

Abstract

The primary objective of conventional manufacturing cell formation typically uses grouping efficiency and efficacy measurement to reduce voids and exceptional parts. This objective frequently leads to extreme solutions, such as the persistently significant workload disparity among the manu­facturing cells. It will have a detrimental psychological impact on operators who work in each formed manufacturing cell. The complexity of the problem increases when there is a requirement to finish all parts before the midday break, at which point the formed manufacturing cells can proceed with the following production batch after the break. This research examines the formation of manufacturing cells using two widely recognized intelligent optimization techniques: genetic algorithm (G.A.) and particle swarm optimisation (PSO). The discussed manufacturing system has flexible machines, allowing each part to have multiple production routing options. The optimisation process involved addressing four simultaneous objectives: enhancing the efficiency and efficacy of the manufacturing cells, minimizing the deviation of manufacturing cells working time with the allocated working hours, which is prior to the midday break, and ensuring a balanced workload for the formed manufacturing cells. The optimisation results demonstrate that the G.A. outperforms the PSO method and is capable of providing manufacturing cell formation solutions with an efficiency level of 0.86, efficacy level as high as 0.64, achieving a minimum lateness of only 24 minutes from the completion target before midday break and a maximum difference in workload as low as 49 minutes.
Optimizing business location for small and medium enterprises considering travel time uncertainty, natural disasters, and density population: a study case in Jakarta Sjahruddin, Herman; Dahlan, Ahmad Faisal
Jurnal Sistem dan Manajemen Industri Vol. 8 No. 1 (2024): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v8i1.8224

Abstract

This study addresses the critical problem of identifying optimal business locations for small and medium enterprises (SMEs), a decision-making process by factors such as travel time uncertainty, natural disasters, and population density. Existing research in this area has not adequately addressed these complexities, leaving a knowledge gap that this study aims to fill. Our research employs two optimization methods, differential evolu­tion (DE) and mixed integer programming (MIP), to maximize customer coverage. We present a comprehensive model that not only determines optimum and near-optimum business locations but also investigates the scalability of the algorithms with increasing facilities and their adaptability to different traffic scenarios. Key findings indicate that the DE algorithm, in particular, demonstrates superior coverage performance. This study contributes to the field by providing a robust and adaptable model for facility location problem-solving. The insights gained have practical applications for both academia and industry, aiding SMEs in making informed, strategic decisions about business location placement.