Jurnal Sistem dan Manajemen Industri

Supply chain performance measurement incorporating green factors using the supply chain operations reference on a fertilizer company

Putri Jasmine Solekha, Qurtubi Qurtubi, Haswika Haswika, Danang Setiawan — Tue, 04 Jun 2024 10:49:42 +0700

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.

Intelligent optimisation for multi-objectives flexible manufacturing cells formation

Muhammad Ridwan Andi Purnomo, Imam Djati Widodo, Zainudin Zukhri — Tue, 04 Jun 2024 10:53:56 +0700

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.

Implementation system monitoring and control temperature and pH in urban silver catfish hatchery to enhance efficiency and responsiveness based on IoT

Firda Amalia, Syarifuddin Nasution — Tue, 04 Jun 2024 10:58:03 +0700

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

Chusnul Aprilianti, Annisa Kesy Garside, Amelia Khoidir, Thomy Eko Saputro — Tue, 04 Jun 2024 00:00:00 +0700

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.

Optimizing business location for small and medium enterprises considering travel time uncertainty, natural disasters, and density population: a study case in Jakarta

Herman Sjahruddin, Ahmad Faisal Dahlan — Tue, 04 Jun 2024 12:25:21 +0700

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.

Analysis of lean-agile-resilient-green (LARG) implementation in the electric car industry in Indonesia

Humiras Hardi Purba, Choesnul Jaqin, Siti Aisyah, Mutiara Nabilla — Thu, 27 Jun 2024 11:34:55 +0700

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.