Jurnal Sistem dan Manajemen Industri

A modified Aquila optimizer algorithm for optimization energy-efficient no-idle permutation flow shop scheduling problem

2023-12-01T10:00:47+07:00

Increasing energy consumption has faced challenges and pressures for modern manufacturing operations. The production sector accounts for half of the world's total energy consumption. Reducing idle machine time by employing No-Idle Permutation Flow Shop Scheduling (NIPFSP) is one of the best decisions for reducing energy consumption. This article modifies one of the energy consumption-solving algorithms, the Aquila Optimizer (AO) algorithm. This research contributes by 1) proposing novel AO procedures for solving energy consumption problems with NIPFSP and 2) expanding the literature on metaheuristic algorithms that can solve energy consumption problems with NIPFSP. To analyze whether the AO algorithm is optimal, we compared by using the Grey Wolf Optimizer (GWO) algorithm. It compares these two algorithms to tackle the problem of energy consumption by testing four distinct problems. Comparison of the AO and GWO algorithm is thirty times for each case for each population and iteration. The outcome of comparing the two algorithms is using a t-test on independent samples and ECR. In all case studies, the results demonstrate that the AO algorithm has a lower energy consumption value than GWO. The AO algorithm is therefore recommended for minimizing energy consumption because it can produce more optimal results than the comparison algorithm.

Optimisation-in-the-loop simulation of multi products single vendor-multi buyers supply chain systems with reactive lateral transhipment

2023-12-02T16:17:10+07:00

Considering that batik is one of the most popular products in Indonesia, it is important to analyse the supply chain system for batik products. In reality, the supply chain system for batik products enables orders between buyers to receive products more rapidly, allowing them to anticipate stock outs and obtain lower ordering costs than when ordering from vendors. It is referred to as reactive lateral transshipment. This paper discusses the development of a simulation-based stochastic optimisation model for a batik product supply chain system with multiproducts and single vendor-multi buyers. The utilised solution searching algorithm is a modified Genetic Algorithms (GA) executed in-loop with the developed simulation-based stochastic model. The results demonstrate that the proposed modified GA is able to provide a global optimum solution, allowing the proposed simulation-based stochastic model to reduce the joint total cost (JTC) of the investigated supply chain system by up to 19% when compared to the local optimisation model in each supply chain party.

Integration models of demand forecasting and inventory control for coconut sugar using the ARIMA and EOQ modification methods

2023-12-02T10:07:00+07:00

Inventory control is critical because the inability to overcome inventory problems causes unpreparedness to meet consumer demand. MSMEs Bekawan Agro Coconut Sugar, independently around 35% -70%, cannot meet consumers' demand for coconut sugar, so an inventory control model is needed. Inventory control models must integrate with demand forecasting as an inventory control input. This study aims to integrate the demand forecasting model with the inventory control model. The method used for demand forecasting is ARIMA. The inventory control model uses a modified EOQ hybrid method because coconut sugar products have a shelf life; they also use coconut sap as raw material, which must be processed to prevent fermentation. The research results show that demand forecasting for one year ahead is a total of 10,310.82 Kilograms with an economic lot size of 120 Kilograms and a reorder point when the inventory position is 30 Kilograms. Daily production of 30 kilograms requires 210 litres of coconut sap/per day. The amount of sap needed requires 105 coconut trees / per day. Arrival time of coconut sugar at the storage warehouse every five days. The resulting model can be a solution for sustainable MSMEs.

Optimizing lot sizing model for perishable bread products using genetic algorithm

2023-12-02T10:07:47+07:00

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.

Design and implementation of intelligent electronic component inspection based on PLC and vision system

2023-12-02T13:55:59+07:00

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.

Fatigue analysis and design of a motorcycle online driver measurement tool using real-time sensors

2023-12-19T19:42:45+07:00

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

2023-12-28T14:20:43+07:00

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%.