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OPERATION EXCELLENCE: Journal of Applied Industrial Engineering
Published by Universitas Mercu Buana
ISSN : 2085429     EISSN : 26545799     DOI : 10.22441/oe
Core Subject : Science,
Decision Sciences, Operations Research & Management
The aim of Operations Excellence: Journal of Applied Industrial Engineering (OE Journal) is to publish theoretical and empirical articles that are aimed to contrast and extend existing theories, and build new theories that contribute to advance our understanding of phenomena related with industrial engineering and industrial management in organizations, from the perspectives of Quality Engineering, Productivity Improvement, Logistic & Distribution, Supply Chain Management, Performance Management & Improvement System, Modelling, Operations Management, Optimization, Green Manufacturing.
Arjuna Subject : -
Articles 5 Documents
 1 
Search results for , issue "Vol. 17 No. 3 November 2025 In Press" : 5 Documents clear
An analysis of human errors in the receiving process of raw material warehouses in the automotive industry using HEART and SHERPA methods Alviandy, Anggie; Oktora, Raden Adriyani
Operations Excellence: Journal of Applied Industrial Engineering Vol. 17 No. 3 November 2025 In Press
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/oe.2025.v17.i3.151

Abstract

The development of industrial manufacturing automation drives the need for efficiency, but the majority of part receiving processes in the automotive warehouse department are still traditional, making them prone to human error. This research aims to identify the causes of human error in receiving, analyze its impact on warehouse accuracy and efficiency, and provide recommendations for improvement. Periodic data from July-December 2024 shows that 43.27% of warehouse errors occurred during receiving. The quantitative method Human Error Assessment and Reduction Technique (HEART) was applied to 6 main activities and 12 subtasks, resulting in the highest error probability (HEP) for the subtask of checking the physical condition of the part (HEP = 12.085). The qualitative approach Systematic Human Error Reduction and Prediction Approach (SHERPA) identified the dominance of action errors and checking errors, particularly in part checking, data input, material handling, and document verification. The combination of findings from HEART-SHERPA reveals that human error slows down the receiving process, disrupts actual stock, and delays production flow. Recommendations for improvement include (1) technical training and routine briefings to enhance operator competency, (2) implementing a buddy system and double verification using checklists, and (3) re-layouting the transit area with tag labels and structured archiving.
Analysis of the influence of service quality on customer satisfaction using the customer satisfaction index and servqual methods: a case study of PT Charoen Pokphand Indonesia Syarifuddin, Rizal; Asrul, Muhammad
Operations Excellence: Journal of Applied Industrial Engineering Vol. 17 No. 3 November 2025 In Press
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/oe.2025.v17.i3.152

Abstract

This study analyzes the influence of service quality on customer satisfaction at PT Charoen Pokphand Indonesia Tbk., Makassar Branch, using the Customer Satisfaction Index (CSI) and SERVQUAL methods. A questionnaire was employed to measure satisfaction levels, while SERVQUAL assessed five service dimensions: tangibles, reliability, responsiveness, assurance, and empathy. Results show a CSI score of 82.10%, placing customer satisfaction in the “Good” category. The responsiveness dimension had the largest gap, indicating a need to enhance service speed and responsiveness. Meanwhile, the tangible dimension had the smallest gap, suggesting potential improvements in physical aspects like cleanliness and facilities. Security concerns also emerged as a notable gap. Based on the gap analysis, improvements in tangible aspects and security systems are recommended to enhance customer loyalty and competitiveness.
Investigating the relationship between work incidents and musculoskeletal disorders in motorcycle technician workshops: a cross-sectional analysis Kurnia, Fikrihadi; Suartika, I Made
Operations Excellence: Journal of Applied Industrial Engineering Vol. 17 No. 3 November 2025 In Press
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/oe.2025.v17.i3.150

Abstract

Workplace hazards and incidents pose significant risks in the automotive industry, necessitating meticulous risk assessment and management. This cross-sectional study was designed to examine the prevalence of work-related injuries and musculoskeletal disorders (MSDs) among motorcycle technicians in workshops situated within Lombok Island, West Nusa Tenggara, Indonesia. A sample of 105 male participants was recruited for the study. Findings revealed that the majority of workers were aged between 20-30 years (67.6%), possessed vocational high school education (61%), were married (55.2%), had 1-10 years of work experience (83.8%), were smokers (58.1%), and abstained from alcohol consumption (83.8%). Workplace incidents predominantly comprised minor injuries (93.3%), with the hands being the most frequently affected body part (65.5%). Additionally, lower back MSDs were prevalent (74.3%) and significantly correlated with workplace incidents. The study concludes that upper extremities were the most commonly affected body part in both incidents and MSDs. These findings emphasize the value of prioritizing workplace safety and implementing preventative strategies to mitigate MSDs in motorcycle workshops, ultimately fostering worker well-being and enhancing workshop productivity.
Maintenance of automatic valve parts in soy blending tanks using the reliability centred maintenance method at PT KHAI Wiguna, Adityanata; Kusnadi, Kusnadi; Nugraha, Asep Erik
Operations Excellence: Journal of Applied Industrial Engineering Vol. 17 No. 3 November 2025 In Press
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/oe.2025.v17.i3.153

Abstract

In the manufacturing industry, effective machine maintenance is essential to ensure production continuity and prevent downtime. PT KHAI faces performance degradation and damage to the automatic valve parts in its soy blending tanks, leading to significant production losses. This study analyzes the maintenance of these components using the Reliability Centred Maintenance (RCM) method. The novelty of this research lies in its specific application to piston-actuated butterfly valves within the liquid handling systems of the food processing industry, a specialized area that remains under-explored compared to heavy machinery or power plant sectors. The methodology involves system identification, Failure Mode and Effect Analysis (FMEA), Logic Tree Analysis (LTA), and Task Selection. The results identify critical failure components, including actuators, bearings, seals, packing valves, solenoid valves, limit switches, and control systems. The proposed maintenance strategy consists of time-directed tasks for four components, condition-directed for one component, and finding failure for three components. In conclusion, this study provides a new framework for mitigating hidden failures in automated actuation systems, offering a replicable maintenance model for ensuring high-hygiene production efficiency in the food industry.
Optimizing the Inventory Fulfillment Level of Store Goods from PT. XYZ Warehouse with the Application of Response Surface Methodology Ardyani, Anggarnis Dwikalyana; Donoriyanto, Dwi Sukma
Operations Excellence: Journal of Applied Industrial Engineering Vol. 17 No. 3 November 2025 In Press
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/oe.2025.v17.i3.154

Abstract

Inventory management in retail warehouses is increasingly challenged by demand volatility and supplier lead time uncertainty. Conventional inventory approaches such as EOQ or min–max control often fail to capture the simultaneous interaction among multiple operational factors, resulting in stock shortages or overstock conditions. PT XYZ experiences recurring fulfillment gaps in non-food products, particularly toiletries, where warehouse stock is unable to consistently meet sub-branch demand. This study proposes the application of Response Surface Methodology (RSM) to model and optimize warehouse inventory fulfillment levels. A Box–Behnken experimental design involving three factors—store demand, supplier incoming goods, and delivery lead time—at three levels generated 15 experimental runs. ANOVA results confirm the statistical significance of the model (F = 176.29) with no lack of fit, while the coefficient of determination (R² = 0.996) indicates strong explanatory power. The optimal inventory level identified through matrix analysis is 18,697.27 units under specific operational conditions. The findings demonstrate that RSM effectively captures factor interactions and provides a data-driven decision framework for inventory optimization. This study contributes methodologically by extending RSM application in retail warehouse management and offers managerial insights to improve service level performance and reduce logistics inefficiencies.

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