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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 322 Documents
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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.

Page 33 of 33 | Total Record : 322

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