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JKIE (Journal Knowledge Industrial Engineering)
Published by Universitas Yudharta Pasuruan
ISSN : 24600113     EISSN : 25414461     DOI : -
Core Subject : Science, Engineering,
Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Mechanical Engineering
JKIE is scientific journal that publishes research in the field of Industrial Engineering such: Industria Management, Optimization, Innovation, Ergonomics/Human Factors Engineering, Supply Chain Management, Operation Research, Statistic, Management Systems, Time & Motion Study, Manufacturing System, Production Planning & Inventory Control, Logictis, Engineering Economy, Modelling Systems, Simulation, Facilities Design & Work Space Design, Quality Engineering (SPC/TQM), Operation Management & Productivity Improvement, Product Design & Development, and Decision Planning & Analysis etc.
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Articles 3 Documents
 1 
Search results for , issue "Vol 13 No 1 (2026)" : 3 Documents clear
Determination of Maintenance Time Interval Scheduling on Jaw Crusher Machine with Reliability Centered Maintenance Method At PT. X In Rembang Muhyidin Agus Wibowo, Moh; Kalista, Anggia; Suwardana, Hendra; Parayuda, Muhammad Hendriyanto
Journal Knowledge Industrial Engineering (JKIE) Vol 13 No 1 (2026)
Publisher : Department of Industrial Engineering - Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/jkie.v13i1.3228

Abstract

The manufacturing industry in the construction-support mining sector faces significant challenges in maintaining the reliability of production equipment, particularly in jaw crusher machines used for andesite stone processing. Frequent machine breakdowns during production activities can reduce productivity, increase downtime, and cause financial losses. This study aims to identify critical components and determine optimal maintenance intervals using the Reliability Centered Maintenance (RCM) method. The analysis results indicate that the critical components of the jaw crusher machine are the Bearing, Toggle, Electric Motor, and Spring. The Bearing and Toggle components require corrective maintenance strategies with maintenance intervals of 111 days, while the Electric Motor and Spring components require preventive maintenance strategies with intervals of 119 days and 109 days, respectively. The proposed maintenance scheduling can be used as a basis for improving machine reliability, minimizing downtime, and enhancing maintenance effectiveness in the production process.
Relationship Between Organisational Culture and Customer Focus on Operational Performance: An Agile Manufacturing Approach Sutrisno; Yudha, Afiff; Narto
Journal Knowledge Industrial Engineering (JKIE) Vol 13 No 1 (2026)
Publisher : Department of Industrial Engineering - Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/jkie.v13i1.6810

Abstract

This paper aims to empirically test the relationships between organizational culture and customer focus, and their impact on operational performance in shipbuilding companies in the context of agile manufacturing. This research used a quantitative PLS-SEM method, with 155 respondents from 27 shipbuilding companies in Indonesia, collected via an online survey using random sampling. The results showed that organizational culture does not directly influence operational performance. Meanwhile, customer focus significantly affects operational performance, and it also mediates the relationship between organizational culture and operational performance. This study fills a gap in manufacturing strategy by adopting an agile manufacturing approach to improve the operational performance of shipbuilding companies, which is measured by indicators of construction time, quality, construction cost, and sales revenue. Besides, this study contributes empirical evidence on the relationship between organizational culture and customer focus, and their impact on operational performance in shipbuilding companies.
Integrating Green Overall Equipment Effectiveness (G-OEE) and Reduce Strategies: A Transformation Toward Sustainable Cigarette Manufacturing Sulistyowati, Enik; Hamidah, Nur; Riyana, Iis
Journal Knowledge Industrial Engineering (JKIE) Vol 13 No 1 (2026)
Publisher : Department of Industrial Engineering - Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/jkie.v13i1.6875

Abstract

The cigarette manufacturing sector currently faces a dual mandate: maximizing production efficicency while drastically reducing its environmental footprint. Traditional Overall Equipment Effectiveness (OEE) metrics often fail to capture ecological dimension, creating a significant measurement gap in sustainable performance. This study addresses this limitation by developing and validating an Integrated Green Overall Equipment Effectiveness (G-OEE) model. By embedding the "Reduce" principle of the Circular Economy (CE) into the classic OEE framework, this research provides a nuanced evaluation of manufacturing operations in East Java. Employing a mixed-methods approach, the study analyzed quantitative data from January 2025 to March 2026, encompassing Availability, Performance, Quality, and Reject rates. The proposed G-OEE model expands the traditional APQ pillars by integrating three critical Green Performance Factors: energy efficiency (GPF1), material utilization (GPF2), and a waste reduction index (GPF3). Findings reveal a striking disparity: while conventional OEE averaged 82.74%, the G-OEE score dropped to 62.20%. This gap effectively exposes hidden environmental inefficiencies that standard metrics typically overlook. The regression validation (R² = 0.89, RMSE = 3.2%) confirms the model’s high predictive validity, establishing G-OEE as a practical decision support tool for production managers. Ultimately, the G-OEE framework enables manufacturers to align Lean efficiency with Circular Economy responsibilities through a single, simultaneous monitoring tool.

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