Jurnal Teknologi dan Manajemen

Identification of Operational Performance in Service Operations through the Evaluation of Waiting Time and Technician Performance at AHASS Workshops

Fandi Hafid Sugianto — 2026-04-29

This study aims to evaluate the operational performance of AHASS motorcycle service workshops, where technicians' working hours and service speed are critical to ensuring service quality and operational efficiency. The workshop performance was assessed using the Overall Equipment Effectiveness (OEE) framework, combined with the Six Big Losses approach, to identify the main sources of time loss and formulate improvement strategies. Data were collected through field observations, interviews with technicians and workshop managers, and historical service records. Technician operational data were analyzed to calculate the OEE components, namely availability, performance, and quality, while Six Big Losses analysis and a Fishbone Diagram were applied to identify the root causes of inefficiencies. The results show that OEE values ranged from 82.49% to 87.15% during the observation period, with the highest value in April, and some months remained slightly below the world-class benchmark. Although the quality component consistently remained above 99%, decreases in availability and performance were the main factors reducing overall OEE. Breakdown losses were the largest contributor to inefficiency, accounting for 267.52 hours (37.37%) of total losses, followed by reduced speed losses at 24.75% and idling and minor stoppages at 22.44%. This study extends the application of OEE and Six Big Losses from the manufacturing sector to motorcycle service operations and provides practical insights for improving technician scheduling, optimizing service workflows, and supporting continuous performance improvement in service-based industries. These findings support data-driven decision-making.

The Implementation of Lean Automation and Kitting System Integration to Improve Assembly Line Efficiency in the Automotive Industry

Setiawan — 2026-04-29

The rapid development of the automotive industry in Indonesia has intensified global competition, requiring manufacturers to continuously improve production efficiency and operational performance. However, inefficiencies remain in the final-2 assembly line, where excessive non–value-added activities such as unnecessary operator movement and part searching contribute to a high cycle time and low Process Cycle Efficiency (PCE). This study aims to reduce production inefficiencies by identifying and eliminating waste in the assembly process. The research employs the Value Stream Mapping (VSM) method to analyze the current production flow and determine sources of non–value-added activities. Based on the analysis, improvement initiatives were implemented through the integration of Lean Automation and the Kitting System. Lean Automation reduces manual repetitive tasks and minimizes operational waste, while the Kitting System organizes and supplies components to the assembly line in a structured and timely manner. The implementation results show a significant improvement in production performance, where the cycle time decreased from 160.08 seconds to 88.08 seconds. Consequently, Process Cycle Efficiency increased from 53.03% to 57.89%. These findings demonstrate that integrating VSM with lean automation and structured kitting effectively enhances production efficiency and supports the development of a more competitive automotive manufacturing system.

Design and Performance Evaluation of a Motor-Driven Adjustable Speed Tool for Corrosion Removal on Bolt Threads in Steam Power Plant Applications

Kadex Widhy Wirakusuma — 2026-04-29

This study presents the design, fabrication, and experimental evaluation of a portable motor-driven adjustable-speed tool for localized corrosion removal on bolt threads in steam power plant maintenance. The prototype combines a variable-speed motor, a rotating wire brush, and a clamping fixture to ensure controlled contact with threaded surfaces. Performance was assessed on corroded bolts (M14 × 60 mm and M16 × 60 mm) at four spindle speeds (450, 900, 1350 and 1800 rpm), recording cleaning time, vibration, and surface temperature. Results show a strong inverse relationship between motor speed and cleaning time; for example, M16 bolts were cleaned in 1.37 minutes at 450 rpm and 0.36 minutes at 1800 rpm. A time-based cleaning efficiency metric peaked at higher speeds for the tested bolt sizes, while higher rpm also increased vibration and surface temperature, indicating an operational trade off. Compared with manual brushing, the prototype delivered faster, more uniform cleaning with reduced operator dependency and lower thread abrasion. An operational range of 1350–1800 rpm is recommended to balance effectiveness and mechanical/thermal constraints. Future work should include quantitative image-based area removal and gravimetric validation to corroborate surface integrity and material removal rates for field deployment.