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All Journal Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse)
Indro Prakoso
Department of Industrial Engineering, Faculty of Engineering, Universitas Jenderal Soedirman, Purwokerto, Indonesia
Aerospace Engineering Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Standard Work Type 3-Based Work Time Measurement and Workload Balancing Analysis Using Yamazumi Chart Ari Andriyas Puji; Indro Prakoso; Muhamad Fauzan Arridho
Journal of Ocean, Mechanical and Aerospace -science and engineering- Vol 70 No 2 (2026): Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse)
Publisher : International Society of Ocean, Mechanical and Aerospace -scientists and engineers- (ISOMAse)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36842/jomase.v70i2.636

Abstract

Load imbalances among Material Handling (MH) operators in the automotive manufacturing industry may result in overload or idle conditions, thereby disrupting material supply and delivery accuracy. This study measured the cycle of time standard of MH activities using the Standardized Work Type 3 (SW Type 3) method, analyses workload distribution through Workload Analysis and the Yamazumi Chart, and designs a feasible workload-balancing scenario for automotive component manufacturing companies. Data were collected via time studies with five repetitions per activity in the Finished Goods (FG), Delivery, and Brake Assembly/Drum in Hat (BA/DIH) areas. Results indicated that the FG area was overloaded, with utilization rates of 115.7–120.0% of the available 480 minutes per shift. The Delivery area experienced critical overload, with utilization rates ranging from 177.0% to 207.8%. In contrast, the BA/DIH area exhibited a maximum workload gap of 70.9 minutes per shift, despite all operators remaining below the available time. The job-balancing scenario, implemented through the redistribution of Supply Empty Box activities, reduced the workload gap among operators by 72.2%, ensuring all operators remained within their available time.
Maintenance System Improvements to Increase Reliability of Continuous Frying Machine Using FMECA and RCM Indro Prakoso; Ari Andriyas Puji; Nur Fitriyah Mufarrihah; Amanda Sofiana; Ali Alhamidi
Journal of Ocean, Mechanical and Aerospace -science and engineering- Vol 70 No 2 (2026): Journal of Ocean, Mechanical and Aerospace -science and engineering- (JOMAse)
Publisher : International Society of Ocean, Mechanical and Aerospace -scientists and engineers- (ISOMAse)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36842/jomase.v70i2.635

Abstract

The optimization of maintenance remains still a challenge in food manufacturing since preventive maintenance is often scheduled at fixed intervals without considering the criticality of components and the real characteristics of failures. Failure Modes, Effects and Criticality Analysis (FMECA) and Reliability-Centered Maintenance (RCM) are two popular tools for planning maintenance. However, only a limited number of studies have combined the two methods to determine the reliability-based maintenance intervals of continuous frying machines based on real industrial failure data. This study propose is to integrate maintenance framework with combining the FMECA and RCM to identify critical components, select appropriate maintenance tasks and define maintenance intervals according to the components’ reliability. The framework was implemented on a continuous frying machine at PT. XYZ and found the wire mesh to be the most critical component. The suggested maintenance intervals were 35 days for the drum filter, 150 days for the circulation pump, 67 days for the pedal, and 14 days for the wire mesh. The Time-Directed Maintenance (TMD) task recommended a preventive replacement interval of 180 days for the circulation pump. The proposed framework provides a systematic approach of maintenance decision making in food manufacturing and demonstrates its practical effectiveness by improving the machine reliability from 1.6% to 13.3% and machine availability from 55.1% to 99.8%.
Co-Authors Ali Alhamidi Amanda Sofiana Ari Andriyas Puji Muhamad Fauzan Arridho Nur Fitriyah Mufarrihah