The research focuses on main engine cooling systems in large-capacity machinery used in heavy manufacturing in Banten Province, Indonesia. These systems are essential for controlling engine temperature. When cooling fails, machines face higher wear, reduced efficiency, safety risks, and costly downtime. The study shows that human experience remains a critical safeguard, even as industries adopt advanced monitoring technologies.
Why Engine Cooling Systems Are a Growing Concern
Modern industrial engines are pushed to operate closer to their design limits than ever before. Manufacturing plants and energy facilities demand nonstop performance, while operating conditions often change rapidly due to fluctuating workloads and environmental factors. Cooling systems are designed to manage heat, but real-world conditions are rarely identical to textbook scenarios.
Globally, cooling system failures remain one of the most common causes of engine breakdowns in heavy industry. While engineers continue to improve thermal design and sensor technology, many failures still originate from conditions that automated systems do not immediately recognize. This gap between design assumptions and real operations places frontline operators at the center of machine reliability.
In Indonesia, where industrial growth continues alongside workforce modernization, understanding how operators interact with complex machines is especially relevant. The study highlights that machinery and humans form a socio-technical system, where performance depends on both technology and human judgment.
How the Research Was Conducted
The research team used a qualitative case study approach to capture real operational experience. Rather than relying on simulations or laboratory data, the researchers went directly into industrial settings.
Data were collected through:
· In-depth interviews with 12 informants, including six engine operators, three supervisors, and three maintenance technicians
· On-site observations of daily machine operations and cooling system management
This approach allowed the researchers to document how operators interpret machine behavior, respond to changing conditions, and make decisions that are not always written into standard operating procedures. The interview and observation data were analyzed using thematic analysis, a method that identifies recurring patterns in human experience.
Key Findings from the Field
The study identifies four major ways operator experience improves cooling system performance.
Early detection of thermal abnormalities Operators often notice subtle warning signs before alarms appear on monitoring panels. Changes in engine sound, vibration, or system response alert experienced operators to potential overheating. This informal detection frequently triggers early corrective action, reducing the risk of serious damage.
Adaptive adjustments beyond written procedures Standard operating procedures provide general guidance, but they cannot cover every real-world situation. Operators routinely adjust coolant flow or operating parameters based on engine load and environmental conditions. These experience-based adjustments help maintain temperature stability during rapid operational changes.
Prevention of repeated failures through experience-based learning Operators remember past breakdowns and recognize recurring patterns. This informal knowledge is shared among colleagues and used to prevent similar problems from happening again. Although rarely documented, this collective memory plays a major role in system reliability.
Bridging the gap between procedures and reality The study finds a clear gap between formal procedures and actual field conditions. In critical situations, operator judgment often determines whether an engine remains stable or moves toward failure. Experience complements procedures rather than replacing them.
Why These Findings Matter Beyond One Industry
The implications of this research extend well beyond heavy manufacturing in Banten. As industries worldwide adopt automation, there is a growing assumption that machines and sensors can fully manage operational risks. This study challenges that assumption.
For industry leaders, the findings suggest that reliability depends not only on equipment investment but also on valuing operator expertise. Training programs that focus on experiential learning can strengthen early detection and response capabilities.
For engineers and system designers, the results highlight the need for human-centered design. Cooling systems and interfaces should support how operators actually perceive and respond to machine behavior.
For policymakers and regulators, the research underscores the importance of integrating human factors into industrial safety standards. Overreliance on procedures without acknowledging field experience may leave critical gaps in risk management.
Insight from the Researchers
The authors emphasize that operator experience should be treated as a strategic asset. Drawing on field evidence, the research team from Politeknik Pelayaran Banten explains that experienced operators “function as an early warning system that complements technical monitoring and helps stabilize engine performance under real operational conditions.” This perspective reframes operators not as procedural followers, but as active contributors to system safety and efficiency.
Author Profile
· Pierre Marcello Lopulalan, MSc, is a lecturer at Politeknik Pelayaran Banten, Indonesia. His expertise includes mechanical systems, marine engineering, and operational optimization of large machinery.
· Hendi Prasetyo, MSc, is affiliated with Politeknik Pelayaran Banten and focuses on engine operations and maintenance management.
· Surnata, MSc, is a researcher at Politeknik Transportasi Sungai Danau dan Penyeberangan Palembang, specializing in transportation systems and applied engineering.
· Rahmat Santoso, MSc, is also based at Politeknik Pelayaran Banten, with expertise in industrial machinery operations and technical training.
Source
Article title: In-depth Analysis of Operator Experiences in Optimizing Main Engine Cooling Systems Based on On-site Operational Insights
Journal: Formosa Journal of Science and Technology
Publication year: 2026
DOI: https://doi.org/10.55927/fjst.v5i1.365
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