<![CDATA[General Background Manufacturing continuity relies entirely on the structural integrity and operational readiness of critical machinery. Specific Background Sugar factories utilizing continuous operational models frequently face sudden mechanical breakdowns, resulting in severe production downtime and excessive emergency repair expenditures. Knowledge Gap Although unexpected mechanical failures severely disrupt production, many factories still lack a quantitatively determined, scheduled maintenance framework based on exact reliability metrics and historical failure intervals. Aims This study determines an optimal maintenance schedule for sugar processing machinery utilizing the Reliability-Centered Maintenance methodology. Results Analysis of 11 failure occurrences yielded a Mean Time to Repair of 0.5364 hours and a Mean Time Between Failure of 29.299 hours. The machinery's operational reliability dropped to 44.08 percent within a 24-hour cycle, despite maintaining a high availability rate of 98.20 percent. Stasiun Pemurnian and Stasiun Gilingan recorded the highest failure frequencies, primarily driven by bearing wear, continuous overloading, severe overheating, and oil contamination. Novelty This research directly translates specific component failure metrics and 24-hour cycle reliability limits into a highly structured, data-driven preventative maintenance timeline for sugar processing operations. Implications Executing a mandated preventative maintenance protocol every two days ensures components are serviced before reaching critical failure limits, substantially minimizing unplanned downtime and securing operational efficiency. Highlights: Unplanned mechanical breakdowns significantly disrupt continuous sugar processing operations, requiring structured maintenance interventions based on exact reliability metrics. Machinery analysis revealed a 29.299-hour Mean Time Between Failure and a 44.08 percent operational reliability limit during a standard 24-hour cycle. Mandating a strict preventative maintenance schedule every two days mitigates unexpected downtime and successfully addresses critical overheating and bearing failures. Keywords: Reliability Centered Maintenance, Mean Time Between Failure, Preventive Scheduling, Equipment Reliability, Operational Availability]]>
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