Mechanical Process Control and Statistical Process Control for Reducing Butter-Oil Defects in Industrial Production

This study provides a quantitative assessment of the reliability and availability of a serial butter-oil manufacturing line from a mechanical engineering perspective. The line comprises critical rotating and fluid-handling subsystems raw-milk receiving pumps, cream separators, heat exchangers, mechanical agitators, homogenizers, gearboxes, and conveying components whose mechanical integrity profoundly impacts throughput and quality. We characterize the production train using continuous-time Markov chains (CTMCs) based on a reliability block diagram (RBD) that depicts series dependencies and maintenance plans. Component-level failure (λ) and repair (μ) rates, derived from realistic duty cycles and mechanical failure modes (bearing wear, seal leakage, misalignment, lubrication starvation, cavitation, fouling, and thermomechanical fatigue), are conveyed to system-level metrics via state-transition analysis. Numerical simulations yield mean time between failures (MTBF), mean time to repair (MTTR), and steady-state availability for the entire system and for mechanically essential subsystems (pump-valve assemblies and homogenization units). Sensitivity analyses identify availability limitations and priorities mechanical factors bearing L10 lifespan, seal mean time between failures, lubricant replacement interval, alignment tolerance, and cooling-water temperature differential according to their impact on throughput decrease. The results suggest that minor improvements in repair logistics for high-criticality assets (such as the use of cartridge seals and quick-release couplings on feed pumps) might exceed substantial reductions in MTBF for low-criticality components. We demonstrate that the integration of mechanical condition monitoring (vibration and temperature trending) with SPC-based run charts and control limits stabilizes essential mechanical variables (overall vibration, RMS acceleration, and discharge pressure ripple), thereby reducing special-cause variation and unanticipated downtime. The study concludes with maintenance strategies for mechanical assets, encompassing spares pooling for prevalent failure categories, precision alignment, optimized lubrication practices, and threshold-based, condition-directed overhauls, yielding measurable improvements in line availability and energy efficiency while upholding butter-oil quality standards.