Predictive Maintenance: Boost Production Efficiency & Reduce Downtime

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In 1927, Thomas Parnell began the pitch‑drop experiment to measure the viscosity of a tar‑like substance. The apparatus has produced only eight drops in over 90 years, a fact that illustrates how rarely critical events can be observed—yet they have enormous implications for production reliability.

Just like the pitch‑drop test, many factories overlook maintenance until a failure forces a costly shutdown. This article shows plant managers how to budget for proactive maintenance and unlock peak efficiency across all processes.

From Paper to Digital Records

The food and beverage sector is renowned for adopting cutting‑edge technology, yet maintenance records often remain on paper. Regulatory pressure once justified paper workflows, but modern digital tools now offer far greater value.

Paper systems lock organizations into legacy habits, obscuring the substantial cost savings, efficiency gains, and competitive edge that electronic records deliver. By embracing digital maintenance platforms, managers give engineers a familiar interface that links the entire workforce, speeding decision‑making and boosting productivity.

Human error is the largest cost of manual maintenance. Mistakes in record‑keeping create redundant actions, rework, and audit headaches. Digital records eliminate printing, reviewing, and retrieval overhead, while enabling real‑time data capture directly on the shop floor.

Equipped with handheld devices, maintenance staff can log observations instantly, freeing time for actual repair work. A digital history of each machine also supplies engineers with actionable data for the next scheduled intervention.

Preventive Maintenance: Reducing Unplanned Outages

Unplanned outages strike when they hurt most—during peak seasons or large‑batch runs—leading to product waste, lost production, cancelled orders, and even lost contracts.

By anticipating potential failures, plant managers can schedule downtime during low‑volume periods, minimizing disruption. For example, if a motor typically fails once a year, that maintenance can be slotted into a slow season, preserving throughput.

Overall Equipment Effectiveness (OEE) measures three pillars: availability, performance, and quality. Availability drops with equipment failures and setup time; performance suffers from idling and speed reductions; quality falls when defects and startup losses rise. Preventive maintenance directly improves each pillar, driving OEE upward.

Just as the pitch‑drop experiment has become a digital livestream, so too can maintenance data be monitored online, allowing managers to predict and preempt failures, saving time and money while keeping production on schedule.

About the Author

Gernut van Laak is the group automation solutions leader of ABB’s food and beverage program, a global technology leader in electrification products, robotics, motion control, and industrial automation.