Maintenance strategies are critical for both the efficiency and longevity of forklifts. Today traditional forklift maintenance methods are increasingly being supplemented and gradually overtaken by newer, data-driven approaches. Understanding this evolution is essential for optimizing forklift performance and reducing downtime. This article will explore each approach to highlight their respective advantages and challenges within the context of forklift fleet management.
Reactive maintenance
Reactive maintenance, sometimes (and not always appropriately) known as corrective maintenance, waits for a forklift to break down due to a functional failure before maintenance is done.
- This form of maintenance does not rely on data, other than the actual fact of failure.
- Advantages: Reactive maintenance presents no upfront costs and needs only a minimal maintenance staff.
- Shortcomings: Fixing a broken down vehicle generally comes at a high(er) cost, often accompanied by unplanned downtime. Repairs and compensating for downtime may require overtime.
Today reactive maintenance is progressively becoming an outdated approach. Its apparent inevitability being gradually and surely overcome by newer strategies.
Preventive maintenance
Also called preventative maintenance, this strategy generally revolves around a fixed maintenance schedule, ideally calculated to occur before failure or breakdown of a forklift (or a specific part).
- Data-wise preventative maintenance relies mainly on experience, usage, and/or time to calculate the maintenance routine.
- Advantages: Preventive maintenance is straightforward to schedule and fit into general operations. On the whole, it’s less costly to replace a single part, even multiple times, than repairing a machine after this component breaks down. When compared to reactive maintenance, preventive maintenance causes less unexpected downtime and increases the forklift’s life span.
- Shortcomings: When the scheduled maintenance frequency is too low, failures will occur. When it’s too high, components with more life in them get ‘fixed’ or replaced, which is wasteful. Also: preventive maintenance does not anticipate singular or uncommon failures.
Preventive (preventative) maintenance has been established as the prevalent method in many industrial systems, including internal vehicle fleets and material handling equipment. It has proven a clear and decisive step forward. However, it seems to be far from the final step. Since new strategies, often led by data-related technologies, are currently rapidly gaining ground. And rightly so.
Predictive maintenance
Predictive maintenance leverages sensors and data to identify trends in forklift status, predicting potential breakdowns or component failures before they occur. This early detection capability enables maintenance teams to schedule repairs proactively, providing ample time to address issues at a convenient moment.
- Predictive maintenance typically analyzes a select few datasets, employing analytics to detect trends in both the data and make an informed decision on the asset's health.
- Advantages: Predictive maintenance offers a real-time indication of the shape of a forklift and/or some of its crucial components are in. This allows for timely and non-wasteful maintenance, comfortable planning, and an increased life span.
- Drawbacks: Gathering and analyzing the data upon which this maintenance strategy bases its predictions, requires hardware and software that represent an investment and possibly extra operator training.
Currently, companies running a forklift fleet with a robust preventive maintenance program in place should seriously consider shifting towards predictive maintenance. A growing number is making the transition and those who have already are reaping the rewards.
Prescriptive maintenance
Prescriptive maintenance builds upon and refines predictive maintenance. It employs sensors, data analytics, and machine learning algorithms to predict potential equipment failures and prescribe specific actions to prevent those failures from occurring. It provides actionable insights into the root causes of potential issues and recommends proactive measures to address them.
- Prescriptive maintenance employs a multitude of datasets, metrics, and likely some proprietary analysis techniques to determine the underlying cause of a potential equipment failure.
- Advantages: An advanced optimization of time and resources through proactive problem-solving. By identifying and addressing the root causes of potential features, equipment reliability, vehicle life span, and overall operational efficiency increase, while unexpected downtime and needless costs decrease.
- Drawbacks: Similar to predictive maintenance, prescriptive maintenance requires an initial investment in hardware and software. Some extra training for the driver/operator may be needed.
Seen as the next and potentially final step in maintenance strategies. Prescriptive maintenance in its ideal form, avoids waste of resources and all but nullifies unexpected failures. Presently prescriptive maintenance is still in its
Conclusion
Mitigating the substantially more costly need for reactive and corrective maintenance through preventive maintenance has long been a significant step forward. The current shift towards predictive maintenance is expected to turn out just as consequential. Not in the least because it lays the foundation for the next and possibly final step: prescriptive maintenance. An even more refined methodology, working from an ever more complete set of data, that won’t merely tell you when a forklift will fail, but what specific part needs replacing, and just as important: it may suggest strategies to make it last longer.
Sources:
- Materialhandling 247 on predictive maintenance
- Endaq on different approaches to maintenance