Narongrit Sritana | Dreamstime
Manufacturing robot maintenance.

How to Optimize Component Replacement Schedules

Nov. 2, 2022
The power and functionality of the cloud will maximize component service life, reduce maintenance cost, and increase equipment availability, for a competitive edge.

Fleet managers understand the role of component replacements in optimal capital allocation, equipment availability, and maintenance efficiency. Whether the fleet represents machinery, robotic equipment, vehicles, aircraft, or major industrial equipment, technology offers a range of tools for improving component replacement schedules.

Modern computerized maintenance management systems (CMMS) have a broad remit, managing so many aspects of equipment maintenance that it’s hard to focus on specifics. Yet, fleet managers have six standard functionalities within their CMMS that can accurately monitor, manage, and optimize their fleet component replacement schedules.

1. Component tracking

Components are central to achieving planned equipment lifecycle and operational costs, with repair and overhaul costs impacting operational performance. Component tracking not only refers to a geographical location but also to component performance, where components sit in their expected lifecycle, and their mean time to repair (MTTR). Such information is critical for informing repair and replacement decisions.

The payback from component tracking lies in identifying indirect costs like lost production, premature component replacement, late deliveries, increased energy consumption, and supplier performance. Such insights enable tactical decisions to drive efficiency and cost reduction in your business.

An example is a fleet experiencing widely variable failure rates of vacuum pumps. Using component tracking data, the fleet manager can prove that pumps overhauled by a vendor suffer early-life failure, causing equipment downtime and increased maintenance costs. That knowledge enables corrective action to improve pump reliability and contain indirect cost escalation.

2. Backlog management

Backlog management is an active failure-prevention strategy detecting component conditions, time-in-service, and equipment performance. Used by maintenance planners, it allows the development of a plan and a set of actions to avoid non-routine maintenance. Multiple inputs to backlog management systems include condition monitoring, notified defects, equipment performance, and operating frequencies in hours, cycles, or calendar times.

Fleet managers can support effective backlog management by demanding good communication between operations and maintenance personnel and encouraging the understanding that a failure to manage maintenance backlogs will drive poor reliability, increase costs, and reduce equipment availability.

A planner scheduling multiple component changes on a vehicle during a planned servicing is an example of backlog management. Some changes will be due to components nearing their overhaul date, others due to evidencing their reduced performance, and some thought to be contributing to an intermittent fault. The planner averts failure, delay, and possible safety concerns by proactively removing these components during scheduled downtime.

3. Planned component replacement

Mechanical and electrical components wear out, and when they do they fail to perform to specification or stop working. Yet, many operators ignore the inevitability of component failure, operating a de facto run-to-failure strategy by convincing themselves that they're extracting maximum value by keeping the equipment operational for longer. Yet, experts have shown that run-to-failure strategies cost three to ten times as much as planned maintenance programs.

Suppose you operate a fleet of robots using flexible grippers to hold and manipulate valuable products during manufacturing. In that case, wear in the gripper fingers must be identified before they start mishandling, dropping, and damaging the product. You can implement a planned component-replacement task triggered once gripper backlash exceeds a set tolerance. The grippers at that tolerance are still serviceable, but experience tells you that further deterioration will incur stoppages, breakage, and emergency maintenance costs. In addition, it's more cost-effective to make the change under controlled circumstances.

4. Mean time between failure (MTBF)

A fleet may have hundreds of components of the same make and model. The MTBF of those components refers to their average service life computed by the CMMS from in-service data. Knowing the MTBF of critical components allows fleet managers to make tactical decisions.

You can organize planned maintenance tasks to inspect the component for its condition and choose to replace it, send it for inspection and repair, or have it overhauled. MTBF allows comparisons of other manufacturers' component lives, the quality of a new overhaul vendor, or the longevity provided by using cheaper seals or lubricants. By acting before a component is statistically predicted to fail, MTBF gives fleet managers the levers to drive cost reductions, increase asset lives, and improve equipment availability through targeted maintenance interventions.

5. Condition monitoring

Condition monitoring is a generic term describing the monitoring of a particular attribute of a component to ensure it is operating within a defined performance threshold. The intent is to identify changes indicating a developing fault.

Modern technology enables fleet managers to continuously monitor critical components for various attributes like vibration, pressure, or temperature. Where continuous monitoring is impractical, intermittent condition monitoring may be used, particularly for monitoring oil for particulates, lubricity, or water ingress.

A cloud-based CMMS linked to machine-mounted sensors gives fleet managers real-time monitoring capability, with alerts raised if the attribute breaches predefined thresholds. An example is the pressure output of a hydraulic pump, where reduced pressure could indicate bypass or wear, reducing operating efficiency and foretelling imminent failure and equipment downtime.

6. Predictive maintenance

Predictive maintenance takes condition monitoring a step further. The collected sensor data is analyzed by predictive software trained to learn and identify patterns in the data and predict future outcomes. When the system determines component degradation, it raises an alert for engineering and maintenance personnel, allowing sufficient time for planning maintenance interventions that do not impact operations.

Fleet managers can use predictive maintenance on critical bearings by monitoring their vibration signature. The analytics engine within the CMMS can detect when changes in the signal occur, alert technicians, and advise the timeframe within which intervention should occur. This advanced warning allows spares, consumables, and technical resources to be prepared, with the maintenance planned before performance drops to an unacceptable level.

Fleet management encompasses a wide variety of equipment. While operators' needs differ, the power and functionality of modern cloud-based maintenance management systems enable fleet managers to optimize their component replacement schedules. The return on investment maximizes component lives, reduces maintenance costs, and increases equipment availability, providing businesses with a competitive edge.

Bryan Christiansen is the founder and CEO of Limble CMMS, a mobile CMMS software that helps managers organize, automate, and streamline maintenance operations.

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