Preventive Maintenance Step #5: Collect Data for Informed Decisions

Working with Data: Reliability-Centered Maintenance (RCM)

Just as autonomous maintenance is the core pillar of most implementations of TPM, RCM is a central pillar of predictive maintenance. Its whole purpose is to collect data to make informed decisions.

RCM typically involves heavy statistics, but there are software packages to help you get the most out of it.

The 6 Steps of Autonomous Maintenance

To implement an autonomous maintenance system, you will need to follow these steps:

RCM: Data Analysis per Machine or Tool

Data needs to be collected and recorded for each individual piece of equipment.

Let’s say you have 3 similar machines, but they are not loaded the same way. The failure pattern of individual machines might look like this – where the crosses indicate a breakdown event:

When you consider each of the machines, you’ll see that merging the data together won’t make much sense because the patterns are so different. Each machine needs to be considered individually.

RCM: Data Analysis per Component Type

It often makes sense to order spare parts and do the replacement without waiting for a breakdown, however, can we assume that the risk of breakdown truly increases past a certain time, or a certain number of cycles?

Most components follow patterns like these:


If this applies to some of your equipment, is a “basic” preventive maintenance policy appropriate? Clearly not. Time in operation, number of cycles, or other time/age based measurements, do not help predict a breakdown.

What To Do If “Basic” Preventative Maintenance Is Not Sufficient?

If cleaning, lubrication, repairs and parts replacement are not solving your maintenance problems, implement the following three steps.

First, if you can add redundancies at a modest extra cost and weight so that one component’s failure does not cause the whole system to fail, do it at the design stage.

Second, if you can monitor the condition of your equipment in a way that alerts you with sufficient notice before a breakdown, go down that path. Monitoring equipment has gotten increasingly easy thanks to:

  • The inexpensive sensors that can be placed permanently
  • The availability of relatively cheap testing equipment that can be used regularly

Third, if you can record historical data for each piece of equipment, you will also be able to record its mean time to failure along with other useful statistics.

Condition Based Monitoring

The idea behind condition monitoring is getting an early warning so you can react to a deviation from a standard before it leads to a breakdown. Just as with data collection, not all your injection presses, or stamping machines, are in the same condition, even if you purchased them all together, so you will need to monitor them individually.

To monitor the condition of your equipment, maintenance technicians will need to often check machines for:

  • Vibration
  • Noise
  • Heat
  • Oil analysis

You also need to record and analyze the data of past breakdowns so that you can take action above a certain threshold. For example, for mechanical components such as bearings, the most common causes of failure are typically:

  • Poor lubrication
  • Excessive load
  • Contamination
  • Poor assembly or setup

You don’t need to have a full history of each breakdown; even if you only have past failure incidents data on 5 or 6 of these 20 machines, you can still rank them and run a Weibull analysis.

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How A Preventive Maintenance System Cuts Costs in Chinese Factories

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