How to demonstrate the benefits of industrial predictive maintenance to senior management

Proving the benefits of industrial predictive maintenance can have astronomical positive effects. Plant and maintenance managers can sometimes feel pressured to defend the merits of predictive maintenance. predictive maintenance techniques. A predictive maintenance programme requires the use of technologies that help industrial personnel make better decisions; and these technologies cost money.

Predictive maintenance technologies are numerous, but what is the best? In other words, what is the most cost-effective combination? It is best to apply the RCM concept to determine which maintenance strategy should be the most appropriate for each failure mode.

Anyone involved knows the percentage of bearing-related failures: misalignment, poor installation, insulation and the like; they also know that some tests are better at identifying certain problems early; the trick is to mix those technologies appropriately.

This is where most programmes get off on the wrong foot. Does a programme start with the development of a wish list, and then either allocate the necessary funds or optimise the budget that has already been granted? In most cases, it is the latter, because the programme is not funded as desired. In this case, linear programming is the best technique to use to optimise the implementation of team hosting technologies.

Select the combination of predictive maintenance technologies The least costly is usually not the best approach towards the highest possible return on investment; regardless of cost, it is the application of technologies that affects the bottom line.

The goal is to detect specific failure modes as early as possible so that repairs can be planned, scheduled and corrected, early in the failure curve. This technology selection strategy results in the most cost-effective corrective action and therefore the best proven return on technology investment.

To optimise the cost of the total programme across the plant, an individual technology may be cost-effective for some machines, but when looking at the entire operation, this can be very costly. Of course, some are more effective if outsourced, especially if they need extensive training or field experience to maintain skills.

Once you have a management in which the technologies are optimal for the plant, the next question that most people confront is: How rigorous and intense should the maintenance programme be for the plant's industrial assets?

Studies have shown that the most cost-effective maintenance programmes include a combination of precision and predictive maintenance practices, preventive maintenance and run-to-failure maintenance strategies. That said, where failure-mode based strategies overlap, predictive maintenance and condition monitoring technology should be preferred over other applications. Predictive maintenance technologies should be developed and applied based on the criticality of industrial assets, with the application of increasing levels of coverage, as well as management systems and maturity levels evolving.

Another key to establishing the intensity of an application lies in historical records. The source of information is usually in the form of CMMS work orders, reflected in the maintenance history of the equipment. The work orders show the actual life requirements during equipment failures.

It is useful to compare corrective maintenance with preventive maintenance; taking measurements can also be used as predictive maintenance. If this data can be retrieved automatically, more data points from the industrial asset are available, and possible human errors during data entry are eliminated, providing a better, more accurate and timely analysis.

If intensity refers to frequency, then equipment criticality, shaft speed, general repair costs and production loss all influence monitoring intensity. However, intensity can often mean more than frequency. This can also relate to the types of monitoring carried out. Is oil sampling appropriate? How about an electrical resistance test rather than a full electrical analysis? Is vibration monitored at each bearing or throughout the equipment?

Benefits of predictive maintenance with real numbers

In order to gain credibility in a predictive maintenance programme At the management level, it is necessary to quantify the money saved by avoiding a shutdown. It is about cost avoidance, which is the total of, parts, labour and downtime costs of the industrial asset. Downtime should be viewed as parts and resources available or unavailable.

Similarly, quoting full savings for every bearing identified is dishonest. People identify worn bearings by sound, temperature and overloads long before anyone thinks to do a spectral analysis. If you lose sight of this fact or your numbers, you can lose credibility.

Whenever a problem is found, publicise it and also say what would have happened if it had not been found. You want to build a subconscious belief in the effectiveness of predictive maintenance, so, at least for the most important findings, it is recommended to make a repair order estimating that the failure would have occurred, but not to exaggerate with domino effect or secondary failures, and then compare it with the costs of the predictive maintenance programme.

It is recommended to have contact with someone in the treasury or cost control team. When these cost-benefit studies reach the plant managers or above, it is advisable for the controller to say: “Those are good numbers; my staff helped to compile them”. Another thing; it is advisable to reach agreements with the priority of avoiding losses due to unavailability. Direct costs are not so controversial, but production and sales costs can be.

How to quantify the benefits of industrial predictive maintenance?

The question “How to quantify the benefits of industrial predictive maintenance” is a question often left unanswered. The obvious answer is a cost avoidance figure, an arbitrary or subjectively assigned number for an event, illustrating a “what if” scenario, based on an identified defect, maintenance costs and production losses. The problem with this approach is that when the cost avoidance figure is presented to justify programmes or request additional funds, even if the estimates are quite accurate, the typical response is that the avoided costs are a fictitious calculation.

For example, it can track downtime, maintenance costs as a percentage of replacement value of an industrial asset, overtime costs, spare parts, predictive and preventive maintenance compliance, and measure implementation time for all conditions.

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