As an example of not having control over the outcome of a performance measure we can consider the reliability indicator measure of ‗Mean Time Between Failure‘ from Figure 3. MTBF is affected by original equipment manufacturing quality, by capital project design selection, by the quality and accuracy of initial installation, by the severity of operating duty, by the quality of operator practices, by the maintenance activities performed or not performed when due, by the quality of parts storage and by maintenance workmanship. A KPI that shows MTBF is not greatly under Maintenance control because of the extent of life cycle influences that Maintenance has no way of affecting. For a company to greatly improve the MTBF of its equipment the whole life-cycle needs to be addressed and not only its maintenance performance. If Maintenance is charged with improving MTBF you would have to develop a company-wide training scheme to teach people at each phase of the life cycle what to do to improve reliability, and follow that with a business-wide project to change business processes to those that produce higher reliability. (That is what DuPont did.)
Many companies only measure maintenance performance with historic indicators. A maintenance performance KPI that appears in a monthly report delivered mid-month is already six weeks out of date for the first week. Historic information is interesting, but as shown in Figure 4, feedback control means a lot of time passes before effects are observed and you can act in response. Useful and relevant maintenance performance indicators are those that drive the actions and behaviours needed to meet the goals you set at the lowest level in Figure 2, the Objectives Cascade. If we can do the cause of high reliability well it automatically follows that we will get a good operating effect that feeds into the corporate goals.
The measures listed in Figure 3 are historic outcomes and indicate the effects of past actions taken. In terms of Figure 1 they are site-level performance measures. They are fine for checking a site‘s overall maintenance performance but they are struck too high up the Objectives Pyramid to tell you if you are doing the right maintenance rightly until a lot of time passes and the effects confirm or condemn the actions taken. You also need KPIs set below the site measure level to confirm the right causes are being done to produce equipment reliability and operating risk reduction.
As an example of not having control over the outcome of a performance measure we can consider the reliability indicator measure of ‗Mean Time Between Failure‘ from Figure 3. MTBF is affected by original equipment manufacturing quality, by capital project design selection, by the quality and accuracy of initial installation, by the severity of operating duty, by the quality of operator practices, by the maintenance activities performed or not performed when due, by the quality of parts storage and by maintenance workmanship. A KPI that shows MTBF is not greatly under Maintenance control because of the extent of life cycle influences that Maintenance has no way of affecting. For a company to greatly improve the MTBF of its equipment the whole life-cycle needs to be addressed and not only its maintenance performance. If Maintenance is charged with improving MTBF you would have to develop a company-wide training scheme to teach people at each phase of the life cycle what to do to improve reliability, and follow that with a business-wide project to change business processes to those that produce higher reliability. (That is what DuPont did.)
Many companies only measure maintenance performance with historic indicators. A maintenance performance KPI that appears in a monthly report delivered mid-month is already six weeks out of date for the first week. Historic information is interesting, but as shown in Figure 4, feedback control means a lot of time passes before effects are observed and you can act in response. Useful and relevant maintenance performance indicators are those that drive the actions and behaviours needed to meet the goals you set at the lowest level in Figure 2, the Objectives Cascade. If we can do the cause of high reliability well it automatically follows that we will get a good operating effect that feeds into the corporate goals.
The measures listed in Figure 3 are historic outcomes and indicate the effects of past actions taken. In terms of Figure 1 they are site-level performance measures. They are fine for checking a site‘s overall maintenance performance but they are struck too high up the Objectives Pyramid to tell you if you are doing the right maintenance rightly until a lot of time passes and the effects confirm or condemn the actions taken. You also need KPIs set below the site measure level to confirm the right causes are being done to produce equipment reliability and operating risk reduction.
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