Regardless of whether you have production units that are reliable or unreliable, I would like to propose a different type of performance indicator for manufacturing leaders to consider from the standpoint of an “investment.”
For this blog, I want to challenge you to think of a planned outage or scheduled maintenance, as if it was a baseball card to be traded. I will trade you my twelve hours of production time for twelve hours of scheduled downtime to maintenance on our assets. How do you know you go a good deal?
There are many classic definitions and performance indicators measuring reliability within Overall Equipment Effectiveness (OEE) or industry benchmarks on unplanned delay rates. These are strong lagging indicators of a department's asset management perspective and can unlock plenty of innovative ideas when benchmarked to like assets. But what these performance indicators sometimes lack is quantifying the value of the exchange of production time with planned downtime.
To measure this return, organizations can consider measuring the effectiveness of this replacement of production time with scheduled downtime with two indicators. The first is the production unit’s Defected Quality Run Rate. It is measured by evaluating the amount of defected product measured within the OEE calculation, divided by the production run time. This value shows the run rate of producing defective material per unit of time.
Quality Defect Run Rate = Defected product / (Calendar Time - Delays)
Equation 1 - Quality Defect Run Rate
The second measurement is to look at the demonstrated capacity of the operating unit considering its reliability and product mix. This is measured by the amount of production minus the quality defects, divided by the calendar time minus delays outside of the control of the production unit. The Society of Maintenance Reliability Professionals would define this in Metric 2.4 as Idle Time or the amount of time an asset is idle or waiting to run. This measurement would indicate the demonstrated capacity based upon the unit’s reliability, quality, and product mix.
Demonstrated Capacity = (Production - Defected product) / (Calendar Time - ΣDelays + Idle Downtime)
Equation 2 - Demonstrated Capacity
Let’s think about these two equations as if we are trading baseball cards, one-for-one. It is obvious to any manufacturer that we should strive to improve our Quality Defect Run Rate. Its also obvious to any manufacturer that we should strive to increase the Demonstrated Capacity over time. But when we look at these two calculations in conjunction with the amount of scheduled downtime, we can see the effectiveness of scheduled downtime over time as an investment. We should want to see a Quality Defect Run Rate decrease as we trade our Nolan Ryan production time for Derek Jeter scheduled downtime. We should want to see the Demonstrated Capacity increase as we trade with scheduled downtime. All production units should want to produce prime production reliably when producing in return for the hours devoted to scheduled downtime.
Typically, within a chart to show these performances over time, the two separate visuals for these key performance indicators are a line chart, measured along the Y1 axis along with scheduled downtime as a bar chart on the Y2 axis. The visual enables a view as an investment of scheduled downtime that is creating the results of optimizing the effectiveness of the production hours.
When you first chart the returns on investment, if we see the Quality Defect Run Rate increasing with no changes in the amount of scheduled downtime, the departmental leadership should challenge the scheduled downtime to drive quality improvements. Are we changing equipment, at the necessary preset intervals, that touch the product? Are our metering preventive maintenance actions not reflective of the current product mix? Are we doing the optimal amount of cleaning so that debris doesn’t compromise the final product?
Within the Demonstrated Capacity view, we should challenge the work that is planned and executed as being prioritized properly to improve the reliability of the asset. Challenging the team to reflect on if we are doing the right work to improve the reliability of the production unit? Do we have the right resources to realize the reliability desired? Are our work identification processes effectively finding issues leading up to an outage?
Production units can unlock new value when looking at scheduled downtime as an investment versus a necessary evil. They can rally around exchanging the production time for improvements in the predictability of the product and reliability of the asset. They can collectively make evaluate if the trades are working in their favor or not.
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