A Standard Operating Procedure (SOP) has the wonderful capacity of controlling the quality of work outcomes
With an SOP you can control the distribution of task quality to repeatedly get known results and guaranteed job quality
Slide 14 – A Standard Operating Procedure Removes Randomness in Quality of Work and Markedly Tightens the Work Quality Outcome Distribution Curve
In Plant Wellness Way EAM we control the distribution of quality of work outcomes with a standard operating procedure. We show the effect of an SOP on the distribution of work task quality by getting course Participants to use the job instructions in the slide above.
We explain to the Participants how to follow the job instructions and emphasize the paperclip must be be broken only in this way. The Presenter explains where to position the clip on the corner of a table and how to cycle the paperclip from a zero position to 180° opposite position until it fails. The cycles to failure are then plotted to develop the failure density distribution curve for this standard operating procedure. One such curve is shown in the image below. You will immediately notice the failure density distribution curve is greatly tightened compared to the failure density distribution curve on the previous slide.
Slide 14A – Failure Density Distribution Curve Tightens Drastically by Following the Standard Operating Procedure on How to Break Paperclips
By using the specified instructions in the SOP, the shape of the failure density distribution curve is controlled. The curve is narrowed, with most of the points stacked in a small spread of cycles to failure. The wide distribution in the failure probability density function seen in the prior slide of Activity 1 has become a much narrower distribution curve. The standard operating procedure removed the randomness caused by the various procedures Participants had invented. Using a standard operating procedure controlled the outcomes of 26 people to within a tight performance range.
The new distribution curve also contains useful intelligence. You can see that 24 of the points fall between 11 and 18 cycles to failure, with two outliers, one at seven cycles to failure, and one at 23 cycles to failure. The outliers are abnormal outcomes that do not fit the distribution curve results expected from the SOP. The outlier at seven cycles to failure tells us the person doing the procedure did not follow it correctly. Had they done the SOP right they would have got a point between 11 and 18 cycles to failure. It is necessary to address that person’s practices. You retrain them in the procedure several times and get them to do a few trial runs to prove their new results fall within the required distribution.
The most distant outlier, at 23 cycles to failure, is tremendously valuable information. Though the Participant also did not follow the procedure, their approach got far greater reliability than all the other outcomes. It is 7 to 8 cycles to failure longer than the average paperclip service life. If the aim of the SOP was to both control the quality of work outcome and to create a standard operating procedure that delivered greatest reliability, then the person who got the most distant outlier achieved the requirements better than all the rest. It is now necessary to go interview and watch the person who got the furthest outlier to learn how they reached such high reliability. What they did differently to the rest of the group to get longer service life is put into a revised SOP. The new Standard Operating Procedure becomes the company-wide specification. Everyone is then trained and tested in the right way to do the improved SOP. This SOP and training will now ensure every user gets higher reliability to within a known range of results.
This slide is a companion to the new Industrial and Manufacturing Wellness book. The book has extensive information, all the necessary templates, and useful examples of how to design and build your own Plant Wellness Way enterprise asset life cycle management system-of-reliability. Get the book from its publisher, Industrial Press, and Amazon Books.
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