A few months ago, I received training on ISO 9001 process auditing. It was very thorough and put on by a very enthusiastic man. I was really enjoying the training, and I planned to take my newfound knowledge and begin to process audit my division.
One of the last things the trainer said to me before we finished for the day was, “Remember, as a quality person, you are only to point out nonconformances and areas for improvement. You are not to personally get involved in fixing them.” That was music to my ears as I was one of the few engineers at my company. I figured this would lessen my workload now that I wouldn’t have to worry about process improvements or any other direct work on production.
As I headed back to my office, I encountered the division manager (my boss) in the supervisor’s office. He asked me how my training was going and then said, “By the way, go take a look at press 3. Its output has been lagging behind. We think it may be a mechanical problem.”
The trainer’s words still fresh in my mind, I boldly replied, “I’m sorry George, I can’t do that anymore. I can only recommend areas of improvement. I can’t be directly involved in production.” I was quite proud of my new direction as strictly a man of quality. Surely my boss could also see the conflict of interest for a quality man to also be a production man.
Unfortunately, he didn’t see things my way. He swiftly digested what I had just said and retorted something along the lines of, “You sure as hell arestill going to be involved in production!”
That was OK with me. I knew he would still want my expertise in production and I was just trying to get a rise out of him. Plus, I enjoy the improvements a business makes from enhancing production and developing a solid quality system. However, this got me thinking as to why we often see production and quality as two distinct animals. I’m sure it’s no surprise to any quality professional reading this article when I say that production and quality are interconnected. Improved quality will undoubtedly lead to better production results. This improved production from high-quality standards could come in the form of decreased down time, less scrap, better communication, or any number of areas. However, it has come to my attention more than once and in more than one company, that workers often see production and quality as mutually exclusive. You are either pumping out product or you are maintaining quality. It’s either one or the other, or so the conventional wisdom goes. Worse yet, sometimes a worker will let quality slide under the false assumption that it will improve production results.
While this thought was swimming around in my head, it came time for the monthly quality meeting with management. At this meeting, the plant general manager brought up a concern that he wanted better metrics as to how our division was performing in terms of production. Because this was during a quality meeting, I thought this was the perfect opportunity to combine my ideas on quality and production and develop a single useful metric to track our progress.
I was looking for a metric I could use that would combine quality and production while being easy to implement. After some research, I found a metric that seemed to be perfect. It was called overall equipment effectiveness (OEE). OEE was a single percentage that could be used to describe how a single work unit—in our case, a stamping press—was performing. OEE involved three parts: availability, performance, and quality. Availability is how much time a press is actually operating and producing parts, as opposed to setup times in which nothing is being produced. Performance is how many parts you produced vs. how many you should have theoretically produced given press speed and time. Finally, quality is a measure of quality parts produced over total parts produced, i.e., how much have you lost to scrap.
In a traditional OEE metric, you would simply multiply availability, performance, and quality together to get a percentage:
OEE = availability x performance x quality
However, we found that our company goals would be better represented by a weighted average. Hence, quality, our main priority, was given the most weight, while availability, which wasn’t a big problem for us, was give the least. Now our metric looked like this:
OEE = (availability x 0.1) + (performance x 0.4) + (quality x 0.5)
With this, we now had a metric that involved quality and production. It was also easy to implement in that the data needed was already being collected in our quality documents. All we had to do at this point was calculate a theoretical yield for performance, which was no problem.
This metric is now a staple of our management meetings and provides a useful tool for production and quality improvements. I can look to the OEE percentage to see which jobs are achieving the best results and which are achieving the worst. I then can do a type of root cause analysis and break down the data to see where a problem is coming from. For example, a low performance score could indicate a need for capital improvement. A low quality score could indicate a bad supply of raw material from a vendor.
The beauty of this metric is that you probably already collect most of the data needed to track OEE and it’s easy to explain to staff. Once you put it into use, you have hard data ammunition to back up any assertions you may want to make to management, which is always helpful. I hope this metric can help you with your continuous improvements as well.
Add new comment