Do you trust your production reports?
We often meet the following situation. An operator completes a paper production report at the end of his shift. In theory, he should do this on a regular basis, but (rightly so!) production is more important. He notes how many parts he has produced, how many defects have occurred that led to reworks and scrap. This is the easy part. Troubles begin when he needs to compare the target with the current state. So: he was supposed to produce 250 units but he produced 190. What happened with the time needed for 60 units? A quick calculation: that was two hours… 15 minutes to start production and 15 minutes to finish a shift, a changeover planned for 30 minutes was prolonged by 30 minutes. That leaves half an hour, which lands under the all-accepting category called “micro stops”. Phew. Done.
The question is: should we then blame the operator for the quality of the production reports? Definitely not! It is not his fault that he doesn’t have the tools to report production effectively and quickly. Do a simple exercise and try to reconstruct minute by minute at the end of the working day. What have you been doing for 8 hours? Do it without looking at your calendar or to-do list?
The main task of the operator is to produce good quality items in the right time. All other activities should be simplified, automated, and minimized. Making decisions based on uncertain production data is like relying on luck. We might hit the root causes, but is that the best way to improve OEE?
Implementing MES is a way to create new standards
In theory, the calculation of OEE seems simple: performance x quality x availability. We have seen the most varied interpretation of these coefficients. The implementation of MES is a great opportunity to revise KPIs and coefficients that tell about the production health. We will eliminate the issue when several factories in the group calculate OEE a little differently, but the results are compared based on one indicator.
Is there then a single, universal way to calculate OEE for every industry and factory? Unfortunately not… The definitions of coefficients themselves are different, depending on the type of production. For example, in automated manufacturing, a micro stop can be any stop shorter than 30 seconds, semi-automated – 5 minutes.
Here should come an experienced partner that will help to standardize KPIs. At ANT we made more than 600 implementations for various industries. Our task during MES implementation is to propose best practices for your factory in terms of OEE calculation. It is worth proposing such a standard for the whole group in order to compare results as “apples to apples”.
Automated data acquisition will revolutionize your production reports
Availability is the time that we spent on production to the time planned for production. One of the biggest benefits of MES implementation is the automation of data acquisition. All states are customized to plant dictionaries and codes. Then, machines can send notifications about downtime automatically or, in the simplest way, system storage for a productive and nonproductive time. In the second case, the operator may be asked to put the reason for stoppages. Whether it does or not won’t affect OEE, but it will allow for more accurate identification of the root causes of drops in availability.