MES 101 Quality Management
Welcome to our MES 101 series where we will cover the basics of a variety of MES components. You will get an overview of what is available in an MES implementation, how to leverage each piece in your process, and how you will get an ROI for your efforts. In the previous installments of this series, we covered Downtime Tracking and Performance Management. This post will wrap up the components of OEE with Quality. The Quality component of OEE is the ratio of the good parts produced to the total parts started. Parts can be defined as actual units of a discrete part or pounds through a process depending on how you measure your production counts.
Figure 1: Quality Calculation
Quality Measuring Sticks
The Quality calculation requires two pieces of data. First, we need to know how many parts we started to produce. For discrete manufacturing processes where you are making an object, this is usually accomplished with a photo-eye on a conveyor line. As raw materials pass by the photo-eye, a counter is incremented, and the value at the end of the shift is your parts started. If you are pulling raw material out of a warehouse or using pounds of raw material, this data may come from operators or an ERP system. One OEE system we implemented for a chocolate manufacturer used the scales on their raw material mixers to generate the pounds started.
The next piece of data is the number of good parts produced. Good parts are everything that was started, minus the quantity of parts not meeting quality specs. The complicating factor here is usually where this data is generated in the first place. Many companies implementing OEE for the first time are using an Excel spreadsheet to track quality information. We're not saying you need to implement a full-blown LIMS system, but at the least, you do need a way to capture the number of scrap and rework parts to calculate a useful quality value. For this post, let's assume we can get this value into your database.1
Breaking It Down
There are a few common quality contributors at the top of the list: startup rejects, raw material issues, equipment failure, and operator error. Startup rejects assume there will be some loss while your process is getting to a steady state after starting a new production run. Raw material and equipment failures are more obvious, and operator error can arise from any number of causes. Understanding how each issue—and any other contributors—affect quality, and how to reduce them are the first places where most companies will realize value.
Diving Deeper
After you have basic quality information acquisition in place, you can start to move into the wonderful world of Statistical Process Control. This will also open up the doors to practices like Six Sigma, some parts of Lean Manufacturing, and beyond. Those are separate series in and of themselves. Given the scope of what surrounds quality, this is going to be a relatively short post.
The basics of Quality are simple:
Track what comes into your process.
Track what goes out of your process.
Reduce the difference between the two by improving the quality factor of your process.
Improving quality saves time, money, energy, and operator efforts on out of spec. goods you can’t sell. Everything together saves spending in every part of the process.
Next Steps
Next in this series, we will dive into moving the flow of information into a new ERP system instead of using Excel and printouts. This will alow you to begin to realize the full capability and power of Manufacturing Execution Systems. Ready to get started now? Email us: Info@CorsoSystems.com
Notes
If for some reason this data isn't available your quality will be 100% and you can address this in Phase 2. Unless fixing Quality issues is your #1 productivity increase, this should be sufficient for now.
Updated - 6/14/2022