What Is Process Stability?
Everything varies. Your vendors provide components with a range of values. Your production process varies, too. Creating, monitoring, and maintaining process stability enhances your product reliability performance.
When I started my professional life as a manufacturing engineer, a senior engineer told me that we take a product design and can only make it worse. He said that, if we could make every unit exactly according to the nominal values of the drawing, every unit would work well.
This made sense to me as I’d been analyzing data gathered from every unit produced. We had just installed a new measurement tool to an early stage of the production process. The tool measured resistivity of the core of the product (a heating cable). The target for the product was 500 ohms. There was no flat line of readings at 500 ohms. The reading bounced from 423 ohms to close to 600 ohms. Sure, the bulk of the readings were just above 500 ohms, yet a quick scan of thousands of reading did not find any exactly at 500 ohms.
The Trick to Process Stability
The impact of variability often eludes many. You have to measure something that actually relates to the final product’s performance. It is possible to measure many elements of a product in production, but not all of them are important.
Start with the FMEA or a discussion with the design engineers. What are the critical elements of the design? What has to be right on the specifications to best ensure that the final product will work?
Sometimes you have to measure a surrogate or something that relates or predicts the final performance. When you find and start measuring an element of the product that is the source of the final product variability, you’re about to learn something: that not all products are the same. They should be, but they are not.
PDCA: Plan, Do, Check, Act
- Edwards Deming and others have long advocated process improvement based on data. So, given your measurements, you have data. Now you need information.
A common approach is to prepare an experiment or adjustment concerning the process or materials. In essence, this can be as simple as changing something, such as the polymer blend drying time from 30 minutes to 45 minutes. You do not just run down to your production floor and start changing things to see what happens. That is a recipe for chaos. Instead, think about what should occur and why. Create an experimental plan. Prepare to collect sufficient data to allow your experiment to create clear results. The sample size or run time is part of the experimental planning and using the appropriate statistical tools.
Run the experiment and collect the data. Do the analysis.
Check the results. Often this is accomplished with another run of the experiment or a pilot run of production. Double check. Did the reduction in variability occur, or did the shift of the mean occur, or both?
Act. Implement the changes and monitor. At this point, you may identify other experiments you need to run as you notice other opportunities for improvements.
Statistical Process Control and Capability Analysis
The measurement step is critical. Once a meaningful measurement system is in place and the product is meeting specifications (mostly), you need better tools than a series of experiments and adjustments. Statistical process control (SPC) tools allow you to efficiently monitor the variability of a process. SPC alerts you to changes (good or bad) soon after they occur. If the process is stable, SPC will provide the evidence (the data) that the process is stable.
Once stable, it’s time to conduct a capability analysis. This tool provides design and manufacturing engineers the information they need to create new products that the current process has the ability to actually produce well.
Summary
PDCA, SPC, and capability analysis are common tools that can assist you in creating products that perform as expected. No two individual products from your assembly line are the same. Differences are ok within reason when it comes to product performance. Measure, adjust, improve, and monitor your processes. Understand and correct causes of unwanted variability. Keep your process under control and your customers happy.
Bio:
Fred Schenkelberg is an experienced reliability engineering and management consultant with his firm FMS Reliability. His passion is working with teams to create cost-effective reliability programs that solve problems, create durable and reliable products, increase customer satisfaction, and reduce warranty costs. If you enjoyed this articles consider subscribing to the ongoing series at Accendo Reliability.