What does statistical process control really do?
Some sophisticated math can help you make your manufacturing more consistent and identify production problems sooner.
You’ve heard of SPC. Statistical process control applies statistical methods to control manufacturing processes. You can go look at all the equations yourself, and you’ll see it’s actually pretty cool math and a practical application of mathematics in manufacturing.
But, what does it really do? SPC is like a lot of things, people have heard about it but few do anything with it. And, when someone actually does something with SPC it’s often a math or quality geek who’s doing something no one else in the plant understands. So, if that’s your take on SPC you’re not alone. I’m not going to be able to explain all of SPC in just a blog post or two, but I would like to talk about what SPC can do in the real world. That is, I’d like to talk about the actual real-world benefits of SPC.
First and foremost, SPC, particularly real-time SPC, can help you avoid failures. There’s lot of math behind this, none of which I’m going to go into, thankfully, but the idea is simple: the analytical capabilities built into SPC can indicate when a process is about to go out of control. And, if you know it’s about to go out of control, you can do something about it before it goes out of control. That helps you significantly reduce quality issues and helps you reduce downgrades and rework all by allowing you to identify problems before they’re problems, and then eliminate, or at least minimize, the failures.
Secondly, SPC helps you improve product consistency because it helps you look at the process at lot more closely so you can start ferreting out the causes of product variability. Maybe you’ll find processes that you thought were very stable aren’t as stable as you thought. SPC lets you determine the degree to which they’re stable or unstable, and then take actions to improve the process. And, SPC gives you the information to figure out if the steps you’re taking actually work. All that helps you improve product consistency and reduce product variability all by helping you reduce variability in your manufacturing processes.
And, last but not least, SPC, particularly historical SPC, helps you with your continuous improvement initiatives. Like most people, you probably have some type of continuous improvement program underway, like six sigma, lean manufacturing, or whatever. SPC helps you analyze where you need improvements and what types of improvements you need to make. As you make those improvements, SPC helps you verify that the improvements are working and things are actually getting better just as you hoped. There’s a lot to this piece as SPC can help in a wide variety of ways in all aspects of a continuous improvement program.
So, forget all the cool math, just trust that it all works. Concentrate instead on the real-world business benefits. SPC helps you avoid failures. Fewer failures reduce quality issues and rework. SPC helps reduce process variability which reduces product variability and improves product consistency. And, SPC helps with just about any aspect of continuous improvement you can think of. All in all, not a bad day’s work for a bunch of math geeks. Take a look at SPC, it’s well worth it.
This post was written by John Clemons. John is director of manufacturing IT at MAVERICK Technologies, a leading system integrator providing industrial automation, operational support, and control systems engineering services in the manufacturing and process industries. MAVERICK delivers expertise and consulting in a wide variety of areas including industrial automation controls, distributed control systems, manufacturing execution systems, operational strategy, and business process optimization. The company provides a full range of automation and controls services – ranging from PID controller tuning and HMI programming to serving as a main automation contractor. Additionally MAVERICK offers industrial and technical staffing services, placing on-site automation, instrumentation and controls engineers.
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2012 Salary Survey
In a year when manufacturing continued to lead the economic rebound, it makes sense that plant manager bonuses rebounded. Plant Engineering’s annual Salary Survey shows both wages and bonuses rose in 2012 after a retreat the year before.
Average salary across all job titles for plant floor management rose 3.5% to $95,446, and bonus compensation jumped to $15,162, a 4.2% increase from the 2010 level and double the 2011 total, which showed a sharp drop in bonus.