04 May 2016: Hexagon Manufacturing Intelligence

Statistical process control is an increasingly widespread method of improving manufacturing visibility, and to provide a beginner’s guide to the technique, Tom Stewart, President of the North American subsidiary of Q-DAS, recorded a podcast interview. Hexagon Manufacturing Intelligence's Accelerate! magazine catches up with the conversation in this HxGN Radio Recap.

Could you give us an overview of what statistical process control (SPC) is?

Statistical process control is the matter of collecting data during the manufacturing process and determining whether the process is stable, in control, and trying to determine the probability that parts will be in spec or out of spec.

What challenges do manufacturers face in applying statistical processes to manufacturing systems?

Well, in many cases the traditional methods of statistical process control, which were originally derived in the 50s, 60s and 70s are simply not applicable today. So in a given plant, while they’re making production parts they have to be concerned about tool wear, and tool life, and targeting a process, and so many process parameters.

Why are those 50s, 60s and 70s processes not applicable today?

In those days the production process was more or less linear. For example, in the automotive industry, it’s transfer line based, where a piece part would be processed in one operation and then sequentially go to the next and the next. So in those days, they were taking the piece parts off of the production line in the order they were manufactured and measuring them in the order they were manufactured. And in that case they could develop a subgrouping of the data and something called the Western Electric Rules: runs, trends, middle thirds, were more applicable than they are today.