SPC on the shopfloor: catch the drift before it becomes scrap

Inspection tells you a part is bad. SPC tells you a part is about to be bad.

That's the whole difference, and it's why statistical process control is one of the most valuable things you can put in front of an operator. Yet in a lot of plants, SPC still means a quality engineer updating a spreadsheet at the end of the week. By then, the scrap is already in the bin.

Specification limits vs control limits

This is the concept people mix up most, so let's align on terminology.

Specification limits come from the customer or engineering. A shaft must be 25.00 mm, ±0.05 mm. Inside the limits is good. Outside is scrap.

Control limits come from the process itself. They're calculated from your own data, typically three standard deviations either side of the average. They describe what your process normally does.

A process can be in control and still make scrap, if its natural spread is wider than the specification. And a process can be entirely within specification while going out of control, drifting steadily towards a limit. That second case is exactly what SPC exists to catch.

Control charts

A control chart plots measurements over time, with the average and control limits drawn on. Operators look for points outside the limits, or patterns that shouldn't happen by chance.

For variable data (things you measure, such as length, weight or temperature), the common charts are:

• X-bar and R: averages and ranges of small subgroups, say five parts every hour
• X-bar and S: the same, using standard deviation, for larger subgroups
• I-MR: individual values and moving range, when you only get one measurement at a time, like a batch result
• EWMA or CUSUM: weighted charts that pick up small, slow shifts sooner than the standard charts

For attribute data (things you count), the choice depends on two questions:

The rules that matter

A point outside the control limits is the obvious signal. But patterns inside the limits often tell you more. The Western Electric and Nelson rules formalise them. The ones I'd teach every operator:

• One point beyond the control limits. Something just changed.
• Seven or more points in a row on one side of the average. The process has shifted.
• Six or more points steadily rising or falling. A trend, often tool wear or temperature drift.
• Points hugging the limits, or alternating up and down. Over-adjustment, or two streams mixed together.

Don't switch on every rule. Too many alarms and operators learn to ignore them. Start with a few, then add more where they prove useful.

Capability: Cp and Cpk

Capability compares your process spread with the specification.

• Cp asks: if the process were perfectly centred, would it fit within the specification?
• Cpk asks: given where the process actually sits, does it fit?

A Cpk of 1.33 is a common minimum for ongoing production. Automotive customers often ask for 1.67 on safety and critical characteristics, and for a Ppk of 1.67 in the initial study before production approval. Check your own customers' requirements; they vary. If your Cp is good but your Cpk is poor, you don't need a better machine. You need to centre the process.

Capability only means something when the process is in control. Calculate it on a process that's all over the place and you'll get a number. It just won't mean anything.

Why SPC belongs in MES/MOM

SPC works when the person who can act on it sees it in time. That's the operator, at the line, during the shift.

Running SPC in MES/MOM gives you things a standalone tool or spreadsheet can't:

• Checks triggered by what's running. The right characteristics for this product, at the right frequency.
• Data from the gauge, not the clipboard. Connected instruments remove transcription errors.
• Context on every point. Order, lot, machine, tool, operator, shift. When the chart shifts, you can see what changed.
• Action, not just alarms. A rule violation can require the operator to record a reason and a corrective action before continuing, or put the lot on hold.

I covered inspection plans and quality operations in MES functionality: quality operations. SPC is the part that turns those inspections from a pass/fail record into an early warning.

Closing the loop

SPC data is gold upstream too. Engineering wants to know which characteristics are hard to hold, so they can rethink tolerances or design. Quality wants trends across sites for the QMS. Where critical characteristics are defined in PLM, sending the capability results back closes the digital thread.

Here's a question to take to your next quality review: of last month's scrap, how much showed up as a trend on a control chart first, and nobody acted on it?