Supply Chain Lab SPC Control Charts Lab Home
Capacity & Operations

SPC Quality Control Charts

A bottling line fills 500 ml bottles; every hour a sample of five is measured onto X̄ and R charts. Sabotage the process - nudge the mean or inflate the variance - and see which chart catches it, how fast, and what it does to Cp and Cpk.

How to use it

The line

Sampling

Sabotage the process

Process healthy: μ=500, σ=4.

Specification limits

Specs are the customer's voice; control limits are the process's voice. They are not the same thing.

–
Cpk (actual)
–
Est. % out of spec
–
Samples to detect

X̄ chart - sample means vs ±3σ control limits (UCL/LCL = X̄̄ ± A₂R̄, A₂=0.577 for n=5). Catches mean shifts.

R chart - sample ranges vs D₃R̄, D₄R̄ (0 and 2.114·R̄ for n=5). Catches variance changes the X̄ chart can miss.

Try these experiments

  1. Arm a +1σ shift and count the samples until a red point - small shifts hide for a long time (that is why CUSUM/EWMA exist).
  2. Widen the specs until Cpk looks great while the armed shift is still undetected - capability improved, control did not. Explain the difference.
  3. Arm variance ×1.8: the R chart fires while the X̄ chart often stays quiet - means can look fine while spread rots.

About this tool

The concept

SPC separates common-cause noise from special-cause change. React to signals, not to noise - adjusting a healthy process makes it worse.

How it works

Limits come from the process itself: X̄̄ ± A₂R̄ and D₃/D₄·R̄, estimated from the calibration samples with σ̂=R̄/d₂.

Capability

Cp=(USL−LSL)/6σ̂ asks if the process could fit the specs; Cpk asks if it actually does, given where the mean sits.