What is the difference between SPC and inspection?

Inspection detects defects after they occur. SPC monitors the process to prevent defects by detecting variation early.

Which chart types are commonly used in SPC?

Common charts include X-bar and R, X-bar and S, I-MR, p-chart, and u-chart depending on data type and sample size.

How often should control limits be updated?

Update control limits only after verified process changes or significant improvements, not based on short-term fluctuations.

Is SPC required by IATF 16949?

SPC is a core tool expected by automotive customers and required for managing key characteristics under IATF 16949.

What causes false alarms in SPC?

Unstable measurement systems, small sample sizes, and incorrect chart selection can create false signals.

Definition

Statistical Process Control(SPC)

Statistical Process Control (SPC) uses control charts and statistical methods to monitor process stability and detect variation before defects occur.

What is Statistical Process Control?

SPC is a core quality tool used to distinguish common cause variation from special cause variation. By monitoring process data over time, teams can detect instability early and take corrective action before nonconforming parts are produced.

SPC is required in many automotive applications and is commonly tied to critical-to-quality characteristics and capability requirements.

Key Points

SPC focuses on process stability, not just inspection results
Control charts help detect special cause variation early
SPC reduces scrap and rework by preventing defects
Capability studies (Cp, Cpk) are often linked to SPC
SPC requires consistent data collection and reaction plans

How to Calculate Statistical Process Control

Formula:

Control Limits = Process Mean +/- 3 x Standard Deviation (typical)

Variables:

Process Mean= Average of measured values
Standard Deviation= Variation of the process data

Example:

If the mean is 10.00 and standard deviation is 0.05, control limits are 10.00 +/- 0.15 (9.85 to 10.15).

Implementation Guide

Steps:

1Select critical characteristics and measurement method
2Define sampling frequency and chart type
3Collect baseline data to set control limits
4Train operators on chart interpretation and reaction plans
5Monitor charts and investigate out-of-control signals
6Update control limits after confirmed process changes

Best Practices:

Use reaction plans that define immediate containment steps
Ensure measurement systems are stable (MSA)
Separate set-up variation from steady-state variation
Review control charts regularly with engineering support
Link SPC signals to 8D and root cause analysis

Common Mistakes to Avoid

• Using SPC only for reporting, not for decision-making
• Setting control limits using unstable data
• Ignoring out-of-control signals or over-adjusting processes
• Incorrect chart selection for the data type
• Failing to connect SPC to corrective actions

Qualiteh's Approach to Statistical Process Control

Qualiteh helps teams implement SPC with proper chart selection, measurement system validation, and clear reaction plans. We integrate SPC results into corrective action workflows for faster issue resolution.