SAP QM Statistical Process Control

You are an SAP QM (Quality Management) consultant specializing in Statistical Process Control implementation. The user wants to set up SPC with control charts and quality scoring in SAP QM.

What to check first

• Run transaction QCC1 to verify QM module is installed and active in your SAP system
• Check SPRO > Quality Management > QM-QC > Control Charts to confirm customizing tables are populated
• Verify user has authorization role SAP_QM_CONTROLLER or SAP_QM_MANAGER in transaction PFCG

Steps

1. Create a control chart group in transaction QCC1: Enter Chart Type (e.g., C-CHART for defect count or X-BAR for measurements), assign inspection characteristics, and set control limits (UCL/LCL)
2. Define inspection lots in QA11 (Create Inspection Lot) with reference to your material and inspection plan; attach the control chart group created in Step 1
3. Set SPC sampling strategy in OQC0: Define lot size ranges, sample sizes, and AQL (Acceptable Quality Level) per ISO 2859-1
4. Configure quality scoring rules in QA32 (Maintain Quality Score): Assign point values for defects, non-conformances, and compliance; set thresholds for supplier rating (Excellent/Good/Poor)
5. Record inspection results in QA11 (Enter Results tab): Input measured values or defect counts; SAP automatically calculates control chart statistics (mean, standard deviation, sigma limits)
6. Review SPC charts in QMOD (Quality Control Dashboard) or transaction QCC2 (Control Chart Analysis): Visual display shows trending, out-of-control points (rule violations), and capability indices (Cpk)
7. Execute quality notification workflow in QM01 if control limits are violated; attach corrective action requests to initiate root cause analysis
8. Run QA37 (Quality Score Report) to generate supplier scorecard and QA36 (Control Chart Report) to export SPC metrics for management review

Code

*& Report: Z_SPC_CONTROL_CHART_SETUP
*& Purpose: Setup and monitor SPC control charts with quality scoring

REPORT z_spc_control_chart_setup.

DATA: lt_insplot TYPE TABLE OF qals,
      lt_results TYPE TABLE OF qqevalh,
      lv_chart_id TYPE qccid,
      lv_mean TYPE p DECIMALS 2,
      lv_stdev TYPE p DECIMALS 2,
      lv_ucl TYPE p DECIMALS 2,
      lv_lcl TYPE p DECIMALS 2,
      lv_cpk TYPE p DECIMALS 3,
      lv_quality_score TYPE p DECIMALS 1.

* Create control chart group
PERFORM create_control_chart USING lv_chart_id.

*

Note: this example was truncated in the source. See the GitHub repo for the latest full version.

Common Pitfalls

• Treating this skill as a one-shot solution — most workflows need iteration and verification
• Skipping the verification steps — you don't know it worked until you measure
• Applying this skill without understanding the underlying problem — read the related docs first

When NOT to Use This Skill

• When a simpler manual approach would take less than 10 minutes
• On critical production systems without testing in staging first
• When you don't have permission or authorization to make these changes

How to Verify It Worked

• Run the verification steps documented above
• Compare the output against your expected baseline
• Check logs for any warnings or errors — silent failures are the worst kind

Production Considerations

• Test in staging before deploying to production
• Have a rollback plan — every change should be reversible
• Monitor the affected systems for at least 24 hours after the change