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Process Compliance Temperature Analysis

Quality control analysis of manufacturing temperature data against specifications. Features histogram with spec limits, process capability metrics (Cp/Cpk), and tiered corrective action recommendations.

Input

What you provide to the skill

5000 temperature measurements from our manufacturing process. Spec: 98.6°C ± 2°C. Show the production team if we’re compliant.

Output

What the skill generates for you

Smart Chart Recommender Analysis

Manufacturing Process Temperature Compliance

Data Analysis Summary

Dataset: 5000 temperature measurements from manufacturing process
Specification: 98.6°C ± 2.0°C (acceptable range: 96.6°C to 100.6°C)
Audience: Production team (technical stakeholders)
Goal: Show compliance with quality standards


Data Quality Report

No data quality issues detected

  • Missing values: 0 (0.0%)
  • Statistical outliers: 27 (0.54%) - within acceptable range

Key Statistics:

  • Mean: 98.70°C
  • Std Dev: 0.642°C

Recommended Chart #1: Histogram with Normal Curve and Spec Limits ⭐ BEST CHOICE

Why it works:
Industry-standard quality control visualization. Shows complete distribution shape, process centering, and percentage within specification limits.

What it shows:

  • Full distribution of all 5000 measurements
  • Whether process is centered on target (98.6°C)
  • Percentage within vs. outside spec limits
  • Outliers and extreme values

Best practices:

  • 40 bins for 5000 data points
  • Overlay fitted normal distribution curve
  • Vertical lines for spec limits (red dashed) and target (green solid)
  • Shaded out-of-spec regions
  • Text box with: n, mean, std dev, in-spec %, Cp, Cpk

Recommended Chart #2: Box Plot with Violin Overlay

Why it works:
Compact summary for dashboards or batch comparisons.

When to use:
Executive summaries or comparing this batch to previous batches.


Charts to AVOID

Bar Chart - Continuous measurements should never be binned into categories
Pie Chart - Makes no sense for measurement distributions
Line Chart - Only if measurements have meaningful sequential order


Key Findings

1. OVERALL COMPLIANCE: 99.46% In-Spec

  • 4,973 out of 5,000 within 96.6-100.6°C
  • 27 measurements out of spec (0.54%)

2. PROCESS CENTERING: Slight Upward Shift

  • Mean: 98.70°C (target: 98.6°C)
  • Process running 0.10°C above target

3. PROCESS CAPABILITY:

  • Cp = 1.04: Adequate inherent capability
  • Cpk = 0.99: Slightly below 1.0 due to off-centering
  • Process is CAPABLE but centering reduces safety margin

Recommended Actions

IMMEDIATE:

  1. Investigate the 0.10°C upward shift - check calibration
  2. Root cause analysis on 27 out-of-spec measurements

SHORT-TERM:

  1. Re-center process to 98.6°C target (adjust setpoint down 0.10°C)
  2. Implement continuous monitoring with control charts

LONG-TERM:

  1. Reduce variation further - target std dev of 0.55°C for Cp > 1.2

Bottom Line

You ARE compliant (99.46% in-spec)
⚠️ But you’re close to the edge (Cpk < 1.0)
🎯 Quick win available: Re-center by -0.10°C to improve capability