𝐓𝐨𝐝𝐚𝐲'𝐬 𝐊𝐍𝐎𝐖𝐋𝐄𝐃𝐆𝐄 𝐒𝐡𝐚𝐫𝐞 : 𝐒𝐏𝐂 𝐄𝐗𝐏𝐋𝐀𝐈𝐍𝐄𝐃 — 𝐒𝐓𝐄𝐏 𝐁𝐘 𝐒𝐓𝐄𝐏

 𝐓𝐨𝐝𝐚𝐲'𝐬 𝐊𝐍𝐎𝐖𝐋𝐄𝐃𝐆𝐄 𝐒𝐡𝐚𝐫𝐞

📊 𝐒𝐏𝐂 𝐄𝐗𝐏𝐋𝐀𝐈𝐍𝐄𝐃 — 𝐒𝐓𝐄𝐏 𝐁𝐘 𝐒𝐓𝐄𝐏

Statistical Process Control (SPC) helps you understand process variation, stability, and capability before defects reach the customer. 🎯

🔹 STEP 1 — Define Specification Limits

🎯 Target = 50.00 mm

⬇️ LSL = 49.80 mm

⬆️ USL = 50.20 mm

Specification limits come from customer/product requirements.

🔹 STEP 2 — Confirm the Measurement System

🛠️ Use calibrated measuring equipment

📏 Perform Gage R&R where appropriate

✅ Ensure measurement variation is small compared with process variation.

🔹 STEP 3 — Collect Rational Subgroup Data

📋 Collect data in time order.

👥 Use rational subgroups — parts produced under similar conditions.

Example: 25 subgroups × 5 parts

🔹 STEP 4 — Plot Control Charts

📈 Use an X̄-R Chart for subgroup data.

Control charts help identify:

• Common-cause variation

• Special-cause variation

• Trends, runs and other non-random patterns

🔹 STEP 5 — Confirm Process Stability

✅ Points within control limits

✅ No significant non-random patterns

➡️ Process is statistically stable.

⚠️ If the process is unstable, identify and remove special causes before capability analysis.

🔹 STEP 6 — Calculate Process Capability

📐 Cp = (USL − LSL) / 6σ

📐 Cpk = min [(USL − X̄)/3σ, (X̄ − LSL)/3σ]

👉 Cpk considers both process variation and process centering.

🔹 STEP 7 — Interpret Cpk

📌 Cpk < 1.00 → Not capable

📌 1.00–1.33 → Needs improvement

📌 1.33–1.67 → Generally capable

📌 1.67–2.00 → Very capable

📌 > 2.00 → Excellent capability

💡 Key SPC Principle:

Stable Process + Capable Process = Consistent Quality

🎯 SPC is not just about calculating numbers.

It is about understanding variation, controlling the process, and continuously improving performance.

source : Six Sigma Manufacturing

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