DOC. NO. 2026-0730
Jointly published by AIAG & VDA · Official July 2026 edition
[July 30 Online Seminar]
AIAG & VDA SPC Manual
1st Edition (2026): Key Changes × Quality Knowledge Base in Practice
Practical process monitoring, corrective action, and recurrence prevention
In 2026, AIAG and VDA jointly published a new SPC manual that further emphasizes learning about a process through process studies, interpretation of variation, and appropriate models. This seminar addresses both halves of that work: understanding the process from its signals and retaining proven corrective-action knowledge.
Go to Microsoft Teams and complete the registration form; select the button labeled “Register.”
From interpreting process signals to preserving and reusing corrective-action knowledge—start with the complete agenda.
AGENDA
| 14:00–14:05 | Opening |
|---|---|
| 14:05–15:00 | Session A | Key SPC changes and practical discussion (Shih-Chuan Hu) |
| 15:00–15:15 | Session A Q&A + break |
| 15:15–15:35 | Session B | Building an enterprise quality knowledge base (Yi-Chun Shih) |
| 15:35–16:00 | Session B Q&A + closing |
Times are planned allocations; the event-day agenda takes precedence.
Key changes in the new SPC manual
and practical discussion
The 2026 manual, jointly published by AIAG and VDA, provides a common SPC framework and terminology. Session A distinguishes official manual content, technical interpretation, and MiDFUN’s implementation perspective, helping you understand study boundaries, methods, and interpretation logic.
Shih-Chuan Hu
Lead speaker on the new SPC manual · CQE Quality Engineer
With nearly 20 years in manufacturing quality management and QMS/QRP implementation, his projects span semiconductor packaging and testing, electronic components, PCB/optoelectronics, precision metals, automotive components, chemicals, and aerospace, including cross-border factory projects in the United States and Japan. His expertise covers SPC, QRP quality resource planning, FMEA/Control Plan, APQP/PPAP, SQM, and quality knowledge management. He will explain the new manual and implementation strategy from an enterprise quality-management perspective.
- 01
SPC management thinking and organizational foundations
Move beyond drawing charts for compliance to roles, capabilities, data quality, and response mechanisms so SPC supports cross-functional process understanding and improvement.
- 02
Process studies and capability assessment
Define the study purpose and included sources of variation before interpreting Cp/Cpk, Pp/Ppk, and Cw/Cwk. Read every index together with evidence of control, the data period, model, and method.
- 03
Process variation and monitoring methods
Understand variation through time order, rational subgrouping, and time-dependent models. Separate analysis from real-time SPC monitoring, and distinguish the roles of control limits and specification limits.
- 04
Digital tools and data governance
Distinguish software verification from validation and retain data, parameters, algorithm versions, and expected results so capability reports are reproducible and quality-issue response is traceable.
Build an enterprise quality knowledge base
From corrective action to proactive process control
SPC uses data, models, and monitoring signals to increase process understanding. MiDFUN extends that learning into management practice through a quality knowledge base where quality issues, causes, corrective actions, and verification records are searchable and reusable for daily prevention. The four topics form a continuous loop, not a one-way flow.
Yi-Chun Shih
Quality knowledge base speaker
She supports manufacturing quality-system services and implementation across SPC, MSA, BKM, FMEA, and document-control workflows. She understands the practical problems of scattered quality data, lost corrective-action knowledge, and weak cross-functional handoffs. She will show how to integrate quality issues, causes, corrective actions, and verification records into a searchable, traceable, sustainable enterprise quality knowledge base.
- 01
Prevent quality issues from recurring
Create traceable relationships among the problem, cause, action, verification, and recurrence prevention.
- 02
Improvement should not stop at case closure
Feed effective practices back into standards, controls, and training instead of leaving them inside one closed case.
- 03
Make risk control operational
Bring historical quality issues and corrective actions into risk identification, process planning, and daily management.
- 04
Data monitoring and continuous improvement
Use continuous monitoring to verify improvement effectiveness and detect new variation.
- ↺
The loop returns to 01: accumulated corrective-action knowledge captures new monitoring signals and makes recurrence less likely.
What you will take away
- 01A plain-language map of the new manual: study boundaries, Cp/Cpk, Pp/Ppk, Cw/Cwk, and reporting methods
- 02A practical interpretation sequence: examine time order and process state, then choose models and monitoring; establish evidence of control before discussing capability
- 03A process for moving from case closure to proactive process control: OCAP → knowledge base
- 04Data and governance to retain in a quality knowledge base: traceability, outliers, and parameter settings
Who should attend
An index meeting its target
does not meanstability has been demonstrated.
Reports arrive on time, indices meet targets, and control charts look quiet. Yet the new manual reinforces one critical sequence:Confirm study boundaries and process state before interpreting capability indices.Cp/Cpk and Pp/Ppk should not be reduced to fixed short-term/long-term labels. State the evidence of control, data period, distribution model, and estimation method. Cw/Cwk focus on within-group variation and provide diagnostic information, but they do not replace the overall process study. A process that “looks stable” still needs reproducible evidence.
2026 edition · Five points in one minute
When the control chartsends a signal
Most companies can move from signal detection and notification to containment and case closure. The difference appears afterward: is the response experience retained and retrievable?
- [14:32:05]SPC ALERT — Control-chart signal: one point above the upper control limit
- [14:32:06]Rule evaluation: Rule 1 — beyond the 3σ control limit
- [14:33:12]Notify: process engineering / quality assurance / line supervisor
- [14:47:00]OCAP launched: containment, investigation, quality-issue record…
- What happens after closure?
The same quality-issue record, handled two ways.
Disposition, corrective action, closure—most organizations work similarly up to this point. The difference begins after closure.
APPROACH A
Close and archive only
- Write “reinforce training” as the action and close the record
- Quietly delete suspect data as “outliers,” losing the original evidence and interpretation boundaries
- Leave corrective-action knowledge in one person’s memory and deep in a folder
- Three months later, the same quality issue appears on another line
- During new-product planning, no one remembers the history
- The same response cost is incurred again
APPROACH B
Write it into the quality knowledge base
- Connect problem, cause, action, and verification in one traceable record
- Retain raw data; if exclusion from calculation is necessary, investigate the cause, document the basis, and preserve the analysis version
- Feed effective practices back into standards, the Control Plan, and the OCAP out-of-control action plan
- Make experience searchable, comparable, and reusable across lines and plants
- Bring historical knowledge into risk identification and process planning
- Address the risk before the next signal appears
How to move from Approach A to Approach B is the focus of the July 30 second session.
SPC does more than calculate numbers;
it uses signals of variationto increase process understanding.
— Summarized from the management direction of the AIAG·VDA SPC 2026 manual.
Session A builds process understanding; Session B asks how effective experience can be retained.
EVENT INFO
| DATE | July 30, 2026 (Thu.) |
|---|---|
| TIME | 14:00–16:00 (includes break and Q&A) |
| FORMAT | Microsoft Teams online seminar |
| SPEAKER | Shih-Chuan Hu (Session A) / Yi-Chun Shih (Session B) |
| FEE | Free |
| CONTACT | Po-En Chiu |qbn@midfun.com.tw | 02-2592-2510 #115 |
Registration instructions
Use the button below to open Microsoft Teams, then select “Register” and complete the form. Registration takes about 1–2 minutes.
After registering, look for the Microsoft Teams confirmation email. A reminder and joining instructions will be sent before the event. Check your junk folder if the confirmation does not arrive. Seminar materials will be emailed after the event.
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APPENDIX
Is the seminar suitable for someone without a statistics background?
Yes. The focus is management thinking, process interpretation, and implementation; complex formula derivations are not a prerequisite.
We still use the old AIAG SPC manual (2005, 2nd edition). Will we be able to follow?
Especially so. Session A corrects common legacy simplifications: Cp/Cpk and Pp/Ppk cannot be separated only as short-term versus long-term, and Cw/Cwk focus on within-group variation without replacing the overall process study. It establishes study boundaries, evidence of control, models, and reporting before discussing system implementation.
How do I receive the joining link after registering?
After Teams Event registration, the system sends a confirmation email and another reminder before the event. Follow the instructions on the official registration page.
May I attend only one session?
Yes, if your schedule requires it. The two sessions form one path from process monitoring to recurrence prevention, so attending both is recommended.
Will seminar materials be provided?
Yes. The organizer will email seminar materials to registrants after the event.
FINAL — JULY 30, 2026 (THU.) · MICROSOFT TEAMS
Turn corrective-action experience
into proactive process control.
Free registration is open. Register now and add the event to your calendar.