I have recently worked with the engineers in QA (Quality and Assurance) team. They have been investigating the products returned from our customers because of a problem, and tried to find the root-causes of the problem. But the returned products have never shown the problem complained by the customers even with thorough tests. We call such returned products as NPF (No-problem found).
They were the experts in QA, and their investigation with the data was very detailed, and they did their best. But they couldn’t find any root-cause of the problem, and only time passed by. So I joined to their team and listened to what was going on.
According to them, they investigated the data saved in the products, the information from the customers, and the data collected from the product return process. But it seemed to me that quality and reliability of the data were questionable.
So I suggested to improve the data collection process first so that reliable data can be used for further investigation in stead of spending time and money for the investigation with the low quality data. The process improvement could take time, but faster overall. And the result of investigation with good data could be more useful.
What I proposed was a typical Lean Six Sigma (DMAIC) framework for the process improvement.
1. Define Project
- Define project scope (Project Charter, Business Case, SIPOC)
- Identify project success-factors or vital few (SIPOC, AHP, QFD)
- Identify stakeholders in the project (RASCI Matrix)
2. Measure Current Process
- Understand current process (Process Map, VSM)
- Identify problems in the current process (C&E Diagram, C&E Matrix)
- Identify potential current process issues (Preliminary Process FMEA)
- Plan for data collection (Data Collection Plan)
3. Analyze Problem and Propose New Solution
- Analyze root-causes of the issues (VA/NVA Analysis, Waste Analysis)
- Create new process modes for simulation (Arena or SimEvents)
- Select best process model (Concept FMEA, Pugh Matrix)
- Analyze implementation cost (Cost Analysis)
4. Improve Process (Implement Solution)
- Identify action items (Gap Analysis)
- Identify process risks (Process FMEA)
- Create implementation plan
- Implement solution
5. Control New Process
- Evaluate new process (Data Collection, Statistical Analysis)
- Evaluate process stability (Statistical Process Control)
- Hand-off with documentation
The main purpose of this project was to improve the process for receiving the returned product from customers so that high quality and reliable data is collected in the process. The process itself was not completed, but there were many stakeholders involved. So the careful planning was needed.