Does one of the following sound familiar? “We are not sure whether we really solved the problem.” “The root cause analysis team has been trying many things but nothing seems to work.” “We do not have enough resources for root cause analysis.” In that case our one-day workshop Root Cause Analysis will give insight how to get out of the impasse, following state-of-the-art techniques.
The purpose of the workshop
Problem solving deals with processes with a spread on the output, leading to products that do not fit requirements. The Statistical Engineering (SE) methodology exploits the fact that one root cause always has the largest contribution and the goal is to find this root cause and to understand it. When you have found the root cause, the solution is most of the time obvious. During this One Day Workshop awareness will be developed to solve problems with help of the SE methodology. The workshop enables the participants to apply this methodology in their own working environment.
What will be learned - the skills
n this workshop the following subjects/skills will be taught:
• Introduction to the SE methodology
• Measuring systems analysis
• Decision tools
• Strategy diagrams
• Specific statistical tools (part swap analysis, GP/TP analysis, multi-vari)
• SE concepts (critical to quality, major root cause)
The One day workshop Root cause analysis is a professional, intensive, one-day workshop, aimed at executives and senior engineers who work in production and development. This workshop is especially designed as an extension to the existing Design for Six Sigma Black Belt training in the area of DMAIC and DIDOV. But this workshop can also be followed separately.
University or college education, or an equivalent level acquired through working experience.
Methodology: ‘Listening to the parts’
The principle of this workshop is: ‘Listening to the parts’. In other words, go to the work floor, take the products that are not meeting requirements and compare these with the correct products. This often reveals more than the overflow of data and statistics that the quality manager receives on a daily basis. When you have a product that is assembled out of different components, it is a good start to disassemble the product and put it together again. When the malfunction keeps persisting there is a problem with one of the components. When the problem after reassembling has disappeared you can eliminate the components as a possible cause and look at the assembly process steps themselves. The underlying thought is that differences will appear more clearly when looking at the extremes.
|The program can be taught in English on request.|