In September 2015 one of Philips Innovation Services most experienced problem solving experts presented a masterclass on quality & reliability problem solving at DAF Trucks, a Paccar company. Thirty-five specialists attended. Most of them are primarily confronted with reliability problems in their daily work. For many, the topics turned out to be eye-opening. They evaluated this introductory course very positively: a 4.1 on average (on a 1-5 scale).
Real-life quality issues were discussed
During the masterclass some general aspects and pitfalls of (Q&R) problem solving have been discussed and the Statistical Engineering (SE) or Shainin methodology has been introduced. Some typical SE tools and techniques were presented and applied to real-life quality issues. A few expressed their uncertainties about how to fit the approach into the ‘daily DAF practice’, but most are very enthusiastic about the methodology and eager to learn more.
Effective approach to tough chronic problems
Certainly, a half day introduction is not enough to get all the details of the methodologies under one’s belt. A key reason why certain problems are ultimately not solved is related to the approach engineers use, which is not effective in all cases. Their approach is often based on a set of tools and techniques that is less effective for solving tough, chronic quality or reliability problems. By definition, chronic problems are those kinds of problems for which it is difficult, if not almost impossible; to conceptualize or brainstorm the possible causes (the Xs).
Studying the behavior of the effect
A first attempt to solve a problem is usually to think with experts about the most plausible causes (=brainstorm). Engineers select the most likely Xs and run an experiment to verify if they were right. Many easy real-life problems can be solved in this manner. However, for tough, chronic problems, this approach often times doesn’t work. The reason is that the actual cause is not in their brainstorm list; it is something that is yet unknown.
That’s why we prefer a methodology that doesn’t start with the listing of possible causes (the Xs). We prefer to start with contrasting extremely good and extremely bad products. So it embarks from studying the behavior of the effect, the Y first, and asking the question: “what makes the difference between an extremely good and extremely bad product?”, the BOB (Best-of-the-Best) and the WOW (Worst-of-the-Worst) in the Shainin jargon.
Would you like to know more about?
Contact our quality & reliability consultant Albert Ponsioen for more information