Problem Solving at Clients

David Hartshorne helps improve product performance and reliability, and manufacturing performance for clients supplying to and building, trains, planes and automobiles worldwide. David’s clients have included ABB, Alcoa, Bosch, Carrier, Daimler-Chrysler, Delphi, Delta, General Motors, Hexcel, Lafarge, Philips, Rolls-Royce Aerospace, ThyssenKrupp, TRW and others. He has worked in precision machining, precision assembly, foundries, sheet metal fabrication, plastic molding, chemical and electronics products.

David's reputation is based upon his ability to assist clients in solving complex technical problems quickly and efficiently. Projects range from reducing parts per million (ppm) defective in manufacturing processes, to reducing ppm field failures, and extending the expected useful life of clients’ products. Some examples of projects illustrate the impact that finding the real root cause can have, and how problem solving relates to redesign.

One client was manufacturing a safety critical component for the power industry. The yield was poor, and the economic and environmental impact was extremely undesirable. A group of technical experts from around the world had been assembled to solve the problem. Over the course of a few months, the team had developed technologies to improve yield, and were ready to conduct a series of experiments. Initially, they consulted David for advice on conducting Statistically Designed Experiments (SDE, also known as Design of Experiments, or DOE). Instead, he showed them how to obtain data, and organise it to converge from effect, Y to cause, X. Within a week, and only three days of David’s time, the real root cause had been identified. Of course, it had not been suspected at all up to that point.

Another client had redesigned part of their product, a high-pressure valve, to change the profile of the fluid delivery curve to suit a new application. The new design suffered an unacceptable variation in fluid delivery quantity from cycle to cycle. Using the convergent strategy Y to E to X, the controlling geometry of the valve was identified, and both the new and existing application designs were refined to reduce cycle-to-cycle delivery variation to fractions of what they were previously. All of this was achieved without resort to an expensive Fractional Factorial DOE.

A third client was replacing a large number of performance critical components on machine tools under warranty. As well as the economic impact, they had at least one very unhappy customer, an automotive engine plant that had purchased a large number of that model. Several independent studies had identified potential suspects such as oil contamination and incorrect installation factors, amongst others. On the basis of the reports, so called corrective actions had been taken, but to no avail. What all of these studies had in common were preconceived ideas and a selective evaluation of the facts. In fact, a Y to E to X approach showed that it was possible to predict exactly which components, in which positions, on which machines would wear out prematurely. Once the real root cause was identified, an effective corrective action was implemented.

David worked with Shainin from 1993, and was a founding member of Shainin LLC in 1997. Prior to that, David’s career was first in Automotive, then the Aerospace industry, with responsibilities for implementing Lean Manufacturing as well as product performance and reliability improvement. David holds a Master of Science degree from Warwick University, UK.
David is a respected speaker and lecturer. For years, he taught Shainin Statistical Engineering seminars, and was a presenter at Shainin Symposia.

David enjoys skiing, landscape design and construction, and reading the history of gardens, science, mathematics and technology.