As a result, most research labs, both in academia and industry, have few people with the expertise to use current modeling capabilities efficiently. Often this lack of understanding implies that modeling is never even considered in solving a problem. Modelers themselves have hardly done better. Only a few years ago our field focused heavily on the development of methods with little focus on the real, technologically relevant problems that could be solved with them. This induces significant bias from computational researchers when selecting a tool to address an industrial problem and may be the reason for many of the failed ventures between industry and modelers in the past.
Industrial sponsors have to realize when they are buying into a method rather than a solution.
Several steps can be taken to reduce this mismatch between modelers and their customers. Education is likely to be the most important one. Through modification of the materials science and engineering curricula we can guarantee that future engineers are aware of computational modeling as an important research tool. Students must be given enough background to realistically assess the applicability of computational modeling to solve a given problem. Integration in industry can be achieved with summer courses and seminars using case studies to focus on the capabilities and limitations of current modeling technology.