The Business Impact Working Group (BIWG) has created the following resources for members of the Engineering Simulation Community:
While engineering simulation is used widely in some companies and industries, almost all companies would benefit from increasing the use of simulation and there are industries where simulation is not widely used. Also small/medium sized companies are less likely to make use of simulation than large companies. The NAFEMS Business Impact Working Group has identified a number of ways to justify increasing the use of engineering simulation. Roger Keene discussed these different methods and offered advice on how to go about convincing senior management of the value of engineering simulation.
The development of a new motorcycle platform is a complex activity comprising of many engineering disciplines. The full development cycle can be as long as 40 months, depending on the complexity of the project. During the later stages of the program, there are typically four build phases, with increasing motorcycles produced at each phase. Engineering Simulation can be used to reduce the number of prototypes produced, and in some cases eliminate a complete build phase. This has three effects; reduced cost of prototype motorcycles, reduced program duration and faster time to market. The cost saving due to these effects is significant and can be used to show that investment in engineering simulation has a high rate of return, which allows the business to be more profitable. The case study presents findings from Royal Enfield internal study on the effectiveness of CAE.
The development of medical devices poses the exciting challenge of working across multiple engineering and clinical disciplines to advance technologies for alleviating pain, restoring health, and extending life. With this opportunity comes the need to advance modeling and simulation technologies to more richly and deeply characterize human anatomy and physiology and predict the interaction with the devices. An additional challenge is that the classes of devices significantly impacting patient’s health are surgically implanted and remain in the body for 10-15 years.
Given these complexities and challenges that push the envelope of mechanistic modeling, is the investment in modeling and simulation technology worth it? What are the factors that contribute to the decision to pursue a modeling and simulation solution in comparison to empirical forms of evidence? These questions will be addressed through the use of two case studies demonstrating business value of investment in modeling and simulation as well as the impact on patient care.