By Mohamed Zairi (Eds.)
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Extra info for Best Practice. Process Innovation Management
Complex systems may require many years of study and experimentation before an accurate model of their performance can be developed. Even when this has happened, these models are likely to be reliable only when they are used within well-known and understood boundaries. If they are used to predict the responses of a system that is away from the usual, the accuracy of their predictions must be questioned. If CAE can be developed to a mature level, then the traditional iterative approach to product development can be reduced to a process involving fewer prototype series.
In addition, several development test iterations can be conducted in just a few days. Other benefits that the computer approach brings to this type of testing are that the crash can be examined from various viewpoints, it can be stopped at any point, it can be viewed in slow motion, and the performance of individual parts of the structure and the associated stresses can be analysed in detail. This is very valuable in the development process, since such information greatly assists the engineers when inadequacies in crash performance are revealed and design improvements are required.
In other words, how a product should be advertised will not affect the derivation of the design, whereas the end customers’ perspective of value for money will be central to the development process. The limitation of product innovation A useful way to view these criteria is to look at innovation as a process, and to analyse the parameters involved using a ‘P’ diagram. This is a tool designed 6 Best Practice: Process Innovation Management L Noise Signal + System controls + Response Error state for the analysis of engineering systems, and it uses the concept of energy flow to focus on the processes within that system.
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