Optimizing the System vs. the Component
|Quality Design||The traditional design approach in the automotive industry is to optimize components (Gormley & MacIsaac, 1989). This component approach is founded on the belief that any design can be broken down into independent and self supporting components. The optimization and the evolution of the whole is assumed from the optimization and evolution of every component (Ziebert, 1991).
From the mid-80s, concurrent engineering methods (ex: DFMA, GT, Taguchi, FMEA, QFD, Value Engineering) and tools (CAD, CAE, CAM, PDM) have been supporting this component approach. Component design started to take into consideration life cycle process requirements. For example, existing components are evaluated according to DFMA rules and the component is modified, preserving its functionality, to improve its ease of manufacturing and assembly. CAD/CAM tools such as feature-based technology allow the simultaneous design process and process planning of components.
Sometimes in designing a new vehicle, our focus on the components, tends to shackle us and blind our very eyes. Then we begin to wonder why we cannot run faster than others and are always playing catchup. Opportunities are all around us. More recently, communications and integration technologies have been helping to close the gaps between the organizations responsible for the various component life cycle processes.
As the automobile grew in functionality and became a more multidisciplinary product, more component development process took place. Better components were substitute for old ones and new components were simply added to the current design version. Examples of the consequences of this approach applied to automotive electronics show that it has not led to the optimization of the whole product and its lifecyle processes (Ziebart, 1991):
Concurrent engineering of components would help component evolution, but only an interdisciplinary, collaborative approach to derive, evolve and verify a lifecyle balanced system can deliver better results that meet customer expectations and public acceptability. Better quality is a result of the fact that the product is developed and verified against requirements that can be traced to original stakeholder's requirements.