Use of Additive Manufacturing in Product Design & Development

Now for past many decades, automotive manufacturing is under perennial pressure owing to consumer aspirations, regulations, globalized competition and sustainability needs. Automotive manufactures are fiercely satisfying all of above constraints through innovative solutions. The resultant vehicles have many complex to very complex systems and subsystems to deliver the performance aspirations. In this game, one of the critical business parameter is rapid time to market. At the current state of the art, time to market directly conflicts with new product development time. Four wheeler new product development consumes upward of 48 months, while risking obsolescence of product features at the time of launch. Automotive manufacturers invest intensely in technologies to achieve this goal of short time to market. Digital technologies delivering high time efficiency have made deep in roads in the automotive product development arena. However yet physical validation is an inevitable step to get vehicle ready for launch. Meaningful validations require functional prototypes. Products being complex in nature, significant lead-time and investments are consumed in prototyping. Conventional part or tool manufacturing works as counterproductive for cost as well as time needs. Hence one more time shortening technique is to build functional prototype for a fixed purpose (validation intent). Built for purpose prototypes deliver extremely high time efficiency, but demand highly skilled prototype manufacturing engineers and technicians. Such rare teams work innovatively combining art and science to compress time lines. This technical paper focuses on smart use of quick manufacturing processes inclusive but not restricting to AM for advancing the product development. The achievement lies in using AM along with allied technologies to achieve the desired fit for purpose functional prototype rapidly. Innovated method would also yield a cost advantage as against the standard prototyping/manufacturing processes. Paper would also discuss on the possibilities of takes these learning for mass manufacturing.