Design for Multiple Industries: A PDP (Parallel Distributed Processing) Approach

Abstract

A Parallel Distributed Processing (PDP) or Neural Network model is proposed. It restructures our knowledge and experience in product development in the form to achieve widest applicability. Up to now, product developments have been discussed within one company or one industry at the widest. But in order to increase productivity and to reduce time, cost and energy consumption by a large margin, a great change in our way of thinking is called for. We need to go beyond one company or one industry and team up with other industries. Just as Concurrent Engineering succeeded in one company or in one industry by bringing downstream information upstream and by processing them concurrently, this goal can be realized if we introduce Parallel Distributed Processing (PDP) model. PDP is more popularly known as Neural Network. As the relationship between raw materials, intermediate products and final products can be described as a neural network, this goal can be achieved if knowledge and experience are shared across different industries and re-assembled at the intermediate components layer. Then, final products can be developed as the combination of these intermediate components just like Lego. This not only eliminates overlaps between industries, but this-organizes our knowledge and experience into the form applicable to wider applications and wider areas so that it brings forth greater flexibility in product development. In short, a PDP or Neural Network model proposed here is the restructuring of our knowledge and experience in order to expand their applications to the widest. Such restructuring not only achieves widest applicability, but it also helps introduce autonomous distributed economy. Our economy has been too much centralized. If we change our economy system to autonomous distributed system, countries can team up more effectively and develop Win-Win relations, which is most important in this age of globalization.