Hierarchies of adaptable learning during product development

Shorter product lifecycles, shrinking time-to-market and increasing global competition, drive companies to premature transitions from the development laboratory to full-scale commercial production. This ramp-up period is usually considered as a transient phenomenon and often ignored by a large body of literature. Hence, the current push for accelerated development and quality manufacturing of new products, has increased the need to model and measure production performance during ramp-up. Despite this need for a concrete framework of these early stages of the product life cycle, a useful model of ramp-up, formalizing this tradeoff between product design and process modeling during the execution phase, is missing. In this context the present work deals with this issue through a structured methodology that highlights the system sensitivities by decoupling process and product design, proposing an algorithm that uses empirical evaluation measures of manufacturing complexity.