An Optimization Approach To Product Development Process Based On Design Structure Matrix

Enterprises must develop their new products with high quality and low prices within a shorter time due to economic globalization and fierce market competition. At the same time, more and more people take cognizance of the importance of product development process. Up to now, many optimization theories and methods of product development process have been proposed. Among these methods, design structure matrix (DSM) presented by American scholar Steward is a representative one. Design structure matrix offers matrix form to describe and analyze product development process in order to reduce the complexity of process and minimize the iterative trial-and-error process, and make the whole development process more systematic, logical and rational. In addition, design structure matrix method has been proven by a number of researchers as a useful tool in optimization and management of product development process.Using the relevant theoretical research achievement for references, the design structure matrix is deeply researched in this dissertation, in which artificial immune network system and feedback control theory are introduced. The applications of design structure matrix in complex product design and development are also discussed.Firstly, the method of task overlapping based on multiple input and output is studied. For overlapping instances among sequential tasks existing in concurrent product development process, the model to overlap product development with rework and iteration is presented based on both information evolution of upstream task and information sensitivity of downstream task. And then, it is expanded to apply to product development process with multiple input and output using design structure matrix. Furthermore, some important parameters such as information evolution and sensitivity in it are discussed and impacts on overlapping caused by them are also revealed. The result shows that there possibly exist potential risks using overlapping strategy.Secondly, the method for solving coupled task set based on resource leveling is investigated. The parallel iteration model based on work transformation matrix (WTM) has not yet been fully considering the specific resource constraints, and it is difficult for product development process to carry out effective quantitative analysis. In view of this point, a model for solving coupled task set based on resource leveling strategy is proposed in order to reduce the unequal allocation of resources caused by idle resources, thereby it can efficiently improve the resource utilization and shorten the iteration time of product development. Furthermore, the genetic algorithm (GA) is applied to the proposed model for searching for the optimal solution.Thirdly, the method of analysis of design iteration based on feedback control theory in a dynamic environment is discussed. The uncertain factors such as task durations, output branches of tasks and resource allocations, existing in product development, are analyzed and their impacts on development process are also discussed. A control and monitoring matrix is introduced to timely adjust process based on feedback control theory. In doing so, on the one hand, the iteration process is able to be completed within the desired lead time; on the other hand, the iteration process can be monitored and controlled.Finally, the method for solving multi-mode resource constrained multi-project scheduling problem based on artificial immune network algorithm is explored. Because there are fewer researches on multi-mode and multi-project scheduling problem, we take it as an object of study. Through analysis, we can easily find that this problem has an obvious multimodal characteristic. Artificial immune network algorithm specially designed for multimodal function optimization proposed by Castro and Timmis has been demonstrated to have powerful multimodal searching ability as well as good stabilization, which includes both local searching and global searching strategy. So, it is very suitable to solve multi-mode and multi-project scheduling problem. This proposed method simplifies information constraints among tasks based on design structure matrix. And then, task scheduling orders are set up based on priority of resource competition using heuristic rules. Operations including clonal selection, negative selection and network suppression are used to realize the local searching and global searching which will assure that the algorithm has a powerful searching ability and also avoid the possible combinatorial explosion.In addition, using the methods mentioned above, the design and development of portal crane is successfully accomplished. The case study indicates that the proposed methods are feasible and effective.