Propagation path optimization of product attribute design changes based on Petri Net fusion ant colony algorithm

Abstract

An effective and controlled design change in product attributes can improve product quality, promote product innovation, and meet customer demands. During design changes, the links among product attributes are intricate. A change in the design of one attribute may lead to a series of changes in other attributes, which result in the change propagation as well as the re-planning and re-design of the propagation path. Therefore, an Expanded Petri Net (EPN) model is constructed to describe the propagation relationship of product attribute design change in this paper. Firstly, the attribute change propagation rules are established based on change propagation impact values. Secondly, to optimize the dynamic scheme of change propagation path, the ant colony path optimization algorithm is integrated into the Extended Petri Net model (Expanded Petri Ant Colony Optimization Algorithm, EP-ACOA). In addition, the constraint test factor and the upper and lower limits of pheromone values are introduced into the algorithm to ensure the whole network traversal of the change propagation path and accelerate the solving speed of the model. Finally, taking the attribute design change of Langevin piezoelectric transducer in an ultrasonic knife as an example, the Petri Net fusion ant colony algorithm was verified to be able to quickly and effectively provide the optimal solution or approximate optimal solution to the propagation path problem of product attribute design changes.