Blow Molding Machine Assembly Task Planning Method Based on Artificial Bee Colony Algorithm

• 1、Key Laboratory of Computer Integrated Manufacturing System of Guangdong Province,Guangdong University of Technology, Guangzhou 510006

Abstract： How to improve the production operation efficiency of assembly workshop is the core of production planning system in blow molding machine manufacturing enterprises. Assembly planning of blow molding machines is a kind of complex jobs assignment problems, which consists of two stages: components assembly and machines installing, and the learning effect is obvious in batch assembly of similar types of machines. Firstly, considering the characteristics of assembly processing of blow molding machine, an assembly jobs partitioning method that taking into account the association in components assembly and in the order of components installing is proposed. Secondly, the optimization model is established to minimize the weighted tardiness quantity, and its outstanding characteristic is that by changing the weight coefficients to consider the real demands of orders batch delivery. Then an improved artificial bee colony algorithm is constructed to solve the problem. Finally, cases are studied according to real-life enterprise, and the practicability and adaptability of the proposed method are verified.

Keywords： assembly operations plan；artificial bee colony algorithm；weighted tardiness；manual operation system；learning effect