Research On Disassembly Process Modeling And Planning For Electromechanical Product

The research on disassembly process planning for electromechanical product is a necessary part of product's design for disassembly & recycling, which can envaluate the product's green characteristic and enhance the integrative benefit in practical disassembly process. The disassembly process planning has become the core of product's design for disassembly & recycling.In mathematics, the Disassembly Sequence Planning (DSP) is a NP-Complete problem. With the increasing of complexity of products, it is very difficult to find out proper disassembly sequence solution. The work presented in this proposal is to seek a method which, based on an appropriate graph model, have the better searching strategy and could solve the DSP problem with a high efficiency.The main contents are as following:(1) Disassembly Hierarchy Information Graph (DHIG) is presented. Based on this graph model, the solution space of product's disassembly sequences is mapped onto an executable and simple graph space. Namely, the DSP problem is transformed into a problem of searching optimum path in the directed and weighted graph. In technology, the process of fulfilling DHIG is a process collecting relevant product's data & information for disassembly sequences planning. In this process, determination of constraint relations between components is the most important, which is vital to disassembly feasibility of nodes in DHIG. A Disassembly Precedence Restriction Matrix (DPRM) extracting system is designed and developed based on 3 dimension CAD platforms.(2) An Ant Colony Optimization (ACO) algorithm based on the graph is applied to realize the search and optimization for disassembly sequence which is symbolized as a path on DHIG. And different from traditional methods, this method combines the fulfilling process of DHIG with searching process for optimum path, which make a solid base for applying this method into engineering. In the process of disassembly sequence planning, there is always non-balanced competition between nodes. Aiming to this property, transition probabilities and pheromone update rule are improved, which enhance the efficiency of ACO. The characteristics of the algorithm are discussed and the comparisons to other intelligent disassembly optimization algorithms are analyzed.(3) Toward the products which have more parts, the method based on grey-clustering for subassembly identification is presented to effectively reduce the complexity of DHIG and further improve the efficiency of disassembly process modeling and planning.(4) Based on the ACO algorithm associated with DHIG model for disassembly sequences planning, a synthetical evaluating method for little disassembly scheme searched by ant colony is researched, which calculates the weight vectors according to the information entropy.(5) Based on the rough theory, an expert knowledge extraction approach about the component integration is studied, which can extend the design knowledge base step by step.(6) According to the proposed basic approaches, a prototype system of disassembly process planning based on ACO is designed and developed. Meanwhile, several technical issues about CAD system's secondary development, which involved in the system, are studied.