Generating disassembly tasks for selective disassembly using ontology-based disassembly knowledge representation

Abstract

Purpose This paper aims to develop methods for generating disassembly tasks for selective disassembly. The disassembly task contains the disassembly information, namely, disassembly direction, disassembly tool and selective disassembly sequence. Design/methodology/approach Ontology is adopted to represent the product, and ontology rules are used to represent the disassembly knowledge. A product ontology model (POM) is introduced on the basis of material, connection matrix and interference matrix. Two types of disassembly knowledge are taken into account, one is the disassembly knowledge of disassembly tool selection and the other is the disassembly knowledge of special connections. Based on the POM and the disassembly knowledge, decision support methods are designed to generate disassembly tasks. Findings A centrifugal pump is used to demonstrate the proposed methods, and the result shows that the methods work well. Research limitations/implications The methods developed in this study are fundamental approaches. The ontology and the ontology rules can be extended with more disassembly knowledge. Originality/value The main contribution of this research is the development of methods for representing disassembly knowledge based on ontology rules and the decision support methods for generating disassembly tasks.

Automatically generating assembly sequences with an ontology-based approach

“…Qiao et al (2018) proposed a geometry-enhanced ontology model and reasoning framework. Jiang et al (2018) constructed ontology to describe product information. The disassembly tool and sequence are obtained by decision support methods of design and reasoning.…”

“…The ontology-based approach centers on the semantic model of assembly experience and knowledge (Jiang et al , 2018; Chen et al , 2016b). Unlike pure mathematics methods, ontology-based hybrid approach has the ability to explicitly represent data semantics, and thus it can effectively describe assembly experience.…”

“…Compared with the knowledge-based methods: The presented ontology method is one of the knowledge-based methods and has an advantage in semantic representation. Qiao et al (2018) and Jiang et al (2018) use ontology to describe assembly knowledge. Based on assembly knowledge, a feasible assembly sequence is generated by rules, inference units and algorithms.…”

“…A centrifugal pump is taken as an instance of Jiang et al (2018), which contains 26 parts and produces a disassembly scheme (which can be sorted into 1,356 assembly sequences) through the design of algorithm. This paper generates 112 assembly sequences.…”

Disassembly sequence planning using a fast and effective precedence-based disassembly subset-generation method

“…8 Zhang and Zhang, 9 Guo et al, 10 and Song et al 11 used the cooperative disassembly hierarchical tree generated using a disassembly hybrid graph model (DHGM) to enhance the exploitation capacity of the branch-and-bound algorithm for the cooperative DSP problem. Jiang et al 12 introduced a product ontology model for generating disassembly tasks for selective disassembly, which takes disassembly tool selection and special connections into consideration. Bahubalendruni and Biswal 13 proposed an assembly model considering four basic predicates, namely, liaison predicate, geometrical feasibility, mechanical feasibility, and stability.…”