Titlebook: Optimisation of Robotic Disassembly for Remanufacturing; Yuanjun Laili,Yongjing Wang,Duc Truong Pham Book 2022 The Editor(s) (if applicabl

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Solutions for Robotic Disassembly Sequence Planning with Backup Actions,echniques use pre-determined robotic processes which cannot deal with unforeseen failed disassembly operations. This chapter models the completion rate of a disassembly plan and introduces the concept of backup actions. The aim of this strategy is to allow a disassembly robot to recover from failure

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Robotic Disassembly Sequence Re-planning,embly order and the direction of not only detachable components but also the removable subassemblies. The algorithm possesses the merits of both the original Bees Algorithm and greedy search. Although it is designed for complete disassembly, the local search operator can be modified to adapt to both

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Solutions for Mixed-Model Disassembly Line Balancing with Multi-robot Workstations,R and classic simple disassembly lines is the number of robots that can be allocated to each workstation. In MDLB-MR, a set of EOL products can be simultaneously disassembled and each product has its own set of precedence relations. The chapter compares the performance of different evolutionary algo

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Robotic Disassembly Sequence Re-planning, products (where the number of components is fewer than 200, which is about ten times the number in the case studies considered in this chapter). With more decision variables, the decision-making time may increase. The re-planning process will therefore become inefficient.

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Book 2022on two crucial optimisation problems in the areas of robotic disassembly through a group of unified mathematical models. The online and offline optimisation of the operational sequence to dismantle a product, for example, is represented with a list of conflicting objectives and constraints. It allow

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Modelling of Robotic Disassembly Sequence Planning,expected disassembly time and success rate of disassembly plans with uncertainties are formulated. The formulation reflects the possibility of failure in which disassembly may be terminated before all components are removed.

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Solutions for Mixed-Model Disassembly Line Balancing with Multi-robot Workstations,rithms (EAs) and concludes that the Problem-specific Bi-criterion EA (PBEA) outperforms the other EAs tested.Furthermore, a combination of non-Pareto-based EAs with the Pareto selection criterion can be effective at solving MDLB-MR problems.

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