Nizar Aifaoui

Disassembly sequence planning based on a genetic algorithm

Disassembly sequence planning is a relatively new subject and has only recently gained interest in the research literature. Disassembly simulations are important not only for improving product design, but also for maintaining an updated process plan, which becomes a tedious and complicated task given the complexity of today’s mechanisms. The crucial issue, in the generation of disassembly plans, is the rise in the amount of sequences, especially with the increase of the number of parts in the mechanism. For this reason, it is crucial to seek an optimal feasible method for the disassembly process. In this paper, an optimized disassembly process based on a genetic algorithm is proposed. The method takes into account several criteria such as maintainability of usury component, part volume, tools change and the change of disassembly directions. The results obtained demonstrate the satisfactory side of these criteria to identify a feasible disassembly sequence.

Toward an integrated CAD assembly sequence planning solution

Assembly sequence planning has drawn the attention of many researchers over the last years. Despite, the great development of CAD software in many aspects (simulation algorithms, interfaces, and ergonomics), automatic generation of assembly sequence planning from CAD assembly remains an issue to improve especially with the increasing complexity of industrial products. In this paper, an approach of assembly sequence planning generation from a CAD assembly model is presented. In order to generate feasible assembly sequence planning, the developed approach begins with the exploration of CAD assembly. Then, a collision analysis is performed to identify all possible obstacles during the components’ motion. An example of CAD assembly is presented in all sections of this paper in order to demonstrate the efficiency of the proposed approach.

Solution space reduction of disassembly sequences generated automatically via computer aids

To develop a simulation tool for automatic disassembly in computer aid design (CAD) environment two difficulties are found: the huge space of generated sequences and their feasibility especially in combinatory generation. This article deals with automatic sequence generation for selective disassembly of mechanical product. Starting from a CAD model a new appropriate connection tree of a target component is constructed. This tree aims at reducing space solution by eliminatory rules. The generation of sequence is based on reading of connection tree branches and eliminatory tests of feasibility. The feasibility is checked by updating the disassembly mobility of each sequence’s element. A case study is presented to prove the effectiveness of the proposed approach.

A disassembly Sequence Planning Approach for maintenance

In recent years, more and more research has been conducted in close collaboration with manufacturers to design robust and profitable dismantling systems. Thus, engineers and designers of new products have to consider constraints and disassembly specifications during the design phase of products not only in the context of the end of life but more precisely in the product life cycle. Consequently, optimization of disassembly process of complex products is essential in the case of preventive maintenance. In Fact, Disassembly Sequence Plan (DSP), which is among the combinatorial problems with hard constraints in practical engineering, becomes an NP-hard problem. In this research work, an automated DSP process based on a metaheuristic method named “Ant Colony Optimization” is developed. Beginning with a Computer Aided Design (CAD) model, a collision analysis is performed to identify all possible interferences during the components’ motion and then an interference matrix is generated to identify dynamically the disassembly parts and to ensure the feasibility of disassembly operations. The novelty of the developed approach is presented in the introduction of new criteria such as the maintainability of the usury component with several other criteria as volume, tools change and disassembly directions change. Finally, to highlight the performance of the developed approach, an implemented tool is developed and an industrial case is studied. The obtained results prove the satisfactory side of these criteria to identify a feasible DSP in a record time.

Dynamic Synthesis of a Multibody System: A Comparative Study Between Genetic Algorithm and Particle Swarm Optimization Techniques

This paper proposes a dynamic synthesis of a flexible multibody systems, mainly, a slider crank mechanism incorporating a flexible connecting rod. Differently to classical synthesis, the mechanism design variables are identified by means of the mechanism dynamic responses such as, the velocity and the acceleration of the slider, and the flexible connecting rod transversal deflection. A comparative study between two optimization techniques, the genetic algorithm (GA) and the Particle Swarm Optimization (PSO), has been established. The two approaches employ different strategies and computational effort to find a solution to a given objective function. Thus, we are interested in the comparison of their implementation. The comparative study asserts that the PSO technique is more suitable for the dynamic synthesis.

Assembly sequences plan generation using features simplification

Abstract The automatic generation of the assembly/disassembly plan is considered a topical problem in the computer-aided tools area. The main problem of the major proposed approaches is the excessive processing time to treat the whole assembly model. This paper proposes a simplification approach of CAD models to make the generation of assembly plan easy. The developed method begins by the elimination of connection elements to obtain a simplified assembly sequence. A case-based reasoning algorithm is, then, developed to insert the entire eliminated elements in the global assembly sequence plan. Two examples of CAD assembly are treated in order to compare and validate the obtained results.

A Disassembly Sequence Planning Approach Based on Particle Swarm Optimization

Recently, Disassembly Sequence Planning (DSP) plays an important role in the life cycle of mechanical products. Disassembly specification during the design phase of a product is considered as a great interest of engineers and designers. This paper presents an automated DSP based on Particle Swarm Optimization (PSO). First, the collision test is performed by the use of the interference test tool of the CAD software in order to identify all possible interferences during the components’ motion. Then interference matrices are generated to ensure the feasibility of disassembly operations. Next, a PSO algorithm, based on the regeneration of DSP, was performed to optimize the DSP using an objective function. Various criteria such as part volume, tools change, directions and maintainability of usury component are considered. Finally, to highlight the performance of the developed approach, an implemented tool is developed and an illustrative example is studied.

Solidworks—Matlab Coupling for Disassembly Plan Generation in a CAE Environment

Nowadays, mechanical products which respond to customer requirements become more and more complex. Concurrent engineering environment requires that various computer-aided tools be used concurrently for design, analysis, and validation of complex product. Computer-aided design (CAD) and computer-aided engineering (CAE) tools should have the capacity of integration or easy interoperability. However, many of them are often unconnected systems that are not intended for collaborative use. Engineering designers and analysts tend to use specific CAD software for design and other CAE software for analysis. Consequently, the triplet (Cost/Delay/Quality) of a complex product cannot be improved. In this paper, a disassembly plan (DP) generation based on a coupling between Solidworks and Matlab is detailed. Base on an encapsulation of parts into a subassemblies bloc, the proposed approach aims to automatically integrate the both softwares in a concurrent engineering context in order to identify and generate a feasible and optimal DP. A comparative example is presented in order to highlight the feasibility and efficiency of the proposed approach.

Assembly Sequence Generation Based on the CAD Model Simplification

At present, Computer-Aided tools are at the heart of the product development cycle. These tools can accelerate and make more efficient the design and simulation tasks. However, there is no commercial aid tool for the assistance in the assembly/disassembly tasks. In this context, many approaches and methods are proposed in which feasible assembly/disassembly sequences can be generated. Amongst the limitations of those approaches is the considerable processing time. In this paper, we propose an approach for the simplification of the product CAD model in order to generate Assembly Sequences (AS). The developed approach, which is automatic and integrated to CAD system, begins by the identification and the elimination of standard components (such as screws, nuts, keys, etc.) present in the model. Then a simplified AS is carried out using a collision analysis. Finally, the global AS is obtained by inserting the eliminated elements into the final AS using a case-based algorithm which contains a census of the different standard component types. This developed case-based algorithm allows, according to the type, the identification of the assembly direction and the chronological order of the eliminated standard component.

Disassembly Method for Early Stages of Design

Economical, useful and waste less time disassembly planning is the asset of recent research works. In spite of varied assembly and disassembly (A/D) approaches proposed in the last two decades, reducing the time of generation and optimization is still their major problem. In this paper a new approach of disassembly planning is proposed. Some criteria are early integrated in the sequence generation using a connection graph. The approach offers a reduced number of valid possibilities and allows an easy and fast optimization process. A case study is presented to prove the effectiveness of the proposed approach.