Integrated Design for Assembly Approach Using Ant Colony Optimization Algorithm for Optimal Assembly Sequence Planning

Murali, Gunji Bala; Deepak, B. B. V. L.; Biswal, Bibhuti Bhusan; Khamari, Bijaya Kumar

doi:10.1007/978-981-10-8055-5_23

Cited by 7 publications

(4 citation statements)

References 16 publications

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“…reducing the number of parts. The integrated problem could be solved using optimization methods such as Ant Colony Optimization, considering directional changes as the fitness function [68]. On the other hand, the computational requirements associated with Constraint Satisfaction Problems dealing with grasp planning may quickly become intractable when number of operations increase.…”

Section: F Alleviating the Computational Burdenmentioning

confidence: 99%

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Industry 4.0 and Prospects of Circular Economy: A Survey of Robotic Assembly and Disassembly

Daneshmand¹,

Noroozi²,

Corneanu³

et al. 2021

Preprint

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Despite their contributions to the financial efficiency and environmental sustainability of industrial processes, robotic assembly and disassembly have been understudied in the existing literature. This is in contradiction to their importance in realizing the Fourth Industrial Revolution. More specifically, although most of the literature has extensively discussed how to optimally assemble or disassemble given products, the role of other factors has been overlooked. For example, the types of robots involved in implementing the sequence plans, which should ideally be taken into account throughout the whole chain consisting of design, assembly, disassembly and reassembly. Isolating the foregoing operations from the rest of the components of the relevant ecosystems may lead to erroneous inferences toward both the necessity and efficiency of the underlying procedures. In this paper we try to alleviate these shortcomings by comprehensively investigating the state-of-the-art in robotic assembly and disassembly. We consider and review various aspects of manufacturing and remanufacturing frameworks while particularly focusing on their desirability for supporting a circular economy.

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Section: F Alleviating the Computational Burdenmentioning

confidence: 99%

“…Assembling a product comprising of N parts typically consists of N − 1 steps. Reducing the number of parts by design improves efficiency and reduces costs [68]. Discrete elements may contribute to developing modular ultralight lattice structures, which facilitate the manufacturing and RA of elements.…”

Section: Facilitating Planning and Execution By Designmentioning

confidence: 99%

Industry 4.0 and Prospects of Circular Economy: A Survey of Robotic Assembly and Disassembly

Daneshmand¹,

Noroozi²,

Corneanu³

et al. 2021

Preprint

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“…In addition to the DFA concept, many other concepts have appeared to support assembly problems from the earlier stages of product life cycle (in the design phase) namely, the DFMA (Design For Manufacturing and Assembly) concept and the integrated approaches of design [11].…”

Section: Literature Reviewmentioning

confidence: 99%

An Artificial Intelligent based System to Automate Decision Making in Assembly Solution Design

Abadi¹,

Manssouri²,

Abadi³

2020

IJACSA

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Nowadays, competitiveness between industries has become very strong. Thus, industries are faced to serious challenges in terms of products qualities, time development and production cost. As assembly operations difficulties cause a big part of production problems, the integration of assembly selection since the earlier product life cycle phases has become a necessity for every company in order to survive. However, despite the large number of approaches that have been proposed in order to achieve this integration goal, many other problems are still present. It is in this context that a flexible and automated decision making system is proposed. It is based on ontologies and also on the Case Based Reasoning (CBR) and Rule Based Reasoning (RBR) concepts. Indeed, this system is an automation of the integrated DFMMA approach, in particular its assembly solution selection methodology. The developed system permits to designers avoiding the redundancy in the works by benefiting from their previous studies and their experience. In addition to that, it facilitates and automates the assembly solution selection even if the number of assembly alternatives is high. Finally, to illustrate the efficacy of the proposed system, a case of study is developed in the end of the work.

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“…Instead of using either soft computing techniques or knowledge-based methods alone to obtain the optimal assembly sequences, Gunji et al. 35 used Design For Assembly (DFA) concept with the soft computing techniques to generate the optimal assembly sequences. In this, the authors tire to reduce the number of levels of the assembly with the use of ACO algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal robotic assembly sequence planning using stability graph through stable assembly subset identification

Murali

Deepak

Raju³

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part C:

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Assembly sequence planning is one of the multi-model optimization problems, in which more than one objective function has to be optimized at a time to obtain the quality assembly sequence. Moreover obtaining the feasible sequences from the possible finite set of sequences is a difficult task as the assembly sequence planning problem is N-P hard combinatorial problem. To solve the assembly sequence planning problem, researchers have developed various techniques to obtain the optimum solution. The developed methodologies have many drawbacks like struck at local optima, poor performance, huge search space and many more. To overcome these difficulties, the current research work aims to use stability graph to generate stable assembly subsets for obtaining the optimum assembly sequences. In the proposed methodology, to reduce the search space and to obtain the quality assembly sequences, stability graph is considered. Moreover, the fitness of assembly subsets is evaluated according to the user weights at each level before proceeding to the higher levels. Due to this, the higher fitness value subsets are eliminated at each stage by which time of execution will reduce enormously. The proposed methodology has implemented on various industrial products and compared the results with the various well-known algorithms.

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Integrated Design for Assembly Approach Using Ant Colony Optimization Algorithm for Optimal Assembly Sequence Planning

Cited by 7 publications

References 16 publications

Industry 4.0 and Prospects of Circular Economy: A Survey of Robotic Assembly and Disassembly

Industry 4.0 and Prospects of Circular Economy: A Survey of Robotic Assembly and Disassembly

An Artificial Intelligent based System to Automate Decision Making in Assembly Solution Design

Optimal robotic assembly sequence planning using stability graph through stable assembly subset identification

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