Design of machine cell in cellular manufacturing systems using PSO approach

Adinarayanan, A.; Dinesh, S.; Balaji, Ds.; Umanath, K.

doi:10.1016/j.matpr.2021.02.472

Cited by 3 publications

(2 citation statements)

References 5 publications

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“…The purpose of their model is to minimize the travel distance of the parts. They used the particle swarm optimization (PSO) algorithm to solve the model [31]. Saraçoğlu et al, discussed a three-level solution method for a parallel multi-stage, multi-product cell production company.…”

Section: Cell Production Systemmentioning

confidence: 99%

Cell Production System Design: A Literature Review

Ghahremani-Nahr

Bathaee

Mazloumzadeh

et al. 2021

IJIMES

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In a cell production system, a number of machines that differ in function are housed in the same cell. The task of these cells is to complete operations on similar parts that are in the same group. Determining the family of machine parts and cells is one of the major design problems of production cells. Cell production system design methods include clustering, graph theory, artificial intelligence, meta-heuristic, simulation, mathematical programming. This article discusses the operation of methods and research in the field of cell production system design. Methodology:To examine these methods, from 187 articles published in this field by authoritative scientific sources, based on the year of publication and the number of restrictions considered and close to reality, which are searched using the keywords of these restrictions and among them articles Various aspects of production and design problems, such as considering machine costs and cell size and process routing, have been selected simultaneously.Findings: Finally, the distribution diagram of the use of these methods and the limitations considered by their researchers, shows the use and efficiency of each of these methods. By examining them, more efficient and efficient design fields of this type of production system can be identified.Originality/Value: In this article, the literature on cell production system from 1972 to 2021 has been reviewed.

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Section: Cell Production Systemmentioning

confidence: 99%

Cell Production System Design: A Literature Review

Ghahremani-Nahr

Bathaee

Mazloumzadeh

et al. 2021

IJIMES

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“…One of the key elements that determine an industry's productivity is layout design. Industries have long employed functional layouts, but in an effort to boost production, modern layouts are gradually replacing them [1].…”

Section: Introductionmentioning

confidence: 99%

Cell Formation and Intra-Cell Optimal Machine Location in CMS: A Novel Genetic Algorithm (GA) Based on Machine Encoding

Wu,

Li,

Rizwan

et al. 2023

Applied Sciences

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Manufacturing industries are in a constant state of competition to attract customers in a variety of methods. Group Technology (GT) is a term used in the field of manufacturing for grouping similar elements based on their similarities in production and design. Cellular manufacturing (CM) is an application of Group Technology (GT) that has gained widespread traction in Small- and Medium-Sized Enterprises (SMEs) during the recent years in order to increase the production floor’s efficiency and output. A Cell Formation consists of grouping identical machinery and assigning them on similar functions. There are three main decisions involved in designing the Cellular Manufacturing System (CMS): Group Scheduling (GS), Group Layout (GL), and Cell Formation (CF). In this study, the primary challenge associated with the CMS is not only the formation of cells but also the optimal placement of machinery within each cell. This paper’s objectives are therefore twofold: the formation of cells and the optimal placement of machinery within cells. For the purpose of Cell Formation and the position of machinery within the cell, a Genetic Algorithm (GA) and Encoding Scheme are employed. In this study, a Genetic Algorithm is used to classify machines and parts, while MATLAB is used for the simulation and encoding scheme. To evaluate the developed objective function and GA, a layout problem of medium size is solved. Results indicate that the proposed strategy is effective for resolving CMS issues and increasing productivity by 8.85%.

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Joint decision-making of virtual module formation and scheduling considering queuing time

Mei

Liu

2023

Data Science and Management

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Design of machine cell in cellular manufacturing systems using PSO approach

Cited by 3 publications

References 5 publications

Cell Production System Design: A Literature Review

Cell Production System Design: A Literature Review

Cell Formation and Intra-Cell Optimal Machine Location in CMS: A Novel Genetic Algorithm (GA) Based on Machine Encoding

Joint decision-making of virtual module formation and scheduling considering queuing time

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