Reconfigurable manufacturing systems from an optimisation perspective: a focused review of literature

Yelles-Chaouche, Abdelkrim R.; Gurevsky, Evgeny; Brahimi, Nadjib; Dolgui, Alexandre

doi:10.1080/00207543.2020.1813913

Cited by 113 publications

(23 citation statements)

References 89 publications

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“…Constraints (7) impose that the demand for any product must be met in any period by performing all of its assembly operations. Since it is allowed to perform the same assembly operation in different cells and by using different side modules, the sum of the number of times an assembly operation is performed by any of these side modules must be equal to the period's demand.…”

Section: Iqp Modelmentioning

confidence: 99%

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Aggregate Planning for Multi-product Assembly Lines with Reconfigurable Cells

Uzunosmanoglu

Raa

Limère

et al. 2021

IFIP Advances in Information and Communication Technology

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This paper deals with aggregate planning of Reconfigurable Assembly Lines (RAL). The assembly line considered in this paper consists of hexagonal cells. These have multiple slots where processing modules can be inserted to perform certain operations. In addition, each cell has a single central slot where a central module can be inserted for inter-cellular and intra-cellular transportation of parts. Multiple products with different assembly sequences must be handled over multiple planning periods. An Integer Quadratic Programming (IQP) model is proposed to solve the following problems simultaneously: (i) assigning processing modules and a central module to the cells; (ii) installation of the cells and conveyors between the cells; and (iii) routing products, ensuring that availability of the resources is not exceeded. The assembly line should be reconfigured over time to adapt to possible product functionality and demand changes at minimum reconfiguration, operational and material handling costs while ensuring the demand is met within each period. The IQP model is implemented and solved for an illustrative problem and its extensions using Gurobi.

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Section: Iqp Modelmentioning

confidence: 99%

“…Other aspects are often considered as well, such as reconfigurability, operational capability, and reliability [6]. An elaborate overview of the relevant literature is found in [7].…”

Section: Introductionmentioning

confidence: 99%

Aggregate Planning for Multi-product Assembly Lines with Reconfigurable Cells

Uzunosmanoglu

Raa

Limère

et al. 2021

IFIP Advances in Information and Communication Technology

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“…It can quickly reconfigure its structure, hardware, and software components in a cost-effective manner. Therefore, it is well capable of adjusting to the new functionality and capacity requirements [8] , [9] . Reconfiguration in a physical form can be achieved at the system level (e.g., adding or removing a machine, or changing the layout of machines) or at the machine level (e.g., changing or modifying modules of a machine) [10] .…”

Section: Introductionmentioning

confidence: 99%

Workforce planning and production scheduling in a reconfigurable manufacturing system facing the COVID-19 pandemic

Vahedi-Nouri¹,

Tavakkoli–Moghaddam²,

Hanzálek³

et al. 2022

Journal of Manufacturing Systems

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“…In order to achieve this desired level of flexibility, six special design characteristics have been defined in literature [1] for a product or process to be termed as 'reconfigurable'. These characteristics focus on adaptability of a manufacturing system at machine and process level that can be upgraded in the system with product development and technological changes [2]. Numerous researches in the area of reconfigurable machine tools (RMT) are available that focus on optimization of machine features that may provide desired level of flexibility to build a part family without redundancy [3,4].…”

Section: Introductionmentioning

confidence: 99%

Meta-Heuristic Approach for the Development of Alternative Process Plans in a Reconfigurable Production Environment

Khan

Ghafoor

Zahid³

2021

IEEE Access

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The need for automated production plans has evolved over the years due to internal and external drivers like developed products, new enhanced processes and machinery. Reconfigurable manufacturing systems focus on such needs at both production and process planning level. The age of Industry 4.0 focused on mass customization requires computer aided planning techniques that are able to cope with custom changes in products and explores intelligent algorithms for efficient scheduling solutions to reduce lead time. This problem has been categorized as NP-Hard in literature and is addressed by providing intelligent heuristics that focus on reducing machining time of the products at hand. However, as 70% of the lead time is consumed in non-value added tasks, it is fundamental to provide modular solutions that can reduce this time and handle part variety. To address the subject, this paper focuses on the generation of automated process plans for a single machine problem while focusing on reducing time lead time. Two evolutionary algorithms (EAs) have been proposed and compared to answer complex problem of process planning. A modified genetic algorithm (GA) has been proposed in addition to cuckoo search (CS) heuristic for this discrete problem. On testing with selected benchmark part ANC101, significant improvement was seen in terms of convergence with proposed EAs. Moreover, a novel Precedence Group Algorithm (PGA) is proposed to generate quality input for heuristics. The algorithm produces a set of initial population which significantly effects the performance of proposed heuristics. For the discrete constrained process planning problem, GA outperforms CS providing 10% more feasible scheduling options and three times lesser run time as compared to CS. The proposed technique is flexible and responsive in order to accommodate part variety, a necessary requirement for reconfigurable systems.

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Reconfigurable manufacturing systems from an optimisation perspective: a focused review of literature

Cited by 113 publications

References 89 publications

Aggregate Planning for Multi-product Assembly Lines with Reconfigurable Cells

Aggregate Planning for Multi-product Assembly Lines with Reconfigurable Cells

Workforce planning and production scheduling in a reconfigurable manufacturing system facing the COVID-19 pandemic

Meta-Heuristic Approach for the Development of Alternative Process Plans in a Reconfigurable Production Environment

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