Two-stage flow-shop scheduling problem with non-identical second stage assembly machines

Navaei, Javad; Ghomi, S. M. T. Fatemi; Jolai, Fariborz; Shiraqai, M. E.; Hidaji, Hooman

doi:10.1007/s00170-013-5187-3

Cited by 22 publications

(4 citation statements)

References 25 publications

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“…This model is at first a non-linear mathematical model and is subsequently converted to a mixed integer linear programming (MILP) to find exact solutions using general algebraic modelling system (GAMS) optimisation software (Mozdgir et al 2013;Navaei et al 2013). The notation used in this model can be structured into two parameter and variable groups.…”

Section: Mathematical Modelmentioning

confidence: 99%

Grouping and sequencing product variants based on setup similarity

Navaei

ElMaraghy

2016

International Journal of Computer Integrated Manufacturing

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In some flow shop environments, set-up times between product variants have an important role and are considered more significant than processing times. Therefore, optimal sequence of various product variants is based on improving machine utilisation. A flow shop environment which addresses the set-up criterion where bypassing is not permitted is considered in this paper. A mathematical model is developed and solved using GAMS optimisation software. The non-linear model is then linearised to find exact solutions. A new policy for sequencing product variants is proposed and compared to the exact solutions obtained from GAMS. This sequencing policy capitalises on the commonality between product variants to increase sequencing efficiency. The developed sequencing policy is simple and easy to apply in manufacturing environments. A case study in the label stickers making industry is used for demonstration and validation. Numerical results indicate that the proposed sequencing policy is capable of finding good, and exact solutions in some cases, in less than one second for all studied small, medium and large problem sizes. The solutions obtained using the proposed sequencing policy has a total average of 1.2% relative error which is quite comparable with the solutions obtained using GAMS.

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Section: Mathematical Modelmentioning

confidence: 99%

Grouping and sequencing product variants based on setup similarity

Navaei

ElMaraghy

2016

International Journal of Computer Integrated Manufacturing

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“…Multi-objective machine scheduling in the custom furniture industry based on evolutionary approach together with a ANN is presented in (Vidal et al, 2011). A hybrid simulated annealing method was used to solve the two-stage assembly of bedroom furniture problem with multiple non-identical assembly machines in (Navaei et al, 2013).…”

Section: Artificial Intelligence For Design and Manufacturingmentioning

confidence: 99%

Technology enablers for the implementation of Industry 4.0 to traditional manufacturing sectors: A review

Jimeno-Morenilla

Azariadis

Molina-Carmona

et al. 2021

Computers in Industry

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The traditional manufacturing sectors (footwear, textiles and clothing, furniture and toys, among others) are based on small and medium enterprises with limited capacity on investing in modern production technologies. Although these sectors rely heavily on product customization and short manufacturing cycles, they are still not able to take full advantage of the fourth industrial revolution. Industry 4.0 surfaced to address the current challenges of shorter product life-cycles, highly customized products and stiff global competition. The new manufacturing paradigm supports the development of modular factory structures within a computerized Internet of Things environment. With Industry 4.0, rigid planning and production processes can be revolutionized. However, the computerization of manufacturing has a high degree of complexity and its implementation tends to be expensive, which goes against the reality of SMEs that power the traditional sectors. This paper reviews the main scientific-technological advances that have been developed in recent years in traditional sectors with the aim of facilitating the transition to the new industry standard.

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“…This case -depicted in Figure 1c-has been addressed for different objectives. The DP m → Rm||C max problem has been modelled as an MILP by Navaei et al (2013), who also propose a metaheuristic. The DP m → P m|ST sd |C max problem is addressed by Zhang et al (2010).…”

Section: Parallel Machines In the Assembly Stage: Dp M → P M/rm/qm Lamentioning

confidence: 99%

Deterministic assembly scheduling problems: A review and classification of concurrent-type scheduling models and solution procedures

Framiñán

2019

European Journal of Operational Research

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Many activities in industry and services require the scheduling of tasks that can be concurrently executed, the most clear example being perhaps the assembly of products carried out in manufacturing. Although numerous scientific contributions have been produced on this area over the last decades, the wide extension of the problems covered and the lack of a unified approach have lead to a situation where the state of the art in the field is unclear, which in turn hinders new research and makes translating the scientific knowledge into practice difficult. In this paper we propose a unified notation for assembly scheduling models that encompass all concurrent-type scheduling problems. Using this notation, the existing contributions are reviewed and classified into a single framework, so a comprehensive, unified picture of the field is obtained. In addition, a number of conclusions regarding the state of the art in the topic are presented, as well as some opportunities for future research.

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Two-stage flow-shop scheduling problem with non-identical second stage assembly machines

Cited by 22 publications

References 25 publications

Grouping and sequencing product variants based on setup similarity

Grouping and sequencing product variants based on setup similarity

Technology enablers for the implementation of Industry 4.0 to traditional manufacturing sectors: A review

Deterministic assembly scheduling problems: A review and classification of concurrent-type scheduling models and solution procedures

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