Unit sized transfer batch scheduling in an automated two-machine flow-line cell with one transport agent

Çetinkaya, Ferda Can

doi:10.1007/s00170-004-2493-9

Cited by 10 publications

(3 citation statements)

References 16 publications

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“…Vickson (1995) [40] employed a fast polynomial algorithm to solve flow shop multi-batch problems, considering the job setting time and sub-batch transfer time. Etinkaya (2006) [41] extended this by incorporating units and independent settings to optimize batch problems in dual-machine process workshops, termed batch flow integration optimization. Despite these advancements, such research mainly focuses on small-scale device environments, with limited exploration of multi-flow integration at the production line level.…”

Section: System Flow Perspectivementioning

confidence: 99%

Synergy Management of a Complex Industrial Production System from the Perspective of Flow Structure

Song,

He,

Jiang

et al. 2023

Systems

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Modern industry has become very complex and requires an equally complex engineering technology system, which includes resource utilization, energy conversion, product research and development, technological innovation, environmental protection and industrial ecology, and other aspects of the system. Continued development of large-scale, streamlined, and continuous processes is critical; however, there are also problems such as data redundancy, overcapacity, redundant construction, and waste of resources. Based on the system synergy theory, this paper introduces the system analysis method from the perspective of flow structure, with the purpose of solving the management defects of complex industrial production systems. First, we analyze the complex industrial production system as a collaborative structure of three subsystems: material flow, energy flow, and information flow. The following concepts are clarified: “material flow is the main body, energy flow is attached to and drives material flow, material flow and energy flow generate information flow, and information flow reversely drives material flow and energy flow”. Secondly, the collaborative evolution process of the complex industrial production system is divided into three periods, which are the generation period, the stalemate period, and the maturity period, and a synergy degree evaluation model is established, which considers the Theil index and subsystem gray correlation method, and extends the dynamic differential equation model of three-stage collaborative evolution. Subsequently, we used MATLAB numerical simulation to demonstrate that the collaborative evolution of production systems is related to four aspects. They are the self-organizing ability of the system, the dominant role of order parameters, the competition and cooperation between order parameters, and whether mutations can become order parameters. At the same time, it was also found that it is basically independent of other factors, such as attenuation inertia. Then, the self-organizing map network (SOM) algorithm was used for the rapid identification of mutation data. Finally, we use the empirical research of SG enterprises to show that their production level and management system are advanced, but they were in a non-cooperative state from 2014 to 2021. In 2022, they had the basic conditions and trends to enter the synergistic generation period, and a synergistic management model is required. At the end of the article, we give a collaborative management method for complex industrial enterprises with a good management foundation. These include the management mechanism based on flow structure collaboration and the management path based on collaborative evolution. Of course, the management countermeasures given in this study are also applicable to other complex process-based industrial enterprises.

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Section: System Flow Perspectivementioning

confidence: 99%

Synergy Management of a Complex Industrial Production System from the Perspective of Flow Structure

Song,

He,

Jiang

et al. 2023

Systems

View full text Add to dashboard Cite

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“…It was -763-Journal of Industrial Engineering and Management -http://dx.doi.org/10.3926/jiem.553 presented some closed form solutions for continuous sublots and a fast polynominally bounded search algorithm for discrete sublots. Other papers proposed the use of removal times (Cetinkaya, 1994), of no-wait condition (Sriskandarajah & Wagneur, 1999) or even allowing interleaving (Cetinkaya, 2006).…”

Section: Problemmentioning

confidence: 99%

A review of lot streaming in a flow shop environment with makespan criteria

Gómez-Gasquet

Segura-Andrés

Romano

2013

JIEM

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Abstract:Purpose: This paper reviews current literature and contributes a set of findings that capture the current state-of-the-art of the topic of lot streaming in a flow-shop.Design/methodology/approach: A literature review to capture, classify and summarize the main body of knowledge on lot streaming in a flow-shop with makespan criteria and, translate this into a form that is readily accessible to researchers and practitioners in the more mainstream production scheduling community. Findings:The existing knowledge base is somewhat fragmented. This is a relatively unexplored topic within mainstream operations management research and one which could provide rich opportunities for further exploration.Originality/value: This paper sets out to review current literature, from an advanced production scheduling perspective, and contributes a set of findings that capture the current state-of-the-art of this topic.

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“…Flow Shop scheduling problem (FSP) can be described as there are n jobs that they must go through m machines with the same processes, and one of its main objectives is to find out the jobs arrangement which makes the maximum completion time to be shortest. A lot of researches are the assumption of infinite buffer space between machines [1]. But there are numerous situations in which discontinuous processing is not allowed, such as water supply and drainage engineering, steel making etc.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Intelligence Algorithm for No-Wait Flow Shop Scheduling

Wang

Rao

Tang

2013

AMR

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Constraint simplified mixed integer programming model was presented based on time transformation mechanism of no-wait flow shop. And a hybrid intelligence algorithm which combines the advantages of heuristic algorithm and neighborhood search algorithm was proposed. The initial population was generated by Johnson method, NEH method, Rajendran Method, Dannerbring method, and heuristic rules. The crossover and mutation operators in each generation were introduce neighborhood search (NS) and tabu search (TS). And the optimal individual was reserved in each generation. We compared the new hybrid intelligence algorithm (abbreviation H&NSGA ) with the algorithm blending heuristic and GA (NSGA), the algorithm blending neighborhood search and GA (HAGA), GA with the optimal individual reserved, and results show that the results and stability of solutions based on H&NSGA are better than the other three algorithms.

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Unit sized transfer batch scheduling in an automated two-machine flow-line cell with one transport agent

Cited by 10 publications

References 16 publications

Synergy Management of a Complex Industrial Production System from the Perspective of Flow Structure

Synergy Management of a Complex Industrial Production System from the Perspective of Flow Structure

A review of lot streaming in a flow shop environment with makespan criteria

A Hybrid Intelligence Algorithm for No-Wait Flow Shop Scheduling

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