Smart Cyber-Physical Manufacturing: Extended and Real-Time Optimization of Logistics Resources in Matrix Production

Bányai, Ágota; Illés, Béla; Glistau, Elke; Machado, Norge Isaías Coello; Tamás, Péter; Manzoor, Faiza; Bányai, Tamás

doi:10.3390/app9071287

Cited by 44 publications

(26 citation statements)

References 108 publications

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“…Logistics processes and work cycles of autonomous operating resources are not considered here. In cooperation with the chair of the authors, the operational delivery process of matrix production is described in [18] using a mathematical model, including extended and real-time optimization under routing, allocation and planning aspects. Heuristics are used to find the best possible solution.…”

Section: Literature Review and Related Workmentioning

confidence: 99%

Matrix Production Systems - Requirements and Influences on Logistics Planning for Decentralized Production Structures

Schmidtke¹,

Rettmann²,

Behrendt³

2021

Proceedings of the Annual Hawaii International Conference on System Sciences

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In the context of the digital transformation of industry and within the framework of Industrie 4.0 and Factory Planning 4.0, new production-organizational principles with decentralized, modular and freely linked production cells are increasingly being discussed. The principle of matrix production with categorized and standardized workstations offers an extremely versatile production environment. It can be used to meet the challenge of an increasing number of product variants in variable quantities. This concept is predominantly considered from a theoretical point of view. Therefore, many aspects regarding the planning and operation of such systems are still up to debate. With the focus on logistics processes, this paper describes the requirements for such flexible, dynamic routing and self-organizing resources in material supply. Furthermore, they are investigated in a generic, conceptual model for a matrix production. Based on a reference scenario from the automotive industry, classical parameters from logistics and production organization are taken up. The influences with regard to decentralized material supply concepts and structural differences to flow production are shown by the results of simulation experiments with the generic model.

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Section: Literature Review and Related Workmentioning

confidence: 99%

Matrix Production Systems - Requirements and Influences on Logistics Planning for Decentralized Production Structures

Schmidtke¹,

Rettmann²,

Behrendt³

2021

Proceedings of the Annual Hawaii International Conference on System Sciences

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show abstract

“…The authors of [ 29 ] proposed a framework for SSF based on a cyber-physical system and agent model of manufacturing resources. Masoud et al [ 30 ] discussed the effect of real-time data on the efficiency of a production logistics system. Azadian et al [ 31 ] studied the operation problem of combining production scheduling with transportation planning to improve the efficiency of operation.…”

Section: Related Workmentioning

confidence: 99%

Real-Time Production and Logistics Self-Adaption Scheduling Based on Information Entropy Theory

Yang

Cao

et al. 2020

Sensors

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In recent years, the individualized demand of customers brings small batches and diversification of orders towards enterprises. The application of enabling technologies in the factory, such as the industrial Internet of things (IIoT) and cloud manufacturing (CMfg), enhances the ability of customer requirement automatic elicitation and the manufacturing process control. The job shop scheduling problem with a random job arrival time dramatically increases the difficulty in process management. Thus, how to collaboratively schedule the production and logistics resources in the shop floor is very challenging, and it has a fundamental and practical significance of achieving the competitiveness for an enterprise. To address this issue, the real-time model of production and logistics resources is built firstly. Then, the task entropy model is built based on the task information. Finally, the real-time self-adaption collaboration of production and logistics resources is realized. The proposed algorithm is carried out based on a practical case to evaluate its effectiveness. Experimental results show that our proposed algorithm outperforms three existing algorithms.

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“…[29] proposed a framework for SFF based on a cyber-physical system and agent model of manufacturing resources. Masoud et al [30] discussesed the effect of real-time data on the efficiency of production logistics system. Azadian et al [31] studied the operation problem of combining production scheduling with transportation planning to improve the efficiency of operation.…”

Section: Rlated Workmentioning

confidence: 99%

Real-time Production and Logistics Self-adaption Scheduling based on Information Entropy Theory

Yang

Cao

et al. 2020

Preprint

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In recent years, the individualized demand of customers brings small batches and diversification of orders towards enterprises. The application of enabling technologies in factory, such as the Industrial Internet of Things (IIoT) and Cloud Manufacturing (CMfg), enhances the ability of customer requirement automatic elicitation and the manufacturing process control. The job shop scheduling problem with random job arrival time dramatically increases the difficulty in process management. Thus, how to collaboratively schedule the production and logistics resources in the shop floor is very challenging, and it has a fundamental and practical significance of achieving the competitiveness for an enterprise. To address this issue, the real-time model of production and logistics resources is built firstly. Then, the task entropy model is built based on the task information. Finally, the real-time self-adaption collaboration of production and logistics resources is realized. The proposed algorithm is carried out based on a practical case to evaluate its effectiveness. Experimental results show that our proposed algorithm outperforms three existing algorithms.

show abstract

Smart Cyber-Physical Manufacturing: Extended and Real-Time Optimization of Logistics Resources in Matrix Production

Cited by 44 publications

References 108 publications

Matrix Production Systems - Requirements and Influences on Logistics Planning for Decentralized Production Structures

Matrix Production Systems - Requirements and Influences on Logistics Planning for Decentralized Production Structures

Real-Time Production and Logistics Self-Adaption Scheduling Based on Information Entropy Theory

Real-time Production and Logistics Self-adaption Scheduling based on Information Entropy Theory

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