Cyclic scheduling of flexible mixed model assembly lines with parallel stations

Öztürk, Cemalettin; Tunalı, Semra; Hnich, Brahim; Örnek, Mustafa Arslan

doi:10.1016/j.jmsy.2015.05.004

“…The flexible mixed-model assembly line (FMMAL) [24], [25] refers to a kind of MMAL of which each stage or operation is introduced with the unrelated parallel assembly stations to eliminate the bottleneck and improve the flexibility. And the FMMAL has become a common form of intelligent production line in mass customization (MC) to organize the assembly operations of modular products.…”

Section: Imentioning

confidence: 99%

Dynamic Scheduling Framework of the Flexible Mixed-Model Assembly Line Based on the Internet of Manufacturing Things

Shi¹,

Guo²

2020

Preprint

0

View full text Add to dashboard Cite

To satisfy the needs of market customization, the traditional manufacturing is gradually transforming and upgrading into the intelligent manufacturing. In mass customization (MC), the assembly operations of modular products tend to be organized as the form of flexible mixed-model assembly line (FMMAL). The dynamic scheduling problem of FMMAL is quite complex with three issues of the product sequencing, station allocation and material delivery. At the same time, the disruption events of station failure, product inserting and product reworking are also considered. To solve this problem, a comprehensive framework combining the architecture of Internet of Manufacturing Things (IoMT) with the dynamic scheduling algorithms is proposed. Firstly, the IoMT-based FMMAL are constructed via the multi-agent system (MAS) and ubiquitous environment. Secondly, a mathematical model of FMMAL are formulated with the decision variables, optimization objectives and constraint conditions. Thirdly, the IoMT-oriented algorithms for dynamic scheduling are proposed including the fuzzy analytic hierarchy process (FAHP) for normalization, weighted sum of properties-improved genetic algorithm (WSP-IGA) for prescheduling, priority weights search-simulated annealing (PWS-SA) for rescheduling. Lastly, a discrete event simulation of a numerical case is conducted to demonstrate the practicality and validity of proposed theories and algorithms. The results show that the proposed hyper-heuristics (WSP-IGA and PWS-SA) can respectively realize the prescheduling and rescheduling of FMMAL in four modes including the synthesized mode, time-efficient mode, just-in-time mode and energy-saving mode, which are superior to the four referenced meta-heuristics.

show abstract

“…The decoding of Chromosome 2 is shown in Equation 23- (25). The decoded Chromosome 2 means a feasible solution of priority matrix of all the products to be assembled in the stations.…”

Section: ) Encoding and Decodingmentioning

confidence: 99%

Dynamic Scheduling Framework of the Flexible Mixed-Model Assembly Line Based on the Internet of Manufacturing Things

Shi¹,

Guo²

2020

Preprint

0

View full text Add to dashboard Cite

To satisfy the needs of market customization, the traditional manufacturing is gradually transforming and upgrading into the intelligent manufacturing. In mass customization (MC), the assembly operations of modular products tend to be organized as the form of flexible mixed-model assembly line (FMMAL). The dynamic scheduling problem of FMMAL is quite complex with three issues of the product sequencing, station allocation and material delivery. At the same time, the disruption events of station failure, product inserting and product reworking are also considered. To solve this problem, a comprehensive framework combining the architecture of Internet of Manufacturing Things (IoMT) with the dynamic scheduling algorithms is proposed. Firstly, the IoMT-based FMMAL are constructed via the multi-agent system (MAS) and ubiquitous environment. Secondly, a mathematical model of FMMAL are formulated with the decision variables, optimization objectives and constraint conditions. Thirdly, the IoMT-oriented algorithms for dynamic scheduling are proposed including the fuzzy analytic hierarchy process (FAHP) for normalization, weighted sum of properties-improved genetic algorithm (WSP-IGA) for prescheduling, priority weights search-simulated annealing (PWS-SA) for rescheduling. Lastly, a discrete event simulation of a numerical case is conducted to demonstrate the practicality and validity of proposed theories and algorithms. The results show that the proposed hyper-heuristics (WSP-IGA and PWS-SA) can respectively realize the prescheduling and rescheduling of FMMAL in four modes including the synthesized mode, time-efficient mode, just-in-time mode and energy-saving mode, which are superior to the four referenced meta-heuristics.

show abstract

“…During production, two interconnected parallel flows can be differentiated. In order to produce a type of parts, it is necessary to pass the workpiece through production stations [2]. The system in which the assembly is performed in the interconnected stations has the characteristics of a flexible manufacturing process [3].…”

Section: Introductionmentioning

confidence: 99%

Image Processing Method Based Quality Test on a Smart Flexible Assembly Mechatronic System With Component Recovery

Gurgu

¹

,

Duca

²

,

Minca

³

2020

J. Sci. Arts

0

View full text Add to dashboard Cite

. The article presents a new approach for image processing algorithms based on image processing techniques: edge detection, normal cross correlation (NCC) and M-estimator Sample Consensus (MASC). The new algorithm is integrated into the station dedicated to the quality test (QT) on a SMART flexible assembly mechatronic system with component recovery. As a result of the QT analysis, the manufacturing flow can continue with either the following operations: disassembly and recovery of components or transport and storage of good products. It is obvious the importance of implementing a high accuracy analysis function for products quality. The new algorithm increases the performance of the detection function both in terms of identification but also in the speed of QT execution. The results obtained in this article will be used in future research for the development of a machine vision system adapted to modern Industry 4.0 technologies, in which it will have the control structure specific to an integrated IoT sensor.

show abstract

Cyclic scheduling of flexible mixed model assembly lines with parallel stations

Cited by 32 publications

References 24 publications

Dynamic Scheduling Framework of the Flexible Mixed-Model Assembly Line Based on the Internet of Manufacturing Things

Dynamic Scheduling Framework of the Flexible Mixed-Model Assembly Line Based on the Internet of Manufacturing Things

Dynamic Scheduling Framework of the Flexible Mixed-Model Assembly Line Based on the Internet of Manufacturing Things

Image Processing Method Based Quality Test on a Smart Flexible Assembly Mechatronic System With Component Recovery

Contact Info

Product

Resources

About