An RFID-based intelligent decision support system architecture for production monitoring and scheduling in a distributed manufacturing environment

Guo, Zitao; Ngai, Eric W.T.; Yang, Can; Liang, Xuedong

doi:10.1016/j.ijpe.2014.09.004

Cited by 176 publications

(85 citation statements)

References 39 publications

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“…Through a case study in the garment industry, they proved the number of defects, production time, and rework cost were improved. Guo et al [23] proposed an RFID-based intelligent decision support system to facilitate production monitoring and scheduling in a distributed labor-intensive manufacturing environment.…”

Section: Rfid Applications In Manufacturingmentioning

confidence: 99%

“…However, if the regular antennas are used as they are in the sequencing work, the tags cannot be read in an orderly manner, and sequencing errors cannot be determined accurately. In order to recognize the correct sequence of RFIDs in a row, we used an RFID sequence-checking algorithm which is proposed in [23]. The algorithm is based on the read frequency (i.e., the number of successful reads in a predefined cycle time).…”

Section: Sequence-checking Algorithmmentioning

confidence: 99%

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Implementation of an RFID-Based Sequencing-Error-Proofing System for Automotive Manufacturing Logistics

Kang

Kim²,

Lee

2018

Applied Sciences

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Abstract:Serialized tracing provides the ability to track and trace the lifecycle of the products and parts. Unlike barcodes, Radio frequency identification (RFID), which is an important building block for internet of things (IoT), does not require a line of sight and has the advantages of recognizing many objects simultaneously and rapidly, and storing more information than barcodes. Therefore, RFID has been used in a variety of application domains such as logistics, distributions, and manufacturing, significantly improving traceability and process efficiency. In this study, we applied RFID to improve the just-in-sequence operation of an automotive inbound logistics process. First, we implemented an RFID-based visibility system for real-time traceability and control of part supply from the production lines of suppliers to the assembly line of a car manufacturer. Second, we developed an RFID-based sequence-error proofing system to avoid accidental line stops due to incorrect part sequencing. The whole system has been successfully installed in a rear-axle inbound logistics process of GM Korea. We achieved a significant amount of cost savings, especially due to the prevention of sequencing errors and part shortages, and the reduction of manual operations. Thorough cost-benefit analysis demonstrates the clear economic feasibility of using RFID technologies for the just-in-sequence inbound logistics in an automobile manufacturing environment.

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Section: Rfid Applications In Manufacturingmentioning

confidence: 99%

Section: Sequence-checking Algorithmmentioning

confidence: 99%

Implementation of an RFID-Based Sequencing-Error-Proofing System for Automotive Manufacturing Logistics

Kang

Kim²,

Lee

2018

Applied Sciences

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“…In [6], the order scheduling problem was addressed under a complex manufacturing environment which considers multiple processes, multiple departments and multiple plants. For recent advances in order scheduling, the reader is referred to [7][8][9][10] and references therein.…”

Section: Introductionmentioning

confidence: 99%

High-Dimensional Robust Multi-Objective Optimization for Order Scheduling: A Decision Variable Classification Approach

Zhong

Tang

et al. 2019

IEEE Trans. Ind. Inf.

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Abstract-This paper tackles the high-dimensional robust order scheduling problem. A multi-objective evolutionary algorithm called constrained nondominated sorting differential evolution based on decision variable classification is developed to search for robust order schedules. The decision variables are classified into highly and weakly robustness-related variables according to their contributions to the robustness of candidate solutions. The experimental results reveal that the performance of robust evolutionary optimization can be greatly improved via analyzing the properties of decision variables and then decomposing the high-dimensional robust optimization problem. It is also unveiled that the order scheduling is greatly affected by the uncertain daily production quantities. The robust order schedules are able to provide more information on earliness/tardiness of the orders, which enhances the flexibility of the production.

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“…RFID technology is known as an automatic identification technology as it uses wireless radio frequency waves which are produced by an electromagnetic field to transfer data to track and identify objects. This technology can be implemented in different fields such as tracking and identifying patients in hospitals [2], warehouse item tracking [3], tracking pallets and cases in shipments [4], monitoring production lines [5], and supply chain management [6].…”

Section: Introductionmentioning

confidence: 99%

Introducing a Novel Hybrid Artificial Intelligence Algorithm to Optimize Network of Industrial Applications in Modern Manufacturing

Azizi

2017

Complexity

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Recent advances in modern manufacturing industries have created a great need to track and identify objects and parts by obtaining real-time information. One of the main technologies which has been utilized for this need is the Radio Frequency Identification (RFID) system. As a result of adopting this technology to the manufacturing industry environment, RFID Network Planning (RNP) has become a challenge. Mainly RNP deals with calculating the number and position of antennas which should be deployed in the RFID network to achieve full coverage of the tags that need to be read. The ultimate goal of this paper is to present and evaluate a way of modelling and optimizing nonlinear RNP problems utilizing artificial intelligence (AI) techniques. This effort has led the author to propose a novel AI algorithm, which has been named "hybrid AI optimization technique," to perform optimization of RNP as a hard learning problem. The proposed algorithm is composed of two different optimization algorithms: Redundant Antenna Elimination (RAE) and Ring Probabilistic Logic Neural Networks (RPLNN). The proposed hybrid paradigm has been explored using a flexible manufacturing system (FMS), and results have been compared with Genetic Algorithm (GA) that demonstrates the feasibility of the proposed architecture successfully.

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An RFID-based intelligent decision support system architecture for production monitoring and scheduling in a distributed manufacturing environment

Cited by 176 publications

References 39 publications

Implementation of an RFID-Based Sequencing-Error-Proofing System for Automotive Manufacturing Logistics

Implementation of an RFID-Based Sequencing-Error-Proofing System for Automotive Manufacturing Logistics

High-Dimensional Robust Multi-Objective Optimization for Order Scheduling: A Decision Variable Classification Approach

Introducing a Novel Hybrid Artificial Intelligence Algorithm to Optimize Network of Industrial Applications in Modern Manufacturing

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