RFID-enabled real-time manufacturing execution system for mass-customization production

Zhong, Ray Y.; Dai, Qingyun; Qu, Ting; Hu, Guiping; Huang, George Q.

doi:10.1016/j.rcim.2012.08.001

Cited by 423 publications

(178 citation statements)

References 36 publications

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“…Second, three levels of enterprise management, production management and production must be vertically integrated via automation. Machine and plant control systems (PCS) shift data to react quickly to automation, and vertical integration can ensure that the information to other levels is accurate in the correct real time [76,77]. Third, the ability to exchange consistent data with other applications in production management level is an important attribute of the MES system; this is called horizontal integration.…”

Section: Status Monitoring and Predictive Maintenancementioning

confidence: 99%

Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

Tsai

2018

Energies

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Abstract:The textile industry is one of the world's major sources of industrial pollution, and related environmental issues are becoming an ever greater concern. This paper considers the environmental issues of carbon emissions, energy recycling, and waste reuse, and uses a mathematical programming model with Activity-Based Costing (ABC) and the Theory of Constraints (TOC) to achieve profit maximization. This paper discusses the combination of mathematical programming and Industry 4.0 techniques to achieve the purpose of green production planning and control for the textile industry in the new era. The mathematical programming model is used to determine the optimal product mix under various production constraints, while Industry 4.0 techniques are used to control the production progress to achieve the planning targets. With the help of an Industry 4.0 real-time sensor and detection system, it can achieve the purposes of recycling waste, reducing carbon emission, saving energy and cost, and finally achieving a maximization of profit. The main contributions of this research are using mathematical programming approach to formulate the decision model with ABC cost data and TOC constraints for the textile companies and clarifying the relation between mathematical programming models and Industry 4.0 techniques. Managers in the textile companies can apply this decision model to achieve the optimal product-mix under various constraints and to evaluate the effect on profit of carbon emissions, energy recycling, waste reuse, and material quantity discount.

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Section: Status Monitoring and Predictive Maintenancementioning

confidence: 99%

Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

Tsai

2018

Energies

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“…They proved that the suggested rules are better than traditional methods such as first in first out (FIFO) and earliest due date (EDD) through simulation tests based on real manufacturing process data. Zhong et al [20] developed a real-time MES framework based on RFID and applied it to mass-customization production shop floors. In addition, they developed a scheduling algorithm using real-time job pools and rules, and proved that the proposed algorithm facilitates real-time work in process control.…”

Section: Rfid Applications In Manufacturingmentioning

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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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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“…They present an approach for mass customization that is based on service-oriented architecture (SOA), and they illustrate it with a case study from the shoe industry. Zhong et al 18 defined mass customization as a competitive mode of producing a wide variety of customized products using a large-scale mass production strategy to satisfy diverse customer requirements. This article presents a radio frequency identification (RFID)-enabled real-time manufacturing execution system for mass customization management that includes real-time data collection.…”

Section: Literature Reviews On Mass Customizationmentioning

confidence: 99%

Design of a mass-customization-based cost-effective Internet of Things sensor system in smart building spaces

Park

Byun

Park

2016

International Journal of Distributed Sensor Networks

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In the coming Internet of Things era, billions of users and devices will be connected to the Internet; this will lead beyond the era of super-connection to the era of super-fusion. In this era, it is more important than ever to design a highly scalable Internet of Things infrastructure by mass customization for cost-effective production of exponentially increasing numbers of Internet of Things systems to provide more intelligent service in smart spaces. The purpose of this article is the design of mass-customization-based Internet of Things system through three-level analysis of the building; it proposes a new concept of a systematic design for providing economical Internet of Things systems for intelligent service in smart building spaces through three-level analysis comprising environmental-, service-, and functional-level analyses.

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RFID-enabled real-time manufacturing execution system for mass-customization production

Cited by 423 publications

References 36 publications

Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

Green Production Planning and Control for the Textile Industry by Using Mathematical Programming and Industry 4.0 Techniques

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

Design of a mass-customization-based cost-effective Internet of Things sensor system in smart building spaces

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