Product life cycle information management in the electronics supply chain

Bindel, Axel; Rosamond, Emma L.; Conway, Paul; West, Andrew A.

doi:10.1177/0954405412448780

Cited by 16 publications

(8 citation statements)

References 30 publications

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“…Advanced temperature sensors and smart sensors have been used in production of hydrogen from methane. 75 Other applications include the use of anti-metallic radio-frequency identification (RFID) in manufacturing environments; 8 printed circuit boards 76 have also been demonstrated. When the smart sensors have processors and software for an efficient exchange of data, they are called as smart products/parts .…”

Section: Characteristics Clustersmentioning

confidence: 99%

Smart manufacturing: Characteristics, technologies and enabling factors

Mittal

Khan

Romero

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part B:

405

261

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The purpose of this article is to collect and structure the various characteristics, technologies and enabling factors available in the current body of knowledge that are associated with smart manufacturing. Eventually, it is expected that this selection of characteristics, technologies and enabling factors will help compare and distinguish other initiatives such as Industry 4.0, cyber-physical production systems, smart factory, intelligent manufacturing and advanced manufacturing, which are frequently used synonymously with smart manufacturing. The result of this article is a comprehensive list of such characteristics, technologies and enabling factors that are regularly associated with smart manufacturing. This article also considers principles of ''semantic similarity'' to establish the basis for a future smart manufacturing ontology, since it was found that many of the listed items show varying overlaps; therefore, certain characteristics and technologies are merged and/or clustered. This results in a set of five defining characteristics, 11 technologies and three enabling factors that are considered relevant for the smart manufacturing scope. This article then evaluates the derived structure by matching the characteristics and technology clusters of smart manufacturing with the design principles of Industry 4.0 and cyber-physical systems. The authors aim to provide a solid basis to start a broad and interdisciplinary discussion within the research and industrial community about the defining characteristics, technologies and enabling factors of smart manufacturing.

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Section: Characteristics Clustersmentioning

confidence: 99%

Smart manufacturing: Characteristics, technologies and enabling factors

Mittal

Khan

Romero

et al. 2017

Proceedings of the Institution of Mechanical Engineers, Part B:

405

261

View full text Add to dashboard Cite

show abstract

“…Through the traceability and process information systems, the performance of the supply chain can be analyzed. Bindel et al 7 discuss the application of an embedded RFID device into printed circuit boards for life cycle monitoring of electronic products to support product service systems. In the construction domain, the study demonstrates the implementation of a wireless passive RFID-based technology system for construction resource field mobility and status monitoring by Costin et al 8 Laniel et al 9 apply RFID to track and monitor temperature in the cold chain.…”

Section: Literature Reviewmentioning

confidence: 99%

Radio frequency identification–enabled monitoring and evaluating in the discrete manufacturing process

Yuan

Guo

Wei

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part B:

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Process monitoring is a major focus on improving productivity of discrete manufacturing. With the recent application of new technologies such as radio frequency identification to manufacturing process, real-time production information has become available for decision support in manufacturing system. This study presents a radio frequency identification–based visibility monitoring rule for tracking work-in-process. Specific to the aviation manufacturing shop floor, a case study for demonstration is designed. The value of radio frequency identification–enabled real-time information is investigated within the discrete manufacturing operation. For this purpose, a simplified simulation model is developed to test the benefit of radio frequency identification–based rule compared to the classical scheduling rule. The results indicate that the adoption of radio frequency identification brings better production performance.

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“…Huang et al [11][12][13] and Qu et al 14 presented approaches for deploying RFID-based wireless manufacturing technology for tracking and managing WIP inventories, walkingworker assembly islands, and adaptive assembly planning in job shops. Bindel et al 15 discussed the application of an embedded RFID device into printed circuit boards for life cycle monitoring of electronic products to support product service systems. By comparing the timing of the RFID reads for the same tag, Mo et al 16 developed a directional discrimination system in which the direction of the RFID tag movement can be discriminated.…”

Section: Related Workmentioning

confidence: 99%

A performance evaluation method for radio frequency identification–based tracking network of job-shop-type work-in-process material flows

Zhang

Jiang

Zheng

et al. 2013

Proceedings of the Institution of Mechanical Engineers, Part B:

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With the rapid development of the modern manufacture, a radio frequency identification-based tracking network has been gradually established to monitor and track the material flows in a job-shop floor. Based on an event-driven graphical schema, this article puts forward a new method for modeling and analyzing the job-shop-type work-in-process material flows tracking network. The schema elements are mapped into the network nodes, and the association relationships among the elements are mapped into the network edges. Furthermore, corresponding measures and metrics are presented to evaluate the work-in-process material flows tracking network performance. Finally, a simple example is given to verify the feasibility of the proposed method. It is expected that this study will provide a systemic evaluation method for guiding and optimizing the radio frequency identification-based tracking configuration solution for job-shop-type material flows.

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Product life cycle information management in the electronics supply chain

Cited by 16 publications

References 30 publications

Smart manufacturing: Characteristics, technologies and enabling factors

Smart manufacturing: Characteristics, technologies and enabling factors

Radio frequency identification–enabled monitoring and evaluating in the discrete manufacturing process

A performance evaluation method for radio frequency identification–based tracking network of job-shop-type work-in-process material flows

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