IoT-Based Prognostics and Systems Health Management for Industrial Applications

Kwon, Daeil; Hodkiewicz, Melinda; Fan, Jiajie; Shibutani, Tadahiro; Pecht, Michael

doi:10.1109/access.2016.2587754

Cited by 206 publications

(75 citation statements)

References 58 publications

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“…Although asset manufacturers and operators have used sensors and manual data collection for decades to collect health data on assets, developments towards IoT offer a new opportunity where data is transmitted from assets to the Cloud [80]. In this architecture, data for health estimation (e.g., condition monitoring, environmental condition data, previous maintenance work, and operating data) is more readily available for health monitoring and prognostic assessment to assist in identifying maintenance work.…”

Section: Applicable Research and Technologiesmentioning

confidence: 99%

Where Do We Start? Guidance for Technology Implementation in Maintenance Management for Manufacturing

Brundage

Sexton

Hodkiewicz

et al. 2019

Journal of Manufacturing Science and Engineering

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Recent efforts in smart manufacturing (SM) have proven quite effective at elucidating system behavior using sensing systems, communications, and computational platforms, along with statistical methods to collect and analyze the real-time performance data. However, how do you effectively select where and when to implement these technology solutions within manufacturing operations? Furthermore, how do you account for the human-driven activities in manufacturing when inserting new technologies? Due to a reliance on human problem-solving skills, today’s maintenance operations are largely manual processes without wide-spread automation. The current state-of-the-art maintenance management systems and out-of-the-box solutions do not directly provide necessary synergy between human and technology, and many paradigms ultimately keep the human and digital knowledge systems separate. Decision makers are using one or the other on a case-by-case basis, causing both human and machine to cannibalize each other’s function, leaving both disadvantaged despite ultimately having common goals. A new paradigm can be achieved through a hybridized system approach—where human intelligence is effectively augmented with sensing technology and decision support tools, including analytics, diagnostics, or prognostic tools. While these tools promise more efficient, cost-effective maintenance decisions and improved system productivity, their use is hindered when it is unclear what core organizational or cultural problems they are being implemented to solve. To explicitly frame our discussion about implementation of new technologies in maintenance management around these problems, we adopt well-established error mitigation frameworks from human factors experts—who have promoted human–system integration for decades—to maintenance in manufacturing. Our resulting tiered mitigation strategy guides where and how to insert SM technologies into a human-dominated maintenance management process.

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Section: Applicable Research and Technologiesmentioning

confidence: 99%

Where Do We Start? Guidance for Technology Implementation in Maintenance Management for Manufacturing

Brundage

Sexton

Hodkiewicz

et al. 2019

Journal of Manufacturing Science and Engineering

View full text Add to dashboard Cite

show abstract

“…With the rapid development of wireless communication technologies, the IoT has been realized step by step in recent years. Over 60% of the IoT application scenarios are massive narrowband IoT (NB-IoT), whose characteristics include massive access devices, transmission delay tolerance and low cost, such as smart meters, eHealth, and so on [1,2,3,4,5]. The low-cost requirement means that cheap/inaccurate crystal oscillators are used, which leads to a large frequency offset between the transmitter and the receiver.…”

Section: Introductionmentioning

confidence: 99%

Frequency Offset Tolerant Synchronization Signal Design in NB-IoT

Zou

2018

Sensors

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Timing detection is the first step and very important in wireless communication systems. Timing detection performance is usually affected by the frequency offset. Therefore, it is a challenge to design the synchronization signal in massive narrowband Internet of Things (NB-IoT) scenarios where the frequency offset is usually large due to the low cost requirement. In this paper, we firstly proposed a new general synchronization signal structure with a couple of sequences which are conjugated to remove the potential timing error that arises from large frequency offset. Then, we analyze the suitable sequence for our proposed synchronization signal structure and discuss a Zadoff–Chu (ZC) sequence with root 1 as an example. Finally, the simulation results demonstrate that our proposed synchronization signal can work well when the frequency offset is large. It means that our proposed synchronization signal design is very suitable for the massive NB-IoT.

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“…In the study of Kwon et al [23], a methodology for the system health industrial application management based on IoT is initiated. A discipline that uses sensors is Prognostics and System Health Management (PHM) to enable the access of health care systems in diagnosing the anomalous behavior and proceeds for the prediction of the remaining useful performance as life asset.…”

Section: Communications On Applied Electronics (Cae) -Issn : 2394-471mentioning

confidence: 99%

Review of Research Approaches for Securing Communication in Internet of Things

Shamshekhar¹,

R.²

2018

CAE

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With the advent of Internet-of-Things (IoT), the communication has become very much ubiquitous with a faster response by supporting pervasive application demands. However, its resistivity towards adversary is still flawed with its existing security techniques. Owing to the novel nature of IoT, there have been various initiating attempts to introduce secure communication schemes for offering better security features to a diverse range of applications in IoT. This paper contributes to discuss existing research trend towards secure communication among the devices in IoT. The discussion present in the paper is anticipated to assists a snapshot of existing methods and approaches to research-based techniques in IoT.

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IoT-Based Prognostics and Systems Health Management for Industrial Applications

Cited by 206 publications

References 58 publications

Where Do We Start? Guidance for Technology Implementation in Maintenance Management for Manufacturing

Where Do We Start? Guidance for Technology Implementation in Maintenance Management for Manufacturing

Frequency Offset Tolerant Synchronization Signal Design in NB-IoT

Review of Research Approaches for Securing Communication in Internet of Things

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