RFID-enabled indoor positioning method for a real-time manufacturing execution system using OS-ELM

The fast development of smart sensors and wearable devices has provided the opportunity to develop intelligent operator workspaces. The resultant Human-Cyber-Physical Systems (H-CPS) integrate the operators into flexible and multi-purpose manufacturing processes. The primary enabling factor of the resultant Operator 4.0 paradigm is the integration of advanced sensor and actuator technologies and communications solutions. This work provides an extensive overview of these technologies and highlights that the design of future workplaces should be based on the concept of intelligent space.

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“…Reduce the number of unnecessary movements of operators [120]. Support real-time Manufacturing Execution Systems (MES) [122].…”

Section: Movement Analysismentioning

confidence: 99%

Enabling Technologies for Operator 4.0: A Survey

et al. 2018

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“…Radio Frequency Identification (RFID) technology has been used to manage objects location in the manufacturing shopfloor. It is more popular than similar technologies for object localization, such as Wireless Sensor Networks (WSN) and WiFi, due to the affordable price and the easy deployment [Ni et al, 2011, Yang et al, 2016.…”

Section: Introductionmentioning

confidence: 99%

An Online RFID Localization in the Manufacturing Shopfloor

Ashfahani

Pratama

Lughofer

et al. 2019

Predictive Maintenance in Dynamic Systems

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Radio Frequency Identification technology has gained popularity for cheap and easy deployment. In the realm of manufacturing shopfloor, it can be used to track the location of manufacturing objects to achieve better efficiency. The underlying challenge of localization lies in the non-stationary characteristics of manufacturing shopfloor which calls for an adaptive life-long learning strategy in order to arrive at accurate localization results. This paper presents an evolving model based on a novel evolving intelligent system, namely evolving Type-2 Quantum Fuzzy Neural Network (eT2QFNN), which features an interval type-2 quantum fuzzy set with uncertain jump positions. The quantum fuzzy set possesses a graded membership degree which enables better identification of overlaps between classes. The eT2QFNN works fully in the evolving mode where all parameters including the number of rules are automatically adjusted and generated on the fly. The parameter adjustment scenario relies on decoupled extended Kalman filter method. Our numerical study shows that eT2QFNN is able to deliver comparable accuracy compared to state-of-the-art algorithms.

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“…(Morariu et al 2016) im-prove the previous research work by implementing and testing redundancy and scalability of virtualized MES. (Yang, Zhang, and Chen 2016) highlights several issues found on the shop-floor which can generate manufacturing objects tracking inaccuracies in a MES. He proposes adoption of RFID systems and an on-line sequential extreme learning machine (OS-LEM) algorithm for data processing in order to deal with the lack of real-time data processing reliability and accuracy of manufacturing objects tracking.…”

Section: From 2015 Until Presentmentioning

confidence: 99%

Smart CPS: vertical integration overview and user story with a cobot

Tamás

Murar

2018

International Journal of Computer Integrated Manufacturing

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In this paper an overview and a demonstration for the vertical integration of manufacturing enterprise layers are described by implementing the Manufacturing Execution System (MES). In the first part of the paper the details regarding the MES implementation are described, while in the second part the use case specific insights are highlighted. The presented use case contains each important step of a production line involving also a collaborative Baxter type robot and the state-of-the-art tools for MES implementation. The cobot-involved use case is relevant and generic enough in the context of Industry 4.0 offering a good overview of a typical vertical integration use case which can be generalized and applied to manufacturing scenarios. The paper ends with the lessons learned from the vertical integration process as well as future direction which can be followed in such a context.

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RFID-enabled indoor positioning method for a real-time manufacturing execution system using OS-ELM

Cited by 63 publications

References 39 publications

Enabling Technologies for Operator 4.0: A Survey

Enabling Technologies for Operator 4.0: A Survey

An Online RFID Localization in the Manufacturing Shopfloor

Smart CPS: vertical integration overview and user story with a cobot

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