In-Process Dimension Monitoring System for Integration of Legacy Machine Tools into the Industry 4.0 Framework

2021 ◽  
Vol 5 (1) ◽  
pp. 20210021
Author(s):  
Sunidhi Dayam ◽  
K. A. Desai ◽  
Mathew Kuttolamadom
Keyword(s):  
Monitoring System ◽  
Machine Tools ◽  
Industry 4.0 ◽  
Process Dimension

scholarly journals Embedded vision device integration via OPC UA: Design and evaluation of a neural network-based monitoring system for Industry 4.0

Procedia CIRP ◽  
2021 ◽  
Vol 100 ◽  
pp. 43-48
Author(s):  
Sascha Julian Oks ◽  
Sebastian Zöllner ◽  
Max Jalowski ◽  
Jonathan Fuchs ◽  
Kathrin M. Möslein
Keyword(s):  
Neural Network ◽  
Monitoring System ◽  
Industry 4.0 ◽  
Embedded Vision ◽  
Device Integration

scholarly journals LoRaWAN and Blockchain based Safety and Health Monitoring System for Industry 4.0 Operators

Proceedings ◽  
2019 ◽  
Vol 42 (1) ◽  
pp. 77 ◽  
Author(s):  
Iván Froiz-Míguez ◽  
Paula Fraga-Lamas ◽  
José Varela-Barbeito ◽  
Tiago M. Fernández-Caramés
Keyword(s):  
Monitoring System ◽  
Industry 4.0 ◽  
Environmental Data ◽  
Insurance Companies ◽  
Area Network ◽  
Wide Area Network ◽  
Long Distance ◽  
Good Reliability ◽  
External Temperature ◽  
Safety And Health

The latest advances in the different Industry 4.0 technologies have enabled the automation and optimization of complex tasks of production processes thanks to their ability to monitor and track the state of physical elements like machinery, environmental sensors/actuators or industrial operators. This paper focuses on the latter and presents the design and evaluation of a system for monitoring industrial workers that provides a near real-time decentralized response system aimed at reacting and tracing events that affect operator personal safety and health. Such a monitoring system is based on the information collected from sensors encapsulated in IoT wearables that are used to measure both personal and environmental data. The communications architecture relies on LoRaWAN, an LPWAN (Low-Power Wide-Area Network) technology that offers good reliability in harsh communications environments and that provides relatively long distance communications with low-energy consumption. Specifically, each wearable sends the collected information (e.g., heart rate, altitude, external temperature, gas concentration, location) from the sensors to the nearest LoRaWAN gateway, which is transmitted to a pool of nodes where information is stored in a distributed manner. Such a decentralized system allows for providing information redundancy and guarantees its availability as long as there is an operative node. In addition, the proposed system is able to store and to process the collected data through smart contracts in a blockchain, which eliminate the need for a central backend and ensure the traceability and immutability of such data in order to share them with third parties (e.g., insurance companies or medical services).

Industrie-4.0-Nachrüstkit für Werkzeugmaschinen/Modular solution for condition-based maintenance and process monitoring – Industry 4.0 retrofitting kit for machine tools

2020 ◽  
Vol 110 (07-08) ◽  
pp. 491-495 ◽  
Author(s):  
David Barton ◽  
Reinhard Stamm ◽  
Sebastian Mergler ◽  
Cedric Bardenhagen ◽  
Jürgen Fleischer
Keyword(s):  
Process Monitoring ◽  
Machine Tools ◽  
Industry 4.0 ◽  
Economic Benefit ◽  
Industrie 4.0 ◽  
High Potential ◽  
Condition Based Maintenance ◽  
Machining Processes ◽  
Software Modules ◽  
Roll Out

Industrie 4.0 verspricht ein hohes wirtschaftliches Potenzial für produzierende Unternehmen. Allerdings wird dieses in bestehenden Werkzeugmaschinen bisher nur wenig ausgeschöpft. Um das Ausrollen von Funktionen für die zustandsorientierte Instandhaltung und die Überwachung des Bearbeitungsprozesses zu ermöglichen, wurde ein modulares Nachrüstkit entwickelt. Mit dem Kit können Maschinen individuell um Hardware- und Softwarebausteine erweitert werden.   Industry 4.0 offers manufacturers a high potential for economic benefit. However, this potential is only rarely exploited in existing machine tools. To enable the roll-out of functions for condition-based maintenance and monitoring of machining processes, a modular retrofitting kit has been developed. This kit allows machines to be individually upgraded with hardware and software modules.

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