scholarly journals Towards Data Acquisition for Predictive Maintenance of Industrial Robots

Procedia CIRP ◽  
2021 ◽  
Vol 104 ◽  
pp. 62-67
Author(s):  
Corbinian Nentwich ◽  
Gunther Reinhart
Keyword(s):  
Data Acquisition ◽  
Industrial Robots ◽  
Predictive Maintenance

Robotics Application in Remote Data Acquisition and Control for Solar Ponds

2012 ◽  
Vol 253-255 ◽  
pp. 705-715 ◽  
Author(s):  
Mohamed Elbanhawi ◽  
Milan Simic
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Energy Production ◽  
Green Energy ◽  
Industrial Robots ◽  
Sampling Station ◽  
Monitoring And Control ◽  
Solar Ponds ◽  
And Control ◽  
Remote Data

This paper presents one application of industrial robots in the automation of renewable energy production. The robot supports remote performance monitoring and maintenance of salinity gradient solar ponds. The details of the design, setup and the use of the robot sampling station and the remote Data Acquisition (DAQ) system are given here. The use of a robot arm, to position equipment and sensors, provides accurate and reliable real time data needed for autonomous monitoring and control of this type of green energy production. Robot upgrade of solar ponds can be easily integrated with existing systems. Data logged by the proposed system can be remotely accessed, plotted and analysed. Thus the simultaneous and remote monitoring of a large scale network of ponds can be easily implemented. This provides a fully automated solution to the monitoring and control of green energy production operations, which can be used to provide heat and electricity to buildings. Remote real time monitoring will facilitate the setup and operations of several solar ponds around cities.

Interface between LabVIEW and FANUC Robot

2012 ◽  
Vol 443-444 ◽  
pp. 464-470
Author(s):  
Hai Ming Zhang ◽  
Xi Chen Yang
Keyword(s):  
Data Acquisition ◽  
Industrial Robot ◽  
Automatic Measurement ◽  
Industrial Robots ◽  
Software Components ◽  
Current Position ◽  
Control Module ◽  
System Variables ◽  
And Control ◽  
Programming Interface

FANUC industrial robots are used more and more widely. However, robots’ communicant protocol and interface are different and unopened. Robot interface technology has become an important factor. Controlling robot movement via interfere has become an important issue in recent years.NI LabVIEW has powerful data acquisition and measurement ability and friendly graphics programming interface. It has the most percentages in the field of automatic measurement. The interface between PC and FANUC industrial robot is studied. A serial of sub VI are developed based on LabVIEW, including connecting robot with PC, initializing robot interface, reading and changing system variables, reading and changing position variables, displaying current position, controlling robot programs and so on. This paper describes the hardware and software components of the system, and the typical communicant and control module between PC and FANUC robot developed by LabVIEW. After testing, the function of every module can be achieved and performs well.

scholarly journals Forecasting Appliances Failures: A Machine-Learning Approach to Predictive Maintenance

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 208
Author(s):  
Sofia Fernandes ◽  
Mário Antunes ◽  
Ana Rita Santiago ◽  
João Paulo Barraca ◽  
Diogo Gomes ◽  
...  
Keyword(s):  
Machine Learning ◽  
Data Acquisition ◽  
Failure Detection ◽  
Predictive Maintenance ◽  
Learning Approach ◽  
Household Appliances ◽  
Machine Learning Approach ◽  
The Cost

Heating appliances consume approximately 48 % of the energy spent on household appliances every year. Furthermore, a malfunctioning device can increase the cost even further. Thus, there is a need to create methods that can identify the equipment’s malfunctions and eventual failures before they occur. This is only possible with a combination of data acquisition, analysis and prediction/forecast. This paper presents an infrastructure that supports the previously mentioned capabilities and was deployed for failure detection in boilers, making possible to forecast faults and errors. We also present our initial predictive maintenance models based on the collected data.

scholarly journals MACHINE TOOL ABILITY REPRESENTATION: A REVIEW

2018 ◽  
Vol 18 (2) ◽  
pp. 5-16 ◽  
Author(s):  
Logesh SADASIVAM ◽  
Andreas ARCHENTI ◽  
Ulf SANDBERG
Keyword(s):  
Machine Tool ◽  
Data Acquisition ◽  
Quantitative Methods ◽  
Manufacturing Industry ◽  
Health Condition ◽  
Predictive Maintenance ◽  
Smart Manufacturing ◽  
Current Trends ◽  
Holistic Understanding ◽  
Further Development

Smart manufacturing and predictive maintenance are current trends in the manufacturing industry. However, the holistic understanding of the machine tool health condition in terms of accuracy, functions, process and availability is still unclear. This uncertainty renders the development of models and the data acquisition related to machine tool health condition ineffective. This paper proposes the term machine tool ability as an interconnection between the accuracy, functions, the process and the availability to overcome the lack of the holistic understanding of the machine tool. This will facilitate the further development of qualitative or quantitative methods as well as models. The research highlights the challenges and gaps to understand the machine tool ability.

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