Monitoring of a Veneer Lathe Knife by the use of an Industrial Internet of Things- Platform
(2018) In CODEN:LUTEDX/TEIE EIEM01 20181Industrial Electrical Engineering and Automation
- Abstract
- The number of devices connected to the Internet grows constantly. This information entity has been labeled the Internet of Things (IoT). One important aspect of this is the industrial applications, sometimes labeled the Industrial Internet of Things (IIoT). Collecting and analyzing the massive amounts of data that industry generates will only become more and more important as technology and the need for efficiency increase.
Novotek is a company with long and extensive experience of industrial IT and automation. Together with their customer Quant Service they are launching a project for predictive maintenance. This aims to monitor several different industrial sites using an industrial platform and the IIoT framework. The monitoring will... (More) - The number of devices connected to the Internet grows constantly. This information entity has been labeled the Internet of Things (IoT). One important aspect of this is the industrial applications, sometimes labeled the Industrial Internet of Things (IIoT). Collecting and analyzing the massive amounts of data that industry generates will only become more and more important as technology and the need for efficiency increase.
Novotek is a company with long and extensive experience of industrial IT and automation. Together with their customer Quant Service they are launching a project for predictive maintenance. This aims to monitor several different industrial sites using an industrial platform and the IIoT framework. The monitoring will allow for tracking of machine status and maintenance needs from both near and afar.
One of the sites for this project is a veneer production line for composite wood products. As a part of the monitoring and predictive maintenance project, this report looks at the possibility of using the
ThingWorx IIoT platform’s analytics functionality to determine the need for maintenance of the cutting knife on a veneer lathe. The goal is to look at its uses for monitoring and predictive maintenance for this particular case but also as a general method. The process for this will be twofold. Since the project uses the IIoT framework one part is how to collect the data from the site and then passing it through the platform and to the analytics program. The second part is the machine learning and statistical methods and algorithms used to analyze the data for predictions. For benchmarking, it will be compared to another analytics product.
The results of the project are not conclusive concerning the knife predictions. Development of the measurement setup is needed. The IIoT platform does however show potential in being used for the intended purpose. (Less) - Popular Abstract
- Predictive Maintenance with the Industrial Internet of Things
The Industrial Internet of Things is growing every day. When machines talk to each other, they will revolutionize industry as we know it.
The Industrial Internet of Things (IIoT), meaning real-time interconnectedness of industrial devices, is said to play a big part in the next industrial revolution, Industry 4.0. Pretty much all industrial devices, or Things, generate data. But data is not information. If it is to be valuable, it must be analyzed with the right tools so that the right decisions can be made. Ultimately, this will lead to a complete automation of the industrial process with smart machines talking and giving advice to each other.
Novotek, a company with long... (More) - Predictive Maintenance with the Industrial Internet of Things
The Industrial Internet of Things is growing every day. When machines talk to each other, they will revolutionize industry as we know it.
The Industrial Internet of Things (IIoT), meaning real-time interconnectedness of industrial devices, is said to play a big part in the next industrial revolution, Industry 4.0. Pretty much all industrial devices, or Things, generate data. But data is not information. If it is to be valuable, it must be analyzed with the right tools so that the right decisions can be made. Ultimately, this will lead to a complete automation of the industrial process with smart machines talking and giving advice to each other.
Novotek, a company with long experience in the areas of industrial IT and automation, is launching an IIoT project together with a customer. As a part of this, a MSc thesis study was done on using an IIoT platform for predictive maintenance. The object of study was a veneer peeling lathe used in the manufacturing of composite wood products. Wood cutting constantly dulls the tools involved and they need to be sharpened or exchanged several times during a workday. If it is possible for the machine to “know” the sharpness of its knife, it can decide when the optimal point of maintenance should be. One possible method to predict this is to monitor overall vibrations in the lathe and look for any patterns.
To handle all the communication, storing and analysis of the data, specialized tools are needed. One such tool is the IIoT platform ThingWorx. ThingWorx has functionality for a multitude of applications. It can keep track of all your Things and handle the communication between them. It also has components for advanced analysis of data, using machine learning and statistical algorithms.
The results of the study are not conclusive but tests for the process imply the usefulness of the IIoT framework. The application implemented creates a well-defined path for data to follow. This functions both for the modeling of the problem as well facilitating predictive process monitoring in actual operation.
Once an IIoT solution has been implemented a company has a complete structure for connecting and monitoring all parts of their business. This goes beyond just reading production parameters from afar. This kind of connected industry can monitor itself. It can make predictions and take the right decisions for the manufacturing autonomously, only involving humans when needed. The possibilities for optimization and efficiency goes far beyond what was thought possible only a decade ago. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8938709
- author
- Lindqvist, Nils LU
- supervisor
- organization
- course
- EIEM01 20181
- year
- 2018
- type
- H3 - Professional qualifications (4 Years - )
- subject
- keywords
- Process Monitoring, Industrial Internet of Things, Automation, Machine Learning, ThingWorx, Industrial IT, Wood Veneer Production
- publication/series
- CODEN:LUTEDX/TEIE
- report number
- 5403
- other publication id
- TEIE-5403
- language
- English
- id
- 8938709
- date added to LUP
- 2019-03-29 13:50:14
- date last changed
- 2019-03-29 13:50:14
@misc{8938709,
abstract = {{The number of devices connected to the Internet grows constantly. This information entity has been labeled the Internet of Things (IoT). One important aspect of this is the industrial applications, sometimes labeled the Industrial Internet of Things (IIoT). Collecting and analyzing the massive amounts of data that industry generates will only become more and more important as technology and the need for efficiency increase.
Novotek is a company with long and extensive experience of industrial IT and automation. Together with their customer Quant Service they are launching a project for predictive maintenance. This aims to monitor several different industrial sites using an industrial platform and the IIoT framework. The monitoring will allow for tracking of machine status and maintenance needs from both near and afar.
One of the sites for this project is a veneer production line for composite wood products. As a part of the monitoring and predictive maintenance project, this report looks at the possibility of using the
ThingWorx IIoT platform’s analytics functionality to determine the need for maintenance of the cutting knife on a veneer lathe. The goal is to look at its uses for monitoring and predictive maintenance for this particular case but also as a general method. The process for this will be twofold. Since the project uses the IIoT framework one part is how to collect the data from the site and then passing it through the platform and to the analytics program. The second part is the machine learning and statistical methods and algorithms used to analyze the data for predictions. For benchmarking, it will be compared to another analytics product.
The results of the project are not conclusive concerning the knife predictions. Development of the measurement setup is needed. The IIoT platform does however show potential in being used for the intended purpose.}},
author = {{Lindqvist, Nils}},
language = {{eng}},
note = {{Student Paper}},
series = {{CODEN:LUTEDX/TEIE}},
title = {{Monitoring of a Veneer Lathe Knife by the use of an Industrial Internet of Things- Platform}},
year = {{2018}},
}