In-process sensing for tool wear monitoring

With the ever-increasing availability of data, it has been crucial for every industries to collect as much data as possible and to make sense of these data to improve the efficiency of their factory or operation. As the world is moving ahead and entering the 4th industrial revolution, it is importan...

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主要作者: Tan, Hock Hao
其他作者: Tegoeh Tjahjowidodo
格式: Final Year Project
語言:English
出版: 2016
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在線閱讀:http://hdl.handle.net/10356/68256
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spelling sg-ntu-dr.10356-682562023-03-04T18:33:35Z In-process sensing for tool wear monitoring Tan, Hock Hao Tegoeh Tjahjowidodo School of Mechanical and Aerospace Engineering DRNTU::Engineering With the ever-increasing availability of data, it has been crucial for every industries to collect as much data as possible and to make sense of these data to improve the efficiency of their factory or operation. As the world is moving ahead and entering the 4th industrial revolution, it is important for manufacturing company to produce better quality product at lower price. This can be achieve by gathering real-time data and making use of such data to improve the process while the product is being produce. In this project, an attempt to produce a model which correlate the applied force from the machine and input to the Acoustic Emission (AE) model will be developed. This model will be develop using Mass-Spring-Damper as its core model along with Newton’s Second Law of Motion as it mathematical foundation. Bachelor of Engineering (Mechanical Engineering) 2016-05-25T04:17:17Z 2016-05-25T04:17:17Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/68256 en Nanyang Technological University 26 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering
spellingShingle DRNTU::Engineering
Tan, Hock Hao
In-process sensing for tool wear monitoring
description With the ever-increasing availability of data, it has been crucial for every industries to collect as much data as possible and to make sense of these data to improve the efficiency of their factory or operation. As the world is moving ahead and entering the 4th industrial revolution, it is important for manufacturing company to produce better quality product at lower price. This can be achieve by gathering real-time data and making use of such data to improve the process while the product is being produce. In this project, an attempt to produce a model which correlate the applied force from the machine and input to the Acoustic Emission (AE) model will be developed. This model will be develop using Mass-Spring-Damper as its core model along with Newton’s Second Law of Motion as it mathematical foundation.
author2 Tegoeh Tjahjowidodo
author_facet Tegoeh Tjahjowidodo
Tan, Hock Hao
format Final Year Project
author Tan, Hock Hao
author_sort Tan, Hock Hao
title In-process sensing for tool wear monitoring
title_short In-process sensing for tool wear monitoring
title_full In-process sensing for tool wear monitoring
title_fullStr In-process sensing for tool wear monitoring
title_full_unstemmed In-process sensing for tool wear monitoring
title_sort in-process sensing for tool wear monitoring
publishDate 2016
url http://hdl.handle.net/10356/68256
_version_ 1759853425494851584