Statistical Analysis of Deep Drilling Process Conditions Using Vibrations and Force Signals

Cooling systems is a key point for hot forming process of Ultra High Strength Steels (UHSS). Normally, cooling systems is made using deep drilling technique. Although deep twist drill is better than other drilling techniques in term of higher productivity however its main problem is premature tool b...

Full description

Bibliographic Details
Main Authors:	Hazwan, Syafiq, A. M. N., Kamarizan, M. F., Ghazali, A. R., Yusoff
Format:	Conference or Workshop Item
Language:	English
Published:	EDP Sciences 2016
Subjects:	TJ Mechanical engineering and machinery TS Manufactures
Online Access:	http://umpir.ump.edu.my/id/eprint/14527/ http://umpir.ump.edu.my/id/eprint/14527/ http://umpir.ump.edu.my/id/eprint/14527/ http://umpir.ump.edu.my/id/eprint/14527/1/Statistical%20Analysis%20of%20Deep%20Drilling%20Process%20Conditions%20Using%20Vibrations.pdf

id	oai:umpir.ump.edu.my:14527
recordtype	eprints
spelling	oai:umpir.ump.edu.my:145272018-01-11T07:30:25Z http://umpir.ump.edu.my/id/eprint/14527/ Statistical Analysis of Deep Drilling Process Conditions Using Vibrations and Force Signals Hazwan, Syafiq A. M. N., Kamarizan M. F., Ghazali A. R., Yusoff TJ Mechanical engineering and machinery TS Manufactures Cooling systems is a key point for hot forming process of Ultra High Strength Steels (UHSS). Normally, cooling systems is made using deep drilling technique. Although deep twist drill is better than other drilling techniques in term of higher productivity however its main problem is premature tool breakage, which affects the production quality. In this paper, analysis of deep twist drill process parameters such as cutting speed, feed rate and depth of cut by using statistical analysis to identify the tool condition is presented. The comparisons between different two tool geometries are also studied. Measured data from vibrations and force sensors are being analyzed through several statistical parameters such as root mean square (RMS), mean, kurtosis, standard deviation and skewness. Result found that kurtosis and skewness value are the most appropriate parameters to represent the deep twist drill tool conditions behaviors from vibrations and forces data. The condition of the deep twist drill process been classified according to good, blunt and fracture. It also found that the different tool geometry parameters affect the performance of the tool drill. It believe the results of this study are useful in determining the suitable analysis method to be used for developing online tool condition monitoring system to identify the tertiary tool life stage and helps to avoid mature of tool fracture during drilling process. EDP Sciences 2016 Conference or Workshop Item PeerReviewed application/pdf en cc_by http://umpir.ump.edu.my/id/eprint/14527/1/Statistical%20Analysis%20of%20Deep%20Drilling%20Process%20Conditions%20Using%20Vibrations.pdf Hazwan, Syafiq and A. M. N., Kamarizan and M. F., Ghazali and A. R., Yusoff (2016) Statistical Analysis of Deep Drilling Process Conditions Using Vibrations and Force Signals. In: MATEC Web of Conferences: The 3rd International Conference on Mechanical Engineering Research (ICMER 2015), 18-19 August 2015 , Zenith Hotel, Kuantan, Pahang, Malaysia. pp. 1-7., 74 (00002). ISSN 2261-236X http://dx.doi.org/10.1051/matecconf/20167400002 DOI: 10.1051/matecconf/20167400002
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TJ Mechanical engineering and machinery TS Manufactures
spellingShingle	TJ Mechanical engineering and machinery TS Manufactures Hazwan, Syafiq A. M. N., Kamarizan M. F., Ghazali A. R., Yusoff Statistical Analysis of Deep Drilling Process Conditions Using Vibrations and Force Signals
description	Cooling systems is a key point for hot forming process of Ultra High Strength Steels (UHSS). Normally, cooling systems is made using deep drilling technique. Although deep twist drill is better than other drilling techniques in term of higher productivity however its main problem is premature tool breakage, which affects the production quality. In this paper, analysis of deep twist drill process parameters such as cutting speed, feed rate and depth of cut by using statistical analysis to identify the tool condition is presented. The comparisons between different two tool geometries are also studied. Measured data from vibrations and force sensors are being analyzed through several statistical parameters such as root mean square (RMS), mean, kurtosis, standard deviation and skewness. Result found that kurtosis and skewness value are the most appropriate parameters to represent the deep twist drill tool conditions behaviors from vibrations and forces data. The condition of the deep twist drill process been classified according to good, blunt and fracture. It also found that the different tool geometry parameters affect the performance of the tool drill. It believe the results of this study are useful in determining the suitable analysis method to be used for developing online tool condition monitoring system to identify the tertiary tool life stage and helps to avoid mature of tool fracture during drilling process.
format	Conference or Workshop Item
author	Hazwan, Syafiq A. M. N., Kamarizan M. F., Ghazali A. R., Yusoff
author_facet	Hazwan, Syafiq A. M. N., Kamarizan M. F., Ghazali A. R., Yusoff
author_sort	Hazwan, Syafiq
title	Statistical Analysis of Deep Drilling Process Conditions Using Vibrations and Force Signals
title_short	Statistical Analysis of Deep Drilling Process Conditions Using Vibrations and Force Signals
title_full	Statistical Analysis of Deep Drilling Process Conditions Using Vibrations and Force Signals
title_fullStr	Statistical Analysis of Deep Drilling Process Conditions Using Vibrations and Force Signals
title_full_unstemmed	Statistical Analysis of Deep Drilling Process Conditions Using Vibrations and Force Signals
title_sort	statistical analysis of deep drilling process conditions using vibrations and force signals
publisher	EDP Sciences
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/14527/ http://umpir.ump.edu.my/id/eprint/14527/ http://umpir.ump.edu.my/id/eprint/14527/ http://umpir.ump.edu.my/id/eprint/14527/1/Statistical%20Analysis%20of%20Deep%20Drilling%20Process%20Conditions%20Using%20Vibrations.pdf
first_indexed	2018-09-07T01:55:32Z
last_indexed	2018-09-07T01:55:32Z
_version_	1610911928707710976

Statistical Analysis of Deep Drilling Process Conditions Using Vibrations and Force Signals

Similar Items