No Cover Image

Book chapter 782 views

Condition Monitoring in Micro-Injection Moulding

Christian Griffiths

Micro and Precision Manufacturing, Pages: 121 - 143

Swansea University Author: Christian Griffiths

Full text not available from this repository: check for access using links below.

Check full text

DOI (Published version): 10.1007/978-3-319-68801-5

Abstract

This chapter looks at the condition monitoring of the micro-injection moulding process (µ-IM). This manufacturing process has been applied successfully to a wide range of products in the micro-scale and is also an appropriate technology for manufacturing meso-parts with both micro- and nano-features...

Full description

Published in: Micro and Precision Manufacturing
ISBN: 9783319688008 9783319688015
ISSN: 1612-1317 1868-1212
Published: Cham Springer International Publishing 2018
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa52874
Tags: Add Tag
No Tags, Be the first to tag this record!
first_indexed 2019-11-26T13:15:41Z
last_indexed 2020-09-17T03:15:49Z
id cronfa52874
recordtype SURis
fullrecord <?xml version="1.0"?><rfc1807><datestamp>2019-11-26T08:56:21.9200334</datestamp><bib-version>v2</bib-version><id>52874</id><entry>2019-11-26</entry><title>Condition Monitoring in Micro-Injection Moulding</title><swanseaauthors><author><sid>84c202c256a2950fbc52314df6ec4914</sid><ORCID/><firstname>Christian</firstname><surname>Griffiths</surname><name>Christian Griffiths</name><active>true</active><ethesisStudent>false</ethesisStudent></author></swanseaauthors><date>2019-11-26</date><deptcode>GENG</deptcode><abstract>This chapter looks at the condition monitoring of the micro-injection moulding process (&#xB5;-IM). This manufacturing process has been applied successfully to a wide range of products in the micro-scale and is also an appropriate technology for manufacturing meso-parts with both micro- and nano-features. Improvement in the quality and the accuracy of parts made from polymers can be successfully achieved by determining the optimum conditions for replication. Process control in manufacturing is critical, and condition monitoring of &#xB5;-IM is a control method for improved understanding of the effects of selected parameter settings. This chapter reports on the condition monitoring methods used to improve the factors that affect part&#x2019;s quality. For each of the examples, the Taguchi design of experiments (DOE) method is used together with demonstrations of various experimental set-ups and the acquisition of data. The chapter advises on the obtainment of information regarding the behaviour of the &#xB5;-IM and the significant factors affecting the process. The selected case studies demonstrate the condition monitoring of the cavity pressure, forces, temperature distribution and air evacuation. For each, the research findings are discussed and conclusions are made.</abstract><type>Book chapter</type><journal>Micro and Precision Manufacturing</journal><paginationStart>121</paginationStart><paginationEnd>143</paginationEnd><publisher>Springer International Publishing</publisher><placeOfPublication>Cham</placeOfPublication><isbnPrint>9783319688008</isbnPrint><isbnElectronic>9783319688015</isbnElectronic><issnPrint>1612-1317</issnPrint><issnElectronic>1868-1212</issnElectronic><keywords/><publishedDay>1</publishedDay><publishedMonth>1</publishedMonth><publishedYear>2018</publishedYear><publishedDate>2018-01-01</publishedDate><doi>10.1007/978-3-319-68801-5</doi><url>http://dx.doi.org/10.1007/978-3-319-68801-5</url><notes/><college>COLLEGE NANME</college><department>General Engineering</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>GENG</DepartmentCode><institution>Swansea University</institution><apcterm/><lastEdited>2019-11-26T08:56:21.9200334</lastEdited><Created>2019-11-26T08:56:21.9200334</Created><authors><author><firstname>Christian</firstname><surname>Griffiths</surname><orcid/><order>1</order></author></authors><documents/><OutputDurs/></rfc1807>
spelling 2019-11-26T08:56:21.9200334 v2 52874 2019-11-26 Condition Monitoring in Micro-Injection Moulding 84c202c256a2950fbc52314df6ec4914 Christian Griffiths Christian Griffiths true false 2019-11-26 GENG This chapter looks at the condition monitoring of the micro-injection moulding process (µ-IM). This manufacturing process has been applied successfully to a wide range of products in the micro-scale and is also an appropriate technology for manufacturing meso-parts with both micro- and nano-features. Improvement in the quality and the accuracy of parts made from polymers can be successfully achieved by determining the optimum conditions for replication. Process control in manufacturing is critical, and condition monitoring of µ-IM is a control method for improved understanding of the effects of selected parameter settings. This chapter reports on the condition monitoring methods used to improve the factors that affect part’s quality. For each of the examples, the Taguchi design of experiments (DOE) method is used together with demonstrations of various experimental set-ups and the acquisition of data. The chapter advises on the obtainment of information regarding the behaviour of the µ-IM and the significant factors affecting the process. The selected case studies demonstrate the condition monitoring of the cavity pressure, forces, temperature distribution and air evacuation. For each, the research findings are discussed and conclusions are made. Book chapter Micro and Precision Manufacturing 121 143 Springer International Publishing Cham 9783319688008 9783319688015 1612-1317 1868-1212 1 1 2018 2018-01-01 10.1007/978-3-319-68801-5 http://dx.doi.org/10.1007/978-3-319-68801-5 COLLEGE NANME General Engineering COLLEGE CODE GENG Swansea University 2019-11-26T08:56:21.9200334 2019-11-26T08:56:21.9200334 Christian Griffiths 1
title Condition Monitoring in Micro-Injection Moulding
spellingShingle Condition Monitoring in Micro-Injection Moulding
Christian Griffiths
title_short Condition Monitoring in Micro-Injection Moulding
title_full Condition Monitoring in Micro-Injection Moulding
title_fullStr Condition Monitoring in Micro-Injection Moulding
title_full_unstemmed Condition Monitoring in Micro-Injection Moulding
title_sort Condition Monitoring in Micro-Injection Moulding
author_id_str_mv 84c202c256a2950fbc52314df6ec4914
author_id_fullname_str_mv 84c202c256a2950fbc52314df6ec4914_***_Christian Griffiths
author Christian Griffiths
author2 Christian Griffiths
format Book chapter
container_title Micro and Precision Manufacturing
container_start_page 121
publishDate 2018
institution Swansea University
isbn 9783319688008
9783319688015
issn 1612-1317
1868-1212
doi_str_mv 10.1007/978-3-319-68801-5
publisher Springer International Publishing
url http://dx.doi.org/10.1007/978-3-319-68801-5
document_store_str 0
active_str 0
description This chapter looks at the condition monitoring of the micro-injection moulding process (µ-IM). This manufacturing process has been applied successfully to a wide range of products in the micro-scale and is also an appropriate technology for manufacturing meso-parts with both micro- and nano-features. Improvement in the quality and the accuracy of parts made from polymers can be successfully achieved by determining the optimum conditions for replication. Process control in manufacturing is critical, and condition monitoring of µ-IM is a control method for improved understanding of the effects of selected parameter settings. This chapter reports on the condition monitoring methods used to improve the factors that affect part’s quality. For each of the examples, the Taguchi design of experiments (DOE) method is used together with demonstrations of various experimental set-ups and the acquisition of data. The chapter advises on the obtainment of information regarding the behaviour of the µ-IM and the significant factors affecting the process. The selected case studies demonstrate the condition monitoring of the cavity pressure, forces, temperature distribution and air evacuation. For each, the research findings are discussed and conclusions are made.
published_date 2018-01-01T04:05:30Z
_version_ 1763753413248548864
score 11.013082

Similar Items