{"id":{"repo_id":"nott-trent","oai_identifier":"oai:irep.ntu.ac.uk:7"},"canonical_url":"https://search.dev.ndltd.org/etd/nott-trent/oai:irep.ntu.ac.uk:7","repository":{"repo_id":"nott-trent","name":"Nottingham Trent University","base_url":"https://irep.ntu.ac.uk/cgi/oai2"},"display":{"title":"Investigation into the effect of fixturing systems on the design of condition monitoring for machining operations","abstract":"The global market competition has drawn the manufacturer’s attention on automated manufacturing processes using condition monitoring systems. These systems have been used for improving product quality, eliminating inspection, and enhancing manufacturing productivity. Fixtures are essential devices in machining processes to hold the tool or workpiece, hence they are influenced directly by the stability of the cutting tool. Therefore, tool and fixturing faults play an important part in the inaccuracy of the machining processes causing deterioration of surface roughness. For the above mentioned reasons, and the limited work in this domain, this thesis develops an experimental investigation to evaluate the effect of fixturing quality on the design of condition monitoring systems. The proposed monitoring system implements multisensors and signal processing methods able to analyse the sensory information and make an appropriate decision. Therefore, several sensors namely force, vibration, acoustic emission, eddy current, power, strain and sound, are combined with a newly suggested approach, named Taylor’s Equation Induced Pattern (TIP), and neural networks to detect tool wear and tool breakage. It also evaluates the monitoring system to provide valuable data to show the effect of fixturing quality. Surface roughness of the workpiece has been measured and compared with the sensitivity of the monitoring system, which reflects the state of tool and fixturing conditions.","abstract_html":"The global market competition has drawn the manufacturer’s attention on automated manufacturing processes using condition monitoring systems. These systems have been used for improving product quality, eliminating inspection, and enhancing manufacturing productivity. Fixtures are essential devices in machining processes to hold the tool or workpiece, hence they are influenced directly by the stability of the cutting tool. Therefore, tool and fixturing faults play an important part in the inaccuracy of the machining processes causing deterioration of surface roughness. For the above mentioned reasons, and the limited work in this domain, this thesis develops an experimental investigation to evaluate the effect of fixturing quality on the design of condition monitoring systems. The proposed monitoring system implements multisensors and signal processing methods able to analyse the sensory information and make an appropriate decision. Therefore, several sensors namely force, vibration, acoustic emission, eddy current, power, strain and sound, are combined with a newly suggested approach, named Taylor’s Equation Induced Pattern (TIP), and neural networks to detect tool wear and tool breakage. It also evaluates the monitoring system to provide valuable data to show the effect of fixturing quality. Surface roughness of the workpiece has been measured and compared with the sensitivity of the monitoring system, which reflects the state of tool and fixturing conditions.","abstract_has_math":false,"creators":["Abbas, JK"],"institution":"Nottingham Trent University","degree_name":"phd","degree_level":"doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013","date_published":"2013","updated_at":"2026-07-24T06:30:42Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Abbas, JK"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2013"]},{"key":"dc:date.issued","label":"Date","values":["2013"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["Nottingham Trent University"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://irep.ntu.ac.uk/id/eprint/7/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["phd"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://irep.ntu.ac.uk/id/eprint/7/1/216973_PHD%2520THESIS%2520-Jabbar%2520Abbas-Final%2520July%25202013.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The global market competition has drawn the manufacturer’s attention on automated manufacturing processes using condition monitoring systems. These systems have been used for improving product quality, eliminating inspection, and enhancing manufacturing productivity. Fixtures are essential devices in machining processes to hold the tool or workpiece, hence they are influenced directly by the stability of the cutting tool. Therefore, tool and fixturing faults play an important part in the inaccuracy of the machining processes causing deterioration of surface roughness. For the above mentioned reasons, and the limited work in this domain, this thesis develops an experimental investigation to evaluate the effect of fixturing quality on the design of condition monitoring systems. The proposed monitoring system implements multisensors and signal processing methods able to analyse the sensory information and make an appropriate decision. Therefore, several sensors namely force, vibration, acoustic emission, eddy current, power, strain and sound, are combined with a newly suggested approach, named Taylor’s Equation Induced Pattern (TIP), and neural networks to detect tool wear and tool breakage. It also evaluates the monitoring system to provide valuable data to show the effect of fixturing quality. Surface roughness of the workpiece has been measured and compared with the sensitivity of the monitoring system, which reflects the state of tool and fixturing conditions."]},{"key":"dc:format","label":"Dc Format","values":["text"]},{"key":"dc:title","label":"Title","values":["Investigation into the effect of fixturing systems on the design of condition monitoring for machining operations"]}]}],"canonical_facts":{"dc:creator":["Abbas, JK"],"dc:date":["2013"],"dc:date.issued":["2013"],"dc:description.abstract":["The global market competition has drawn the manufacturer’s attention on automated manufacturing processes using condition monitoring systems. These systems have been used for improving product quality, eliminating inspection, and enhancing manufacturing productivity. Fixtures are essential devices in machining processes to hold the tool or workpiece, hence they are influenced directly by the stability of the cutting tool. Therefore, tool and fixturing faults play an important part in the inaccuracy of the machining processes causing deterioration of surface roughness. For the above mentioned reasons, and the limited work in this domain, this thesis develops an experimental investigation to evaluate the effect of fixturing quality on the design of condition monitoring systems. The proposed monitoring system implements multisensors and signal processing methods able to analyse the sensory information and make an appropriate decision. Therefore, several sensors namely force, vibration, acoustic emission, eddy current, power, strain and sound, are combined with a newly suggested approach, named Taylor’s Equation Induced Pattern (TIP), and neural networks to detect tool wear and tool breakage. It also evaluates the monitoring system to provide valuable data to show the effect of fixturing quality. Surface roughness of the workpiece has been measured and compared with the sensitivity of the monitoring system, which reflects the state of tool and fixturing conditions."],"dc:format":["text"],"dc:identifier.uri":["https://irep.ntu.ac.uk/id/eprint/7/1/216973_PHD%2520THESIS%2520-Jabbar%2520Abbas-Final%2520July%25202013.pdf"],"dc:language":["en"],"dc:publisher.institution":["Nottingham Trent University"],"dc:relation.isreferencedby":["https://irep.ntu.ac.uk/id/eprint/7/"],"dc:title":["Investigation into the effect of fixturing systems on the design of condition monitoring for machining operations"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["phd"]},"updated_at":"2026-07-24T06:30:42Z"}