{"id":{"repo_id":"qu-belfast","oai_identifier":"oai:pure.qub.ac.uk/portal:studenttheses/7876bc81-ad30-453a-9176-4e3549156ec1"},"canonical_url":"https://search.dev.ndltd.org/etd/qu-belfast/oai:pure.qub.ac.uk/portal:studenttheses/7876bc81-ad30-453a-9176-4e3549156ec1","repository":{"repo_id":"qu-belfast","name":"Queen's University Belfast","base_url":"https://pureadmin.qub.ac.uk/ws/oai"},"display":{"title":"A hybrid framework for the design of production systems combining simulation and optimisation methods","abstract":"To address the challenges in modern industries and to improve Industry 4.0 capability, digitalised design methods and solutions need to be more integrated and self-adaptive. However, current approaches for production design methods that can provide adaptive design and planning for manufacturing systems in line with the challenges in Industry 4.0.<br/><br/>The core problem in designing and planning for manufacturing systems in this project is the assembly line balancing problem (ALBP), together with other aspects of a production system, have bee studied by simulation and optimisation techniques. In existing methods, both simulation and optimisation methods and tools have been developed for the focused problem, however, there are still great challenges to overcome.<br/>","abstract_html":"To address the challenges in modern industries and to improve Industry 4.0 capability, digitalised design methods and solutions need to be more integrated and self-adaptive. However, current approaches for production design methods that can provide adaptive design and planning for manufacturing systems in line with the challenges in Industry 4.0.&lt;br/&gt;&lt;br/&gt;The core problem in designing and planning for manufacturing systems in this project is the assembly line balancing problem (ALBP), together with other aspects of a production system, have bee studied by simulation and optimisation techniques. In existing methods, both simulation and optimisation methods and tools have been developed for the focused problem, however, there are still great challenges to overcome.&lt;br/&gt;","abstract_has_math":false,"creators":["Li, Shuang"],"institution":"Queen's University Belfast","degree_name":"Doctor of Philosophy","degree_level":"Doctoral Thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Murphy, Adrian","Butterfield, Joseph"],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-7","date_published":"2022-7","updated_at":"2026-07-24T03:56:18Z","subjects":["Simulation","optimisation","genetic algorithm","discrete event simulation","Industry 4.0","line balancing","digital manufacturing"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:pure.qub.ac.uk/portal:studenttheses/7876bc81-ad30-453a-9176-4e3549156ec1"],"render_values":[{"text":"oai:pure.qub.ac.uk/portal:studenttheses/7876bc81-ad30-453a-9176-4e3549156ec1","href":null,"code":true}]}]},"links":{"outbound_url":"https://pure.qub.ac.uk/en/studentTheses/7876bc81-ad30-453a-9176-4e3549156ec1","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Murphy, Adrian","Butterfield, Joseph"]},{"key":"dc:creator","label":"Author","values":["Li, Shuang"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-7"]},{"key":"dc:date.issued","label":"Date","values":["2022-7"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["School of Mechanical and Aerospace Engineering"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["Queen's University Belfast"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://pure.qub.ac.uk/en/studentTheses/7876bc81-ad30-453a-9176-4e3549156ec1"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Doctoral Thesis"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Doctor of Philosophy"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Simulation","optimisation","genetic algorithm","discrete event simulation","Industry 4.0","line balancing","digital manufacturing"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights.embargodate","label":"Dc Rights Embargodate","values":["2022-03-04"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:pure.qub.ac.uk/portal:studenttheses/7876bc81-ad30-453a-9176-4e3549156ec1","https://pure.qub.ac.uk/en/studentTheses/7876bc81-ad30-453a-9176-4e3549156ec1"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://pure.qub.ac.uk/files/293538501/Thesis_Submit.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["To address the challenges in modern industries and to improve Industry 4.0 capability, digitalised design methods and solutions need to be more integrated and self-adaptive. However, current approaches for production design methods that can provide adaptive design and planning for manufacturing systems in line with the challenges in Industry 4.0.<br/><br/>The core problem in designing and planning for manufacturing systems in this project is the assembly line balancing problem (ALBP), together with other aspects of a production system, have bee studied by simulation and optimisation techniques. In existing methods, both simulation and optimisation methods and tools have been developed for the focused problem, however, there are still great challenges to overcome.<br/>"]},{"key":"dc:title","label":"Title","values":["A hybrid framework for the design of production systems combining simulation and optimisation methods"]}]}],"canonical_facts":{"dc:contributor.advisor":["Murphy, Adrian","Butterfield, Joseph"],"dc:creator":["Li, Shuang"],"dc:date":["2022-7"],"dc:date.issued":["2022-7"],"dc:description.abstract":["To address the challenges in modern industries and to improve Industry 4.0 capability, digitalised design methods and solutions need to be more integrated and self-adaptive. 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