{"id":{"repo_id":"cambridge","oai_identifier":"oai:www.repository.cam.ac.uk:1810/370039"},"canonical_url":"https://search.dev.ndltd.org/etd/cambridge/oai:www.repository.cam.ac.uk:1810/370039","repository":{"repo_id":"cambridge","name":"Cambridge University","base_url":"https://api.repository.cam.ac.uk/server/oai/request"},"display":{"title":"How to visualise energy waste in manufacturing","abstract":"In response to global climate change, various governments, organisations, companies, and other stakeholders have set “Net-Zero” targets. This has led manufacturing firms to focus on improving the energy efficiency of their production systems. A critical aspect of this is reducing unnecessary energy consumption, namely energy waste. However, a clear definition and classification of energy waste in both academic and industrial contexts has been lacking. Following Design Research Methodology (DRM) and adopting case studies, this research aims to address the main research question: How to visualise energy waste in manufacturing? Initially, the study establishes a definition of “energy waste” through a literature review. It concludes that energy waste should be viewed from three perspectives: management, technology, and design. Subsequent case studies across 27 factories in 6 countries led to a refined definition: “The difference between the actual energy consumption of a production system and its theoretical minimum required to fulfil users’ needs”. Furthermore, the research establishes an energy waste framework that categorises 13 types of energy waste into four main groups. Moreover, this research also investigates why energy waste often remains invisible, identifying 16 key reasons and establishing a mechanism that explains this invisibility at four different levels. Based on these findings, this research further developed a tool for visualising energy waste, designed to help manufacturers identify and reduce such waste. The design principles and underlying methodology of the tool can effectively guide practitioners in recognising energy waste, particularly in the context of the digital era. This research not only provides a comprehensive strategy for understanding and reducing energy waste but also has significant practical implications. A preliminary estimate suggests that by addressing energy waste, the global manufacturing sector could reduce its energy consumption by up to 5%, without substantial investment. Future research directions include conducting quantative studies on energy waste, encompassing: the measurement of energy waste and a deeper analysis of the reasons behind its invisibility; and the expansion of the concept of energy waste to the level of the supply chain and even the entire lifecycle.","abstract_html":"In response to global climate change, various governments, organisations, companies, and other stakeholders have set “Net-Zero” targets. This has led manufacturing firms to focus on improving the energy efficiency of their production systems. A critical aspect of this is reducing unnecessary energy consumption, namely energy waste. However, a clear definition and classification of energy waste in both academic and industrial contexts has been lacking. Following Design Research Methodology (DRM) and adopting case studies, this research aims to address the main research question: How to visualise energy waste in manufacturing? Initially, the study establishes a definition of “energy waste” through a literature review. It concludes that energy waste should be viewed from three perspectives: management, technology, and design. Subsequent case studies across 27 factories in 6 countries led to a refined definition: “The difference between the actual energy consumption of a production system and its theoretical minimum required to fulfil users’ needs”. Furthermore, the research establishes an energy waste framework that categorises 13 types of energy waste into four main groups. Moreover, this research also investigates why energy waste often remains invisible, identifying 16 key reasons and establishing a mechanism that explains this invisibility at four different levels. Based on these findings, this research further developed a tool for visualising energy waste, designed to help manufacturers identify and reduce such waste. The design principles and underlying methodology of the tool can effectively guide practitioners in recognising energy waste, particularly in the context of the digital era. This research not only provides a comprehensive strategy for understanding and reducing energy waste but also has significant practical implications. A preliminary estimate suggests that by addressing energy waste, the global manufacturing sector could reduce its energy consumption by up to 5%, without substantial investment. Future research directions include conducting quantative studies on energy waste, encompassing: the measurement of energy waste and a deeper analysis of the reasons behind its invisibility; and the expansion of the concept of energy waste to the level of the supply chain and even the entire lifecycle.","abstract_has_math":false,"creators":["Geng, Duanyang"],"institution":"University of Cambridge","degree_name":"Doctor of Philosophy (PhD)","degree_level":"Doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Evans, Stephen"],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-12-06","date_published":"2023-12-06","updated_at":"2026-07-22T22:23:53Z","subjects":["Energy efficiency","Energy saving","Energy waste","Manufacturing","Visualisation"],"languages":["eng"],"rights":[],"rights_urls":["https://www.repository.cam.ac.uk/bitstreams/822cb279-aca1-48b8-8d78-04a7c1bfa9b7/download","https://www.rioxx.net/licenses/all-rights-reserved/"],"identifier_entries":[]},"links":{"outbound_url":"https://doi.org/10.17863/CAM.109623","outbound_label":"DOI","outbound_source":"dc:identifier.doi"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Evans, Stephen"]},{"key":"dc:creator","label":"Author","values":["Geng, Duanyang"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.issued","label":"Date","values":["2023-12-06"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Cambridge"]},{"key":"dc:relation.isreferencedby.uri","label":"Dc Relation Isreferencedby URI","values":["https://www.repository.cam.ac.uk/handle/1810/370039"]},{"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":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Energy efficiency","Energy saving","Energy waste","Manufacturing","Visualisation"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["https://www.repository.cam.ac.uk/bitstreams/822cb279-aca1-48b8-8d78-04a7c1bfa9b7/download","https://www.rioxx.net/licenses/all-rights-reserved/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.doi","label":"DOI","values":["https://doi.org/10.17863/CAM.109623"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://www.repository.cam.ac.uk/bitstreams/9b55bcdc-e0e1-4c44-a8cb-258bc06f4a07/download"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In response to global climate change, various governments, organisations, companies, and other stakeholders have set “Net-Zero” targets. 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Furthermore, the research establishes an energy waste framework that categorises 13 types of energy waste into four main groups. Moreover, this research also investigates why energy waste often remains invisible, identifying 16 key reasons and establishing a mechanism that explains this invisibility at four different levels. Based on these findings, this research further developed a tool for visualising energy waste, designed to help manufacturers identify and reduce such waste. The design principles and underlying methodology of the tool can effectively guide practitioners in recognising energy waste, particularly in the context of the digital era. This research not only provides a comprehensive strategy for understanding and reducing energy waste but also has significant practical implications. A preliminary estimate suggests that by addressing energy waste, the global manufacturing sector could reduce its energy consumption by up to 5%, without substantial investment. Future research directions include conducting quantative studies on energy waste, encompassing: the measurement of energy waste and a deeper analysis of the reasons behind its invisibility; and the expansion of the concept of energy waste to the level of the supply chain and even the entire lifecycle."]},{"key":"dc:format.checksum.md5","label":"Dc Format Checksum Md5","values":["5886466767e67801e85ae0516d93eb21","87eda9de84448d1f82354d60eee3eb5f"]},{"key":"dc:title","label":"Title","values":["How to visualise energy waste in manufacturing"]}]}],"canonical_facts":{"dc:contributor.advisor":["Evans, Stephen"],"dc:creator":["Geng, Duanyang"],"dc:date.issued":["2023-12-06"],"dc:description.abstract":["In response to global climate change, various governments, organisations, companies, and other stakeholders have set “Net-Zero” targets. This has led manufacturing firms to focus on improving the energy efficiency of their production systems. 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Moreover, this research also investigates why energy waste often remains invisible, identifying 16 key reasons and establishing a mechanism that explains this invisibility at four different levels. Based on these findings, this research further developed a tool for visualising energy waste, designed to help manufacturers identify and reduce such waste. The design principles and underlying methodology of the tool can effectively guide practitioners in recognising energy waste, particularly in the context of the digital era. This research not only provides a comprehensive strategy for understanding and reducing energy waste but also has significant practical implications. A preliminary estimate suggests that by addressing energy waste, the global manufacturing sector could reduce its energy consumption by up to 5%, without substantial investment. 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