Adoption of Industry 4.0 for Sustainable Manufacturing
A Master of Science thesis in Mechanical Engineering by Parham Dadash Pour entitled, “Adoption of Industry 4.0 for Sustainable Manufacturing”, submitted in April 2022. Thesis advisor is Dr. Mohammad Nazzal and thesis co-advisor is Dr. Basil Darras. Soft copy is available (Thesis, Completion Certific...
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| Format: | doctoralThesis |
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2022
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| Online Access: | http://hdl.handle.net/11073/24103 |
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| _version_ | 1864513444552638464 |
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| author | Pour, Parham Dadash |
| author_facet | Pour, Parham Dadash |
| author_role | author |
| dc.contributor.none.fl_str_mv | Nazzal, Mohammad Darras, Basil |
| dc.creator.none.fl_str_mv | Pour, Parham Dadash |
| dc.date.none.fl_str_mv | 2022-09-12T09:10:54Z 2022-09-12T09:10:54Z 2022-04 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | 35.232-2022.23 http://hdl.handle.net/11073/24103 |
| dc.language.none.fl_str_mv | en_US |
| dc.subject.none.fl_str_mv | Industry 4.0 Multi-Criteria Decision Making Sustainable Manufacturing Fuzzy Logic Technology Selection |
| dc.title.none.fl_str_mv | Adoption of Industry 4.0 for Sustainable Manufacturing |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/doctoralThesis |
| description | A Master of Science thesis in Mechanical Engineering by Parham Dadash Pour entitled, “Adoption of Industry 4.0 for Sustainable Manufacturing”, submitted in April 2022. Thesis advisor is Dr. Mohammad Nazzal and thesis co-advisor is Dr. Basil Darras. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form). |
| format | doctoralThesis |
| id | aus_db09b01d26e42992f61884432bdfdd51 |
| identifier_str_mv | 35.232-2022.23 |
| language_invalid_str_mv | en_US |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/24103 |
| publishDate | 2022 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
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| spelling | Adoption of Industry 4.0 for Sustainable ManufacturingPour, Parham DadashIndustry 4.0Multi-Criteria Decision MakingSustainable ManufacturingFuzzy LogicTechnology SelectionA Master of Science thesis in Mechanical Engineering by Parham Dadash Pour entitled, “Adoption of Industry 4.0 for Sustainable Manufacturing”, submitted in April 2022. Thesis advisor is Dr. Mohammad Nazzal and thesis co-advisor is Dr. Basil Darras. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The Fourth Industrial Revolution (Industry 4.0) intends to help different industries monitor, control, and run their production systems efficiently. Most of the currently available Industry 4.0 implementation frameworks focus on providing users with an implementation plan that do not include information regarding technology selection or readiness assessment. In this work, a comprehensive Industry 4.0 implementation framework is developed to help manufacturing firms improve their current state of production. The framework developed consists of five main stages. These stages are gap analysis, Industry 4.0 technology selection, Industry 4.0 readiness assessment, Industry 4.0 reference architecture selection, and pilot project assessment. An Industry 4.0 technology selection model is developed that uses Fuzzy Analytical Hierarchy Process (FAHP) to assign weights to the production, social, economic, and environmental indicators. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) is used to aggregate the results and rank the technology alternatives based on their scores. Furthermore, a novel Industry 4.0 readiness tool is developed to assess how capable the facility is to implement Industry 4.0 technologies. A case study was carried out by applying the developed Industry 4.0 technology selection and readiness assessment procedures on an aluminium extrusion factory. Cyber-Physical Systems, Big Data Analytics, and Autonomous/Industrial Robots were the top three ranked technologies to be implemented having closeness coefficient scores of 0.964, 0.928, and 0.601, respectively. The firm obtained a readiness score of 45.8% based on the developed readiness assessment model revealing that the firm is at an intermediate readiness level.College of EngineeringDepartment of Mechanical EngineeringMaster of Science in Mechanical Engineering (MSME)Nazzal, MohammadDarras, Basil2022-09-12T09:10:54Z2022-09-12T09:10:54Z2022-04info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2022.23http://hdl.handle.net/11073/24103en_USoai:repository.aus.edu:11073/241032025-06-26T12:36:18Z |
| spellingShingle | Adoption of Industry 4.0 for Sustainable Manufacturing Pour, Parham Dadash Industry 4.0 Multi-Criteria Decision Making Sustainable Manufacturing Fuzzy Logic Technology Selection |
| status_str | publishedVersion |
| title | Adoption of Industry 4.0 for Sustainable Manufacturing |
| title_full | Adoption of Industry 4.0 for Sustainable Manufacturing |
| title_fullStr | Adoption of Industry 4.0 for Sustainable Manufacturing |
| title_full_unstemmed | Adoption of Industry 4.0 for Sustainable Manufacturing |
| title_short | Adoption of Industry 4.0 for Sustainable Manufacturing |
| title_sort | Adoption of Industry 4.0 for Sustainable Manufacturing |
| topic | Industry 4.0 Multi-Criteria Decision Making Sustainable Manufacturing Fuzzy Logic Technology Selection |
| url | http://hdl.handle.net/11073/24103 |