A Unit Manufacturing Process Characterization Methodology and Supporting Terminology for Sustainable Manufacturing Assessment Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/7p88ck55j

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  • Manufacturing industry drives economic activity and growth around the world, but manufacturing activities consume large amounts of material, energy, and labor resources. Therefore, the impacts of manufacturing need to be accounted for and reduced. Direct benefits of manufacturing are products and income, which, in turn, influence the lives of people in the local community and the consumers purchasing the manufactured products. The design process for products and requisite manufacturing facilities should incorporate environmental and social criteria in addition to economic criteria to more comprehensively assess sustainability performance. Sustainability assessments for manufactured products and manufacturing facilities can be carried out by assessing the incremental elements of manufacturing industry, which are unit manufacturing processes (UMPs). A challenge in the research area is that current methods for UMP assessment are ad hoc and the methods do not incorporate the system as a whole. The purpose of this research is to enable sustainable manufacturing decision making by 1) unifying an assessment methodology for UMPs, 2) developing an information modeling framework for characterizing UMPs and workpieces, and 3) demonstrating UMP composability (connectivity) modeling for use in sustainability assessments. The methodology is developed through literature review, and unifies 23 different UMP manufacturing assessment methods by analyzing each for overlapping and unique steps in the approaches. Thus, a nine-step assessment methodology emerged, which has multiple applications in industry, including process and facility assessment and improvement. A next step for MPF modeling is to link UMP models by modeling the workpiece state, but supporting tools were need to identifying how to correctly model the interactions between the UMP and the workpiece. The information modeling framework developed herein provides the theoretical background for how UMP models interact by linking the function of the UMP to the effect on the workpiece and by identifying the calculation variables necessary to assess UMPs. The information modeling framework developed for composing UMP models is demonstrated through the energy analysis of a metal component. The component is manufactured by recrystallization annealing, reducing (milling), through hardening, and recovery annealing (tempering). Models are composed (connected) by utilizing knowledge of how UMPs impart transformation to the workpiece and the information embedded in the workpiece that is transported to subsequent UMPs. Workpiece information includes the geometry and properties of the current state and future states. Previous work reported in literature has focused on geometry modeling (e.g. CAD, CAM), while this work focuses on property modeling. This research develops an overarching detailed approach to manufacturing sustainability assessments through in-depth analysis of UMPs. The result of using this UMP approach will provide guidance toward a more sustainable future.
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  • description.provenance : Rejected by Julie Kurtz(julie.kurtz@oregonstate.edu), reason: Rejecting because there are two page 60's, one is table 3.1 and the other starts with 3.4.1. Also I noticed you have a blank page between chapters except for before chapter 5. Usually it's best not to have blank pages but if you want to keep it before each chapter then add a blank page before chapter 5. Once revised, log back into ScholarsArchive and go to the upload page. Replace the attached file with the revised file and resubmit. Thanks, Julie on 2015-09-09T16:45:27Z (GMT)
  • description.provenance : Submitted by Ian Garretson (garretsi@onid.orst.edu) on 2015-09-09T18:06:41Z No. of bitstreams: 2 Thesis_2015.09.09.pdf: 1889112 bytes, checksum: 2931cf5e5b3e81312b93f8d98360199e (MD5) license_rdf: 1232 bytes, checksum: bb87e2fb4674c76d0d2e9ed07fbb9c86 (MD5)
  • description.provenance : Approved for entry into archive by Laura Wilson(laura.wilson@oregonstate.edu) on 2015-09-16T16:23:36Z (GMT) No. of bitstreams: 2 Thesis_2015.09.09.pdf: 1889112 bytes, checksum: 2931cf5e5b3e81312b93f8d98360199e (MD5) license_rdf: 1232 bytes, checksum: bb87e2fb4674c76d0d2e9ed07fbb9c86 (MD5)
  • description.provenance : Approved for entry into archive by Julie Kurtz(julie.kurtz@oregonstate.edu) on 2015-09-09T18:21:35Z (GMT) No. of bitstreams: 2 Thesis_2015.09.09.pdf: 1889112 bytes, checksum: 2931cf5e5b3e81312b93f8d98360199e (MD5) license_rdf: 1232 bytes, checksum: bb87e2fb4674c76d0d2e9ed07fbb9c86 (MD5)
  • description.provenance : Made available in DSpace on 2015-09-16T16:23:36Z (GMT). No. of bitstreams: 2 Thesis_2015.09.09.pdf: 1889112 bytes, checksum: 2931cf5e5b3e81312b93f8d98360199e (MD5) license_rdf: 1232 bytes, checksum: bb87e2fb4674c76d0d2e9ed07fbb9c86 (MD5) Previous issue date: 2015-08-28
  • description.provenance : Submitted by Ian Garretson (garretsi@onid.orst.edu) on 2015-09-04T19:49:32Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: bb87e2fb4674c76d0d2e9ed07fbb9c86 (MD5) Thesis_2015.09.04.pdf: 1888174 bytes, checksum: 2556ab1e5b31fa5f7ec985b1a5c0cfde (MD5)

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