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dc.contributor.advisorStrandhagen, Jan Ola
dc.contributor.advisorSgarbossa, Fabio
dc.contributor.advisorSemini, Marco
dc.contributor.authorOluyisola, Olumide Emmanuel
dc.date.accessioned2021-06-18T14:04:34Z
dc.date.available2021-06-18T14:04:34Z
dc.date.issued2021
dc.identifier.isbn978-82-326-6785-7
dc.identifier.issn2703-8084
dc.identifier.urihttps://hdl.handle.net/11250/2760217
dc.language.isoengen_US
dc.publisherNTNUen_US
dc.relation.ispartofseriesDoctoral theses at NTNU;2021:202
dc.relation.haspartPaper 1: Oluyisola, Olumide Emmanuel; Strandhagen, Jo Wessel; Buer, Sven-Vegard. RFId technology in the manufacture of customized drainage and piping systems: a case study. IFAC-PapersOnLine 2018 ;Volum 51.(11) s. 364-369 https://doi.org/10.1016/j.ifacol.2018.08.320en_US
dc.relation.haspartPaper 2: Oluyisola, Olumide Emmanuel; Salmi, Tuomo Eero Olavi; Strandhagen, Jan Ola. Causes of Delivery-Time Variance in Maritime-Equipment Manufacturing Supply-Chains: An Empirical Study. IFIP Advances in Information and Communication Technology 2018 ;Volum 535. s. 415-421 https://doi.org/10.1007/978-3-319-99704-9_51en_US
dc.relation.haspartPaper 3: Høyer, Madeleine Ruiz; Oluyisola, Olumide Emmanuel; Strandhagen, Jan Ola; Semini, Marco. Exploring the challenges with applying tracking and tracing technology in the dairy industry. IFAC-PapersOnLine 2019 ;Volum 52.(13) s. 1727-1732 https://doi.org/10.1016/j.ifacol.2019.11.450en_US
dc.relation.haspartPaper 4: Oluyisola, Olumide Emmanuel; Sgarbossa, Fabio; Strandhagen, Jan Ola. Smart Production Planning and Control: Concept, Use-Cases and Sustainability Implications. Sustainability 2020 ;Volum 12.(9) https://doi.org/10.3390/su12093791 This is an open access article distributed under the Creative Commons Attribution License (CC BY 4.0)en_US
dc.relation.haspartPaper 5: Oluyisola, O. E.; Bhalla, S.; Sgarbossa, F.; Strandhagen, J. O. Designing and Developing Smart Production Planning and Control Systems in the Industry 4.0 Era: A Methodology and Case Study.
dc.titleTowards Smart Production Planning and Control: Frameworks and case studies investigating the enhancement of production planning and control using internet-of-things, data analytics and machine learningen_US
dc.typeDoctoral thesisen_US
dc.subject.nsiVDP::Technology: 500::Mechanical engineering: 570en_US


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