Using market preference analytics to maximise plant utilisation leading to flexible manufacturing system design and operations in the FMCG industry

dc.contributor.authorVuyelwa, William Khanyiso
dc.date.accessioned2022-10-04T13:00:32Z
dc.date.available2022-10-04T13:00:32Z
dc.date.issued2021
dc.descriptionA research report submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Master of Science in Engineering. 2021en_ZA
dc.description.abstractThis Delphi Study’s main thrust is to investigate market preference and equipment management data, i.e., big data in product development. Subsequently, testing how linking these to flexible manufacturing systems design and operations can maximise plant utilisation in the FMCG industry. In this sequential exploratory mixed methods inquiry with sixteen (16) panellists, a framework that links big data to maximised plant utilisation, through twelve (12) hypotheses is tested. The study suggests that the results are in line with extant literature on the investigated constructs and linkages. The findings strengthen extant literature and contribute empirical evidence to applying big data in the supply chain and product lifecycle management work-processes. The results confirm big data’s potential to improve collaboration across the investigated value chain. The findings of this research have regulatory implications for government, strategy implications for practitioners and research implications for academiaen_ZA
dc.description.librarianCK2022en_ZA
dc.facultyFaculty of Engineering and the Built Environmenten_ZA
dc.identifier.urihttps://hdl.handle.net/10539/33380
dc.language.isoenen_ZA
dc.schoolSchool of Mechanical, Industrial, and Aeronautical Engineeringen_ZA
dc.titleUsing market preference analytics to maximise plant utilisation leading to flexible manufacturing system design and operations in the FMCG industryen_ZA
dc.typeThesisen_ZA

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