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Intelligent manufacturing eco-system: A post COVID-19 recovery and growth opportunity for manufacturing industry in Sub-Saharan countries.
Mezgebe, Tsegay T; Gebreslassie, Mulualem G; Sibhato, Hailekiros; Bahta, Solomon T.
  • Mezgebe TT; Manufacturing Engineering Chair, Ethiopian Institute of Technology-Mekelle, Mekelle University, P.O.Box 231, Mekelle, Ethiopia.
  • Gebreslassie MG; Center of Energy, Ethiopian Institute of Technology-Mekelle, Mekelle University, P.O.Box 231, Mekelle, Ethiopia.
  • Sibhato H; Industrial Systems Chair, Ethiopian Institute of Technology-Mekelle, Mekelle University, P.O.Box 231, Mekelle, Ethiopia.
  • Bahta ST; Center of Energy, Ethiopian Institute of Technology-Mekelle, Mekelle University, P.O.Box 231, Mekelle, Ethiopia.
Sci Afr ; 19: e01547, 2023 Mar.
Article in English | MEDLINE | ID: covidwho-2165828
ABSTRACT
The lagging behind intelligent technologies and the COVID-19 pandemic together have impacted the emerging economy particularly the manufacturing sector in sub-Saharan countries. This paper systematically discusses intelligent manufacturing technologies with an aim to map out their importance and industrial applicability and to show their significance to contain COVID-19 pandemic. Intelligent Manufacturing Systems (IMS) is then adapted as a post COVID-19 recovery and growth opportunity to ensemble to production processes of manufacturing industry in the sub-Saharan countries. Proposition of a Triple Helix Collaboration Eco-system that delineate a recursive contribution of Government(s), academia, and industry accompanies the IMS adoption. The intention is to shape the existing industrial challenges through networking in the area of intelligence technologies. While proposing the Eco-system, a post COVID-19 recovery and growth opportunity and intra-Africa scientific collaborations are taken into account.
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Full text: Available Collection: International databases Database: MEDLINE Topics: Long Covid Language: English Journal: Sci Afr Year: 2023 Document Type: Article Affiliation country: J.sciaf.2023.e01547

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Full text: Available Collection: International databases Database: MEDLINE Topics: Long Covid Language: English Journal: Sci Afr Year: 2023 Document Type: Article Affiliation country: J.sciaf.2023.e01547