Abstract
Artificial Intelligence (AI) in manufacturing has received significant attention in recent years due to its potential to assist manufacturing teams in monitoring projects, identifying defects and potential risks, and improving complex workflows and processes. Traditionally, manufacturing projects have been highly knowledge intensive, involving security-conscious processes, and internal and external actors. As AI solutions become more cost-effective and are deployed as assistive tools to support teams in projects, their deployment in manufacturing can be realized. This paper presents a conceptual framework that introduces how AI can enhance the efficiency of manufacturing projects and be successfully applied to projects. A review of extant literature on AI in manufacturing projects is presented and an empirical investigation with 10 manufacturing project managers and AI subject matter experts from engineering organizations in the UK is given. The proposed framework outlines how AI can be applied to manufacturing projects, encompassing both the necessities of projects for the application of AI, and the necessities of AI for their in manufacturing projects. Finally, managerial implications are provided for manufacturing leaders and project managers.
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References
Brynjolfsson, E., McAfee, A.: The business of artificial intelligence. Harv. Bus. Rev. 7, 3–11 (2017)
Gartner, Inc.: Gartner identifies three megatrends that will drive digital business into the next decade. https://www.gartner.com/en/newsroom/press-releases/2017-08-15-gartner-identifies-three-megatrends-that-will-drive-digital-business-into-the-next-decade Last Accessed June 07 2022
Stone, P., et al.: One hundred year study on artificial intelligence: Report of the 2015–2016 study panel. Technical report, Stanford University, 2016. Accessed: June 07, 2021. [Online]. Available: https://ai100.stanford.edu/2016-report
Auth, G., Jokisch, O., Dürk, C.: Revisiting automated project management in the digital age – a survey of AI approaches. Online J. Appl. Knowl. Manag. 7(1), 27–39 (2019). https://doi.org/10.36965/OJAKM.2019.7(1)27-39
Winter, R., Rohner, P., Kiselev, C.: Mission impossible? exploring the limits of managing large IT projects and ways to cross the line. In: Proceedings of the 52nd Hawaii International Conference on System Sciences, Grand Wailea, HI, USA, 2019, pp. 6388–6397. https://doi.org/10.24251/HICSS.2019.768
Wagner, T., Phelps, J., Guralnik, V., VanRiper, R.: An Application View of COORDINATORS: Coordination Managers for First Responders AAAI (2004)
Xu, K., Muñoz-Avila, H.: CaBMA: Case-Based Project Management Assistant. AAAI (2004)
Hofmann, P., Jöhnk, J., Protschky, D., Urbach, N.: Developing purposeful AI use cases – a structured method and its application in project management,” presented at the WI2020 (2020). https://doi.org/10.30844/wi_2020_a3-hofmann
Brenner, W., et al.: User, use & utility research: the digital user as new design perspective in business and information systems engineering. Bus. Inf. Syst. Eng. 6(1), 55–61 (2014)
Kerzner, H.: Project management: a systems approach to planning, scheduling, and controlling, 11th edn. John Wiley & Sons, Hoboken, USA (2013)
Turnerand, J.R., Müller, R.: On the nature of the project as a temporary organization. Int. J. Project Manage. 21(1), 1–8 (2003)
Atkinson, R.: Project management: cost, time and quality, two best guesses and a phenomenon, it’s time to accept other success criteria. Int. J. Project Manage. 17(6), 337–342 (1999)
Papke-Shields, K.E., Boyer-Wright, K.M.: Strategic planning characteristics applied to project management. Int. J. Project Manage. 35(2), 169–179 (2017)
Jöhnk, J., Hartmann, M., Urbach, N.: All roads lead to burning rome: towards a conceptual model of IT project success. In: 15th International Conference on Wirtschaftsinformatik (WI), pp. 1412–1427. GITO, Verlag (2020)
Fauser, M.J., Schmidthuysen, M., Scheffold, B.: The Prediction of Success in Project Management (2015)
Project Management Institute.: PMBOK Guide – A guide to the project management body of knowledge. 6th edn. Project Management Institute, Newtown Square, USA (2017)
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Sahli, A., Pei, E., Evans, R. (2023). A Conceptual Framework for Applying Artificial Intelligence to Manufacturing Projects. In: Alfnes, E., Romsdal, A., Strandhagen, J.O., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures. APMS 2023. IFIP Advances in Information and Communication Technology, vol 690. Springer, Cham. https://doi.org/10.1007/978-3-031-43666-6_44
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DOI: https://doi.org/10.1007/978-3-031-43666-6_44
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