Prioritising smart factory investments – A project portfolio selection approach

Abstract

Industry 4.0, which describes the transformation of existing production environments toward smart factories, is implemented in ever more manufacturing companies. Smart factories offer diverse advantages such as high flexibility, dynamic scheduling, as well as accurate fault diagnosis and prediction. Hence, manufacturing companies need support for assessing which projects they should implement to transform their production environment. As no such guidance exists in the literature, we propose a multi-dimensional decision model that accounts for interdependencies among production components, for projects with different performance effects, and for digital capabilities constitutive of smart factories (i.e., real-time ability, interoperability, virtualisation and decentralisation). The decision model schedules smart factory projects over multiple planning periods and assesses project roadmaps in line with objectives that comply with established performance measures and the digital capabilities of smart factories. We evaluate and discuss the decision model in interviews with two factory managers and three researchers with great experience in the smart factory domain. Based on a software prototype, we also successfully applied the decision model at a manufacturing company based on real-world data.

KEYWORDS:

• Smart factory
• project portfolio management
• performance measurement
• multi-criteria decision making
• digital capabilities

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Stephan Dreyer

Stephan Dreyer studied Informatics (Bachelor of Science) at the Technical University of Munich. He then enrolled in the elite graduate program Finance & Information Management (Master of Science with honors) at the Technical University of Munich, the University of Augsburg, and the University of Bayreuth. Stephan gained practical experience at Loyalty Partner Solutions GmbH in Munich and Carl Zeiss Meditec AG in Oberkochen. For a research project about digital human representations and their applications for health behavior change, he visited the University of Newcastle in Newcastle/Australia. He worked as a research assistant at the FIM Research Center and the project group Business & Information Systems Engineering of Fraunhofer FIT from June 2018 to November 2019.

Andreas Egger

Andreas Egger studied Business Administration (Bachelor of Science) at the University of Ulm. He then enrolled in the elite graduate program Finance & Information Management (Master of Science with honors) at the Technical University of Munich, the University of Augsburg, and the University of Bayreuth. Andreas gained practical experience at BMW Group and MAN Truck&Bus AG in Munich. For a research project on process mining and robotic process automation, he visited Queensland University of Technology (QUT) in Brisbane/Australia. At the FIM Research Center and the project group Business & Information Systems Engineering of Fraunhofer FIT, he started as a research assistant in May 2019 and is a Doctoral Candidate since May 2020.

Louis Püschel

Louis Püschel holds a PhD in Business and Information Systems Engineering (BISE) from the University of Bayreuth and a Diploma in Industrial Engineering from the Brandenburg University of Technology Cottbus-Senftenberg (Germany). Since May 2015, Louis has been working as research assistant at the Research Center Finance & Information Management (FIM), the University of Bayreuth, and the Project Group BISE of the Fraunhofer FIT, with a focus on business process management and the Internet of Things.

Maximilian Röglinger

Maximilian Röglinger is a Professor of Information Systems at the University of Bayreuth. He serves as Deputy Academic Director of the Research Center Finance & Information Management (FIM), where he heads the business process management (BPM) group. Maximilian is also working with the Fraunhofer FIT’s Project Group Business & Information Systems Engineering. Most of his work centres around BPM, customer relationship management and digital transformation. He has published in journals such as Business & Information Systems Engineering, Decision Support Systems, European Journal of Information Systems, Journal of the Association for Information Systems, and Journal of Strategic Information Systems. Maximilian is highly engaged in projects with companies such as Deutsche Bahn, Deutsche Bank, Hilti, Infineon Technologies, Schott and Siemens. He earned his PhD at the University of Augsburg and holds a Diploma in Business and Information Systems Engineering from the University of Bamberg.