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Project Portfolio Selection for the Digital Transformation Era

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Industry 4.0: Managing The Digital Transformation

Part of the book series: Springer Series in Advanced Manufacturing ((SSAM))

Abstract

By bringing various technological advances together, Industry 4.0 promises production systems to boost in productivity. The transformation of the existing production systems into an Industry 4.0 factory is a strategic and long-term undertaking which needs a high capital investment, training of personnel and change of the environment and the culture in almost all of the functions of the value chain. Thus, it is required to be planned well by the companies. To be successful in the Industry 4.0 era, companies will not only have to simultaneously execute interdependent projects, but also require to perform project portfolio selection task in multi-dimensional environments in the presence of high uncertainty. Since determining optimal project portfolio for digital transformation among various project alternatives demands the consideration of multiple constraints and interdependencies, an integer programming model is proposed to address this problem in this chapter. To demonstrate its effectiveness and practicality, the proposed optimization model is applied to the Industry 4.0 project alternatives of an automotive manufacturer.

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Abbreviations

PPM:

Project Portfolio Management

PPOM:

Project Portfolio Optimization and Management

LP:

Linear Programming

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Authors and Affiliations

  1. Department of Industrial Engineering, Faculty of Management, Istanbul Technical University, 34367, Maçka, Istanbul, Turkey

    Erkan Isikli, Seda Yanik, Emre Cevikcan & Alp Ustundag

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  1. Erkan Isikli
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  2. Seda Yanik
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  3. Emre Cevikcan
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  4. Alp Ustundag
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Correspondence to Erkan Isikli .

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Isikli, E., Yanik, S., Cevikcan, E., Ustundag, A. (2018). Project Portfolio Selection for the Digital Transformation Era. In: Industry 4.0: Managing The Digital Transformation. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-319-57870-5_6

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  • DOI: https://doi.org/10.1007/978-3-319-57870-5_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57869-9

  • Online ISBN: 978-3-319-57870-5

  • eBook Packages: EngineeringEngineering (R0)

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