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Using AI to Advance Factory Planning: A Case Study to Identify Success Factors of Implementing an AI-Based Demand Planning Solution

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Decision Support Systems XI: Decision Support Systems, Analytics and Technologies in Response to Global Crisis Management (ICDSST 2021)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 414))

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Abstract

Rational planning decisions are based upon forecasts. Precise forecasting has therefore a central role in business. The prediction of customer demand is a prime example. This paper introduces recurrent neural networks to model customer demand and combine the forecast with uncertainty measures to derive decision support of the demand planning department. It identifies and describes the keys to the successful implementation of an AI-based solution: bringing together data with business knowledge, AI methods and user experience, and applying agile software development practices.

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Author information

Authors and Affiliations

  1. Digital Industries, Siemens AG, Munich, Germany

    Ulrike Dowie & Ralph Grothmann

Authors
  1. Ulrike Dowie
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  2. Ralph Grothmann
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Corresponding author

Correspondence to Ralph Grothmann .

Editor information

Editors and Affiliations

  1. Loughborough University, Loughborough, UK

    Uchitha Jayawickrama

  2. International Hellenic University, Kavala, Greece

    Pavlos Delias

  3. University of Zaragoza, Zaragoza, Spain

    María Teresa Escobar

  4. University of Macedonia, Thessaloniki, Greece

    Jason Papathanasiou

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Dowie, U., Grothmann, R. (2021). Using AI to Advance Factory Planning: A Case Study to Identify Success Factors of Implementing an AI-Based Demand Planning Solution. In: Jayawickrama, U., Delias, P., Escobar, M.T., Papathanasiou, J. (eds) Decision Support Systems XI: Decision Support Systems, Analytics and Technologies in Response to Global Crisis Management. ICDSST 2021. Lecture Notes in Business Information Processing, vol 414. Springer, Cham. https://doi.org/10.1007/978-3-030-73976-8_10

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  • DOI: https://doi.org/10.1007/978-3-030-73976-8_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-73975-1

  • Online ISBN: 978-3-030-73976-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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