A Classification of Data Structures for Process Analysis in Internal Logistics

Maximilian Wuennenberg, Charlotte Haid, Johannes Fottner

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Data Science plays a crucial role in driving new approaches to process optimization. With the increasing complexity of internal logistics systems, data-oriented methods have become essential in addressing the challenges that arise. However, standardized process analytics frameworks are lacking due to the heterogeneity of the underlying processes and the resulting data. This article aims to address this complexity by presenting a categorization of internal logistics data, consolidating the current state of the art. The categorization takes into account both real-world and scientifically proposed data architectures, providing a comprehensive overview. It includes a classification of comparative data fields based on their importance, the associated internal logistics processes, and potential usage scenarios. This classification is designed to cater to different use cases, such as diagnostics or prescriptive analytics. By presenting this categorization, the article enables practitioners to effectively leverage generated process data in a more goal-oriented manner. It empowers them to conduct suitable analyses tailored to their specific needs and objectives, based on the provided data architectures. In summary, this article offers valuable insights into internal logistics data categorization, providing a framework for practitioners to make informed decisions and optimize processes using data-driven approaches.

Original languageEnglish
Title of host publicationInnovative Intelligent Industrial Production and Logistics - 4th International Conference, IN4PL 2023, Proceedings
EditorsSergio Terzi, Kurosh Madani, Oleg Gusikhin, Hervé Panetto
PublisherSpringer Science and Business Media Deutschland GmbH
Pages53-67
Number of pages15
ISBN (Print)9783031493386
DOIs
StatePublished - 2023
Event4th International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2023 - Rome, Italy
Duration: 15 Nov 202317 Nov 2023

Publication series

NameCommunications in Computer and Information Science
Volume1886 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference4th International Conference on Innovative Intelligent Industrial Production and Logistics, IN4PL 2023
Country/TerritoryItaly
CityRome
Period15/11/2317/11/23

Keywords

  • Data analytics
  • Internal logistics
  • Process analysis

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