scholarly journals A method to design Smart Services based on information categorization of industrial use cases

Procedia CIRP ◽  
2019 ◽  
Vol 83 ◽  
pp. 77-82 ◽  
Author(s):  
Konrad Exner ◽  
Elisa Smolka ◽  
Till Blüher ◽  
Rainer Stark
2018 ◽  
Vol 108 (07-08) ◽  
pp. 543-548
Author(s):  
T. Pschybilla ◽  
D. Baumann ◽  
S. Manz ◽  
W. Wenger ◽  

Mit der fortschreitenden Digitalisierung in der Produktion werden konstant ansteigende Datenmengen generiert. Eine besondere Rolle kommt dabei dem Gebiet der Data Analytics zu, welches die Gewinnung von Wissen aus Daten und damit die Entscheidungsfindung unterstützen kann. Im Beitrag wird ein Reifegradmodell zur Einordnung von Anwendungsfällen der Data Analytics in der Produktion vorgestellt und an einem Beispiel der Smart Services der Trumpf GmbH + Co. KG angewendet.   With the progressing digitization in manufacturing, continuously increasing amounts of data are being generated. The field of data analytics plays an important role in this context by advancing the acquisition of knowledge from data and thus decision-making. This paper presents a maturity model for the classification of data analytics use cases in manufacturing. The model is applied to an example of Smart Services at Trumpf GmbH + Co. KG.


Author(s):  
Alexandra Brintrup

While artificial intelligence (AI) in supply chains (SC) has become a popular topic, there is a distinct lack of conceptual frameworks with which to categorize and review how various subtopics of AI can help in subfields of supply chain management. To address this gap, this chapter conceptualizes the new topic of SC AI through a human-mimicking intelligent agent that exhibits “smart” SC behavior. It then develops several SC AI capability blocks for the intelligent agent and reviews and synthesizes studies to date within these capability blocks. The chapter concludes by highlighting several industrial use cases and extant challenges reported in the literature that need to be tackled to move this exciting new field forward.


Procedia CIRP ◽  
2019 ◽  
Vol 81 ◽  
pp. 1119-1124
Author(s):  
Volker Stich ◽  
Anne Bernardy ◽  
Vasco Seelmann ◽  
Jan Hicking

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