Title :
Engineering intelligence - Product-service concepts and requirements in industry
Author :
Lanz, Minna ; Nykanen, Ossi ; Aaltonen, Jussi ; Ranta, Pekka A. ; Koskinen, Kari T. ; Andersson, Pernille H.
Author_Institution :
Tampere Univ. of Technol., Tampere, Finland
fDate :
July 30 2013-Aug. 2 2013
Abstract :
European manufacturing and construction sector is wrestling with the fundamental and rapid changes in their business environment. Business environment is becoming more dynamic and distributed, thus old standardization and mass-customization methods can no longer support the companies. In order to survive the companies must be able to offer fully customized product-service concepts instead of technical solutions. This causes challenges relating to efficiency of collaboration, utilization of information flows, agility and interoperability of technical solutions and operation culture. The products, processes and services need to be designed “for humans by humans”. The competence development methods and enhanced learning have to be comprehensively taken into account. This paper summarizes the challenges among industry and provides a new approach Engineering Intelligence Ecosystem (EIE) that addresses aforementioned challenges of complex engineering systems.
Keywords :
artificial intelligence; construction industry; engineering information systems; mass production; product customisation; production engineering computing; Europe; business environment; company survival; competence development methods; construction sector; engineering intelligence ecosystem; information flow; learning enhancement; manufacturing sectors; mass customization; product-service customization; standardization; technical solution interoperability; Artificial intelligence; Biological system modeling; Business; Collaboration; Ecosystems; Manufacturing; Semantics; built environment; collaborative environment; competence development; context-awareness; customer participation; factories of future; intelligent business process; machine systems; manufacturing; production systems; semantic knowledge modelling;
Conference_Titel :
Assembly and Manufacturing (ISAM), 2013 IEEE International Symposium on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4799-1656-6
DOI :
10.1109/ISAM.2013.6643510