Towards an Approach to Identify the Optimal Instant of Time for Information Capturing in Supply Chains

Supply chains are becoming increasingly complex and with this development the challenges towards information management increase. The importance of capturing the right, most relevant information in order to avoid having too much information to handle is commonly accepted in industry and academia. But the question not yet sufficiently discussed by industry and academia is: What is the optimal instant of time to capture the relevant information along the process chain? With this paper the authors look into this issue by first analyzing two practical cases, from a transport and a manufacturing perspective. Afterwards, the elements of information captured are shortly elaborated and finally, constraints on the determination of the optimal instant of time for information capturing are elaborated in order to build a foundation for further research. This paper is a first step towards a methodological approach taking on these issues. A short conclusion and outlook summarizes the paper.

[1]  John A. Sharp,et al.  The selection of information systems for production management: An evolving problem , 2000 .

[2]  Y. Braunstein,et al.  Information management , 1996 .

[3]  Dieter Spath,et al.  Tore öffnen: Quality-Gate-Konzept für den Produktentstehungsprozess , 2001 .

[4]  Edward A. Lee.  Cyber-physical Systems -are Computing Foundations Adequate? Position Paper for Nsf Workshop on Cyber-physical Systems: Research Motivation, Techniques and Roadmap , 1998 .

[5]  V. Agarwal,et al.  The intelligent product driven supply chain , 2002, IEEE International Conference on Systems, Man and Cybernetics.

[6]  Ben J. Hicks,et al.  Lean information management: Understanding and eliminating waste , 2007, Int. J. Inf. Manag..

[7]  Klaus-Dieter Thoben,et al.  An approach to monitoring quality in manufacturing using supervised machine learning on product state data , 2013, Journal of Intelligent Manufacturing.

[8]  Jc Johan Wortmann,et al.  Application of labels to trace material flows in multi-echelon supply chains , 2004 .

[9]  Kevin Ashton,et al.  That ‘Internet of Things’ Thing , 1999 .

[10]  Duncan McFarlane,et al.  The Impact of Automatic Identification on Supply Chain Operations , 2003 .

[11]  Jong-min Choe,et al.  The consideration of cultural differences in the design of information systems , 2004, Inf. Manag..

[12]  Tilo Pfeifer,et al.  Masing Handbuch Qualitätsmanagement , 2014, Masing Handbuch Qualitätsmanagement.

[13]  John Feather,et al.  International Encyclopedia of Information and Library Science , 2013 .

[14]  Angappa Gunasekaran,et al.  Information systems in supply chain integration and management , 2004, Eur. J. Oper. Res..

[15]  Robert Schmitt,et al.  Qualitätsmanagement: Strategien, Methoden, Techniken , 2010 .

[16]  Andreas Otto.  Supply Chain Event Management: Three Perspectives , 2003 .

[17]  Pingyu Jiang,et al.  RFID-Enabled Real-Time Manufacturing Information Tracking Infrastructure for Extended Enterprises , 2009, DET.

[18]  Daniel Hellström,et al.  The cost and process of implementing RFID technology to manage and control returnable transport items , 2009 .

[19]  Antonio Iera,et al.  The Internet of Things: A survey , 2010, Comput. Networks.

[20]  B. Beamon.  Supply chain design and analysis:: Models and methods , 1998 .

[21]  Philip Powell,et al.  Competitive advantage from IT in logistics: The integrated transport tracking system , 1998 .

[22]  Pierpaolo Pontrandolfo,et al.  Analysis of information flows to enhance the coordination of production processes , 2002 .

[23]  Thomas Prefi.  Qualitätsmanagement in der Produktentwicklung , 2014 .

[24]  Gregor Engels,et al.  Comprehensive Architecture Evaluation and Management in Large Software-Systems , 2008, QoSA.