Decision Analytics and Soft Computing with Industrial Partners: A Personal Retrospective

Methods in decision analytics are becoming essential tools for organizations to process the increasing amount of collected data. At the same time, these models should be capable of representing and utilizing the tacit knowledge of experts. In other words, companies require methods that can make use of imprecise information to deliver insights in real time. In this chapter, we provide a summary of three closely related research projects designed by building on the concept of knowledge mobilization. In these three cases, we provide solutions for typical business analytical problems originating mainly form the process industry. Fuzzy ontology represented as a fuzzy relation provides the basis for every application. By looking at the similarities among the three cases, we discuss the main lessons learnt and provide some important factors to be considered in future applications of soft computing in industrial applications.

[1]  Ana Paula Barbosa-Póvoa,et al.  Progresses and challenges in process industry supply chains optimization , 2012 .

[2]  R. Hogarth,et al.  Why Forecasts Fail. What to Do Instead , 2010 .

[3]  Clyde W. Holsapple,et al.  A unified foundation for business analytics , 2014, Decis. Support Syst..

[4]  Moustafa Elshafei,et al.  RBF neural network inferential sensor for process emission monitoring , 2013 .

[5]  E. Herrera-Viedma,et al.  A new consensus model for group decision making using fuzzy ontology , 2013, Soft Comput..

[6]  Bogdan Gabrys,et al.  Data-driven Soft Sensors in the process industry , 2009, Comput. Chem. Eng..

[7]  Fernando Ortega Managing vagueness in ontologies , 2011 .

[8]  Christer Carlsson,et al.  Decision making with a fuzzy ontology , 2012, Soft Comput..

[9]  Wenhong Luo,et al.  The Analytics Movement: Implications for Operations Research , 2010, Interfaces.

[10]  J. Alberto Espinosa,et al.  Advanced Analytics -- Issues and Challenges in a Global Environment , 2014, 2014 47th Hawaii International Conference on System Sciences.

[11]  W. A. Lucas,et al.  Best Practices for Industry-University Collaboration , 2010 .

[12]  Christer Carlsson,et al.  A Soft Computing Approach to Mastering Paper Machines , 2013, 2013 46th Hawaii International Conference on System Sciences.

[13]  George J. Klir,et al.  Fuzzy sets and fuzzy logic - theory and applications , 1995 .

[14]  Biao Huang,et al.  Design of inferential sensors in the process industry: A review of Bayesian methods , 2013 .

[15]  Christer Carlsson,et al.  Fuzzy Ontology Used for Knowledge Mobilization , 2013, Int. J. Intell. Syst..

[16]  Jeanne G. Harris,et al.  Competing on Analytics: The New Science of Winning , 2007 .