Problem Solving and Risk Management Methodology

Intending to lead organizations to continuous improvement, this chapter proposes a methodology that involves three axes: risk management, problem- solving, and feedback experience. This methodology allows organizations to characterize the experiences they have already confronted, as well as new experiences (which can be risks or problems) with the use of taxonomies established by the organization. It also enables them to capitalize and exploit their knowledge base. This work proposes a best-use approach of the past experiences that are similar to a current event and facilitate their treatment and provide solutions. The authors take the feedback as a point of articulation between the two methodologies because it is a mechanism that offers knowledge where it can be found that the organizations must avoid and take advantage of.

[1]  Bernard Kamsu-Foguem,et al.  Continuous improvement through knowledge-guided analysis in experience feedback , 2011, Eng. Appl. Artif. Intell..

[2]  L. Geneste,et al.  A framework for the improvement of combinatorial optimization: An experience feedback approch , 2007 .

[3]  Freimut Bodendorf,et al.  Case-based reasoning for complexity management in Industry 4.0 , 2020 .

[4]  Laurent Geneste,et al.  Hybridization of statistical and cognitive experience feedbacks to perform risk assessment: Application to aircraft deconstruction , 2012, 2012 IEEE International Conference on Industrial Engineering and Engineering Management.

[5]  Sin Yin Teh,et al.  The integration of FMEA with other problem solving tools: A review of enhancement opportunities , 2017 .

[6]  Philippe Clermont,et al.  Towards a model of integration between Risk Management and Lesson Learning system for Project Management , 2015, 2015 International Conference on Industrial Engineering and Systems Management (IESM).

[7]  Bernard Kamsu-Foguem,et al.  Structural-model approach of causal reasoning in problem solving processes , 2011, 2011 IEEE International Conference on Information Reuse & Integration.

[8]  Aimee Cecilia Hernández García,et al.  MEDIDAS DE SIMILITUD BASADAS EN CARACTERÍSTICAS PARA LA EVALUACIÓN DE RELACIONES TAXONÓMICAS (SIMILARITY MEASURES BASED ON FEATURES FOR THE EVALUATION OF TAXONOMIC RELATIONSHIPS) , 2018 .

[9]  Laurent Geneste,et al.  Decision-Support Methodology to Assess Risk in End-of-Life Management of Complex Systems , 2017, IEEE Systems Journal.

[10]  Bernard Kamsu-Foguem,et al.  Analysis reuse exploiting taxonomical information and belief assignment in industrial problem solving , 2013, Comput. Ind..

[11]  Jindong Qin,et al.  Failure mode and effects analysis (FMEA) for risk assessment based on interval type-2 fuzzy evidential reasoning method , 2020, Appl. Soft Comput..