Fuzzy Cognitive Maps for Human Reliability Analysis in Production Systems

Cognitive maps provide a graphical and mathematical representation of an individual’s system of beliefs: a cognitive map shows the paths taken, including the alternatives, to reach a destination. With the current increasing need for efficiency of both plant and human operator, fuzzy cognitive maps (FCM) have proved to be able to provide a valid help in assessing the most critical factors for operators in managing and controlling production plants. A FCM represents a technique that corresponds closely to the way humans perceive it; they are easily understandable, even by a non-professional audience and each parameter has a perceivable meaning. FCMs are also an excellent means to study a production process and obtain useful indications on the consequences which can be determined by the variation of one or more variables in the system examined. They can provide an interesting solution to the issue of assessing the factors which are considered to affect the operator’s reliability. In this chapter fuzzy cognitive maps will be investigated for human reliability in production systems.

[1]  Dan Petersen Human-error reduction and safety management , 1996 .

[2]  Bill Karakostas,et al.  The use of fuzzy cognitive maps to simulate the information systems strategic planning process , 1999, Inf. Softw. Technol..

[3]  Mo Adam Mahmood,et al.  A Comprehensive Model for Measuring the Potential Impact of Information Technology on Organizational Strategic Variables , 1991 .

[4]  B. Kosko Fuzzy Thinking: The New Science of Fuzzy Logic , 1993 .

[5]  Brian H. Kleiner,et al.  New developments concerning managing human factors for safety , 2000 .

[6]  B Kirwan,et al.  The validation of three human reliability quantification techniques--THERP, HEART and JHEDI: Part II--Results of validation exercise. , 1997, Applied ergonomics.

[7]  Rachael Gordon,et al.  The contribution of human factors to accidents in the offshore oil industry , 1998 .

[8]  Robert E. Melchers,et al.  Probabilistic Risk Assessment of Engineering Systems , 1997 .

[9]  Soung Hie Kim,et al.  Fuzzy cognitive maps considering time relationships , 1995, Int. J. Hum. Comput. Stud..

[10]  Takashi Toriizuka,et al.  Application of performance shaping factor (PSF) for work improvement in industrial plant maintenance tasks , 2001 .

[11]  H. Unger,et al.  The human error rate assessment and optimizing system HEROS - a new procedure for evaluating and optimizing the man-machine interface in PSA , 2001, Reliab. Eng. Syst. Saf..

[12]  James C. Bezdek,et al.  Pool2: a generic system for cognitive map development and decision analysis , 1989, IEEE Trans. Syst. Man Cybern..

[13]  Prasad V. Prabhu,et al.  A review of human error in aviation maintenance and inspection , 2000 .

[14]  Andrew R. Atkinson The role of human error in construction defects , 1999 .

[15]  P C Cacciabue,et al.  Human factors impact on risk analysis of complex systems. , 2000, Journal of hazardous materials.

[16]  Barry Kirwan,et al.  Development and application of a human error identification tool for air traffic control. , 2002, Applied ergonomics.

[17]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[18]  Konstantinos G. Margaritis,et al.  An experimental study of the dynamics of the certainty neuron fuzzy cognitive maps , 1999 .

[19]  Bart Kosko,et al.  Fuzzy Cognitive Maps , 1986, Int. J. Man Mach. Stud..

[20]  W. R. Taber Estimation of expert weights using fuzzy cognitive maps , 1987 .

[21]  B Kirwan The validation of three human reliability quantification techniques--THERP, HEART and JHEDI: Part III--Practical aspects of the usage of the techniques. , 1997, Applied ergonomics.

[22]  Chiu-Chi Wei,et al.  Failure mode and effects analysis using grey theory , 2001 .

[23]  C.E. Pelaez,et al.  Applying fuzzy cognitive-maps knowledge-representation to failure modes effects analysis , 1995, Annual Reliability and Maintainability Symposium 1995 Proceedings.

[24]  H. A. Lingstone,et al.  The Delphi Method: Techniques and Applications , 1976 .

[25]  J. Meredith,et al.  Alternative research paradigms in operations , 1989 .

[26]  Chrysostomos D. Stylios,et al.  Fuzzy cognitive maps: a model for intelligent supervisory control systems , 1999 .

[27]  Barry Kirwan,et al.  Collection of offshore human error probability data , 1998 .

[28]  G. Bradley Chadwell,et al.  Contribution of human factors to incidents in the petroleum refining industry , 1999 .

[29]  Kim Warren,et al.  Exploring competitive futures using cognitive mapping , 1995 .

[30]  J. B. Bowles,et al.  Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis , 1995 .

[31]  Barry Kirwan,et al.  The development of a nuclear chemical plant human reliability management approach: HRMS and JHEDI☆ , 1997 .

[32]  Ola Svenson,et al.  Safety barrier function analysis in a process industry: A nuclear power application , 1996 .

[33]  Ola Svenson,et al.  Human errors and work performance in a nuclear power plant control room: associations with work-related factors and behavioral coping☆ , 1997 .

[34]  Li-Min Fu CAUSIM: A rule-based causal simulation system , 1991, Simul..

[35]  David B. Paradice,et al.  SIMON: an object-oriented information system for coordinating strategies and operations , 1992, IEEE Trans. Syst. Man Cybern..

[36]  Oliver Sträter,et al.  Assessment of human reliability based on evaluation of plant experience: requirements and implementation , 1999 .

[37]  B Kirwan,et al.  A case study of a human reliability assessment for an existing nuclear power plant. , 1996, Applied ergonomics.

[38]  Peter B. Borwein,et al.  uzzy cognitive maps and cellular automata : An evolutionary approach or social systems modelling , 2012 .

[39]  W.-R. Zhang,et al.  A cognitive-map-based approach to the coordination of distributed cooperative agents , 1992, IEEE Trans. Syst. Man Cybern..

[40]  James J. Higgins,et al.  A literature survey of the human reliability component in a man-machine system , 1988 .

[41]  Konstantinos G. Margaritis,et al.  Cognitive Mapping and Certainty Neuron Fuzzy Cognitive Maps , 1997, Inf. Sci..

[42]  B. Vos,et al.  Virtuous and vicious cycles on the road towards international supply chain management , 1999 .

[43]  Rod Taber,et al.  Knowledge processing with Fuzzy Cognitive Maps , 1991 .

[44]  Shigeo Abe,et al.  Neural Networks and Fuzzy Systems , 1996, Springer US.

[45]  Robert Sargent,et al.  Development and evaluation of the Maintenance Error Decision Aid (MEDA) process , 2000 .

[46]  A. V. D. Ven,et al.  Group Techniques for Program Planning , 1975 .

[47]  Alexander M. Goulielmos,et al.  The man‐machine interface and its impact on shipping safety , 1997 .

[48]  John B. Bowles,et al.  Using Fuzzy Cognitive Maps as a System Model for Failure Modes and Effects Analysis , 1996, Inf. Sci..

[49]  J. N. Sørensen,et al.  Safety culture: a survey of the state-of-the-art , 2002, Reliab. Eng. Syst. Saf..

[50]  Chrysostomos D. Stylios,et al.  Modelling supervisory control systems using fuzzy cognitive maps , 2000 .

[51]  Kyung S. Park,et al.  Considering performance shaping factors in situation-specific human error probabilities , 1996 .

[52]  Abraham Kandel,et al.  Automatic construction of FCMs , 1998, Fuzzy Sets Syst..

[53]  Martha Grabowski,et al.  Using system simulation to model the impact of human error in a maritime system , 1998 .

[54]  Chrysostomos D. Stylios,et al.  A Soft Computing Approach for Modelling the Supervisor of Manufacturing Systems , 1999, J. Intell. Robotic Syst..