scholarly journals An ontological framework for knowledge modeling and decision support in cyber-physical systems

2016 ◽  
Vol 30 (1) ◽  
pp. 77-94 ◽  
Author(s):  
Leonard Petnga ◽  
Mark Austin
Author(s):  
A. V. Smirnov ◽  
T. V. Levashova

Introduction: Socio-cyber-physical systems are complex non-linear systems. Such systems display emergent properties. Involvement of humans, as a part of these systems, in the decision-making process contributes to overcoming the consequences of the emergent system behavior, since people can use their experience and intuition, not just the programmed rules and procedures.Purpose: Development of models for decision support in socio-cyber-physical systems.Results: A scheme of decision making in socio-cyber-physical systems, a conceptual framework of decision support in these systems, and stepwise decision support models have been developed. The decision-making scheme is that cybernetic components make their decisions first, and if they cannot do this, they ask humans for help. The stepwise models support the decisions made by components of socio-cyber-physical systems at the conventional stages of the decision-making process: situation awareness, problem identification, development of alternatives, choice of a preferred alternative, and decision implementation. The application of the developed models is illustrated through a scenario for planning the execution of a common task for robots.Practical relevance: The developed models enable you to design plans on solving tasks common for system components or on achievement of common goals, and to implement these plans. The models contribute to overcoming the consequences of the emergent behavior of socio-cyber-physical systems, and to the research on machine learning and mobile robot control.


Author(s):  
Yuri P. Pavlov ◽  
Evgeniy Ivanov Marinov

Modeling of complex processes with human participations causes difficulties due to the lack of precise measurement coming from the qualitative nature of the human notions. This provokes the need of utilization of empirical knowledge expressed cardinally. An approach for solution of these problems is utility theory. As cyber-physical systems are integrations of computation, networking, and physical processes in interaction with the user is needed feedback loops, the aim of the chapter is to demonstrate the possibility to describe quantitatively complex processes with human participation. This approach permits analytical representations of the users' preferences as objective utility functions and modeling of the complex system “human-process.” The mathematical technique allows CPS users dialog and is demonstrated by two case studies, portfolio allocation, and modeling of a competitive trade by a finite game and utility preference representation of the trader. The presented formulations could serve as foundation of development of decision support tools and decision control.


Author(s):  
Pascal Freier ◽  
Matthias Schumann

Cyber-physical systems promise a complete networking of all actors and resources involved in production and thus an improved availability of information. In this context decision support systems enable appropriate processing and presentation of the captured data. In particular, production scheduling could benefit from this, since it is responsible for the short-term planning and control of released orders. Since decision support systems and cyber-physical systems together are not yet widely used in production scheduling, the aim of this research study is to analyse the adoption of these technologies. In order to do so, we conducted a qualitative interview study with experts on production scheduling. Thereby, we identified eleven influencing factors and 22 related challenges, which affect the adoption of decision support systems in production scheduling in the context of cyber-physical systems. We further discuss and assess the identified influencing factors based on the interview study. The results help to explain and improve the adoption of those systems and can serve as a starting point for their development.


Author(s):  
Yuri P. Pavlov ◽  
Evgeniy Ivanov Marinov

Modeling of complex processes with human participations causes difficulties due to the lack of precise measurement coming from the qualitative nature of the human notions. This provokes the need of utilization of empirical knowledge expressed cardinally. An approach for solution of these problems is utility theory. As cyber-physical systems are integrations of computation, networking, and physical processes in interaction with the user is needed feedback loops, the aim of the chapter is to demonstrate the possibility to describe quantitatively complex processes with human participation. This approach permits analytical representations of the users' preferences as objective utility functions and modeling of the complex system “human-process.” The mathematical technique allows CPS users dialog and is demonstrated by two case studies, portfolio allocation, and modeling of a competitive trade by a finite game and utility preference representation of the trader. The presented formulations could serve as foundation of development of decision support tools and decision control.


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