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Background: Safety risk assessment of human-computer interaction behavior is very important for safety design and management in complex human-computer system such as airplane cockpit and monitoring system in nuclear power plant. Many major accidents were a result of lack of efficient hazard identification and risk assessment approaches, as described in various patents. Methods: The process of human-computer interaction risk assessment is established. The event tree analysis is employed to identify the hazard to the system and human beings. The dynamic safety risk assessment model is provided based on Bayesian network (BN) considering the uncertainty and correlation of the human-computer interaction behaviors. The safety risk level could be determined by matching the risk matrix with the assessment results on severity and probability. Results: An illustration, which takes a typical human-computer system as the study object, shows that the approach proposed in this paper is suitable and efficient for safety risk assessment of humancomputer interaction behaviors. Conclusion: With the development of technologies, the safety risk of the systems with human in the loop has received increasing attention. Safety risk assessment of human-computer interaction behavior is a very important part for safety design and management in complex human-computer system such as cockpit of vehicles and monitoring systems in nuclear power plant so that the user experience would be enhanced and safety risk would be controllable.

Background: This article reviews recent patents pertaining to the technological achievements and shortcomings of aircraft Position Indicator and Actuator System (PIAS). Generally, most patents have concentrated more on design, while implementing various developed single or multiobjective algorithms to solve component or system optimal design problems such as those of PIAS. Thus, there is a noticeable lack of patent efforts on either developing new constraint-handling techniques especially for multi-objective optimization, or applying advance single-objective constrainthandling techniques to multi-objective optimization. Method: To address this, the authors of this article in there past work developed a multi-objective optimization algorithm called Genetic Pareto Set Identification Algorithm plus Different Sex (GPSIA+DS), which considers the feasible and infeasible solution in it optimization strategy. However, the application of GPSIA+DS to real world reliability engineering problem has not been validated. Result: Thus, in this work, GPSIA+DS ability to handle an aircraft PIAS optimization problem was presented. PIAS component failure rates were obtained via Fault Tree Analysis (FTA). PIAS cost and reliability were the study objective functions subject to weight constrains. The performance of GPSIA+DS for the test problem was investigated through a comparative study. Conclusion: In the comparative study GPSIA+DS was compared with fast-sort genetic algorithm plus constrained dominance principle (NSGA-II+CD). Although NSGA-II+DS out performed GPSIA+DS for this test problem, it is evident that GPSIA+DS is equally an efficient algorithm.

Maintainability influencing attributes are analyzed, their weight and value calculating methods are given, and the maintainability fuzzy evaluation method is proposed based on the relative closeness. According to the maintenance task simulation operated in virtual environment, the maintainability virtual evaluation model is built by analyzing the maintenance task for each replaceable unit of product. At last, a case study is given based upon the main landing gear system of a certain type civil aircraft, and the result indicates that the model is suitable for maintainability qualitative evaluation and can support maintainability concurrent design.