Development of model for human factor influence assessment on construction and road machines operation efficiency

Abstract

Introduction. The human factor and the characteristics of construction and road machine operators, such as experience, work experience, professional skills, skill, etc., have a significant impact on the efficiency of equipment operation. The human factor, on average, is the cause of about a third of the failures of construction and road machines. One of the most effective ways out of this situation is to improve the machines from the point of view of ensuring the compatibility of the elements of the human-machine system. The article considers the issues of the engineering and psychological component of compatibility.Materials and methods. The method of analysis of hierarchies is used, when solving the problem of identifying the causes of operators’ errors and fuzzy logic, to build a model for assessing the impact of the human factor on the efficiency of construction and road machines.Results. As a result of a comprehensive assessment of the causes of errors, it was found that the largest combination of criteria is a group of errors associated with the peculiarities of the task being performed, as well as the properties of the information processed by a person. The developed model for assessing the influence of the human factor on the efficiency of machine operation uses risk as an output variable, and input variables a generalized indicator of the complexity of the algorithm and the level of qualification of the machine operator.Discussion and conclusions. The resulting model allows you to make a primary assessment of the impact of the human factor and maintenance and repair planning, as well as be used in personnel management processes, for example, in terms of sending personnel for training. Further improvement is seen in the development of neurofuzzy anfys models which provide a knowledge base for more effective risk assessment by specific precedents. The structure of the model in terms of input variables for a more correct risk assessment is also possible to be changed.