An Overview of Human Reliability Analysis Techniques in Manufacturing Operations

Abstract

In recent years, there has been a decrease in accidents due to technical failures through technological developments of redundancy and protection, which have made systems more reliable. However, it is not possible to talk about system reliability without addressing the failure rate of all its components; among these components, "man" – because his rate of error changes the rate of failure of components with which he interacts. It is clear that the contribution of the human factor in the dynamics of accidents – both statistically and in terms of severity of consequences – is high [2]. Although valid values are difficult to obtain, estimates agree that errors committed by man are responsible for 60–90% of the accidents; the remainder of accidents are attributable to technical deficiencies [2,3,4]. The incidents are, of course, the most obvious human errors in industrial systems, but minor faults can seriously reduce the operations performances, in terms of productivity and efficiency. In fact, human error has a direct impact on productivity because errors affect the rates of rejection of the product, thereby increasing the cost of production and possibly reduce subsequent sales. Therefore, there is need to assess human reliability to reduce the likely causes of errors [1]. The starting point of this work was to study the framework of today’s methods of human reliability analysis (HRA): those quantitative of the first generation (as THERP and HCR), those qualitative of second (as CREAM and SPAR-H), and new dynamic HRA methods and recent improvements of individual phases of HRA approaches. These methods have, in fact, the purpose of assessing the likelihood of human error – in industrial systems, for a given operation, in a certain interval of time and in a particular context – on the basis of models that describe, in a more or less simplistic way, the complex mechanism that lies behind the single human action that is potentially subject to error [1]. The concern in safety and reliability analyses is whether an operator is likely to make an incorrect action and which type of action is most likely [5]. The goals defined by Swain and Guttmann (1983) in discussing the THERP approach, one of the first HRA methods developed, are still valid: The objective of a human reliability analysis is ‘to evaluate the operator’s contribution to system reliability’ and, more precisely, ‘to predict human error rates and to evaluate the degradation to human–machine systems likely to be caused by human errors in association with equipment functioning, operational procedures and practices, and other system and human characteristics which influence the system behavior’ [7]. The different HRA methods analysed allowed us to identify guidelines for determining the likelihood of human error and the assessment of contextual factors. The first step is to identify a probability of human error for the operation to be performed, while the second consists of the evaluation through appropriate multipliers, the impact of environmental, and the behavio...

Optimizing human reliability in work shifts scheduling: A real case of clothing job shop

“…In human reliability analysis models, the probability of human error is calculated based on the activities of the worker and the factors that shape performance. Factors that shape performance are related to the work environment or mental and physical capabilities of the workforce or both 15 . Human reliability analysis models are divided into two main categories: quantitative models and qualitative models.…”

Path to modeling dynamic performance shaping factors in nuclear power plants operation – A review

“…Moreover, many researchers realize that cognitive activities are supposed to be considered. In the first‐generation methods, the effects of cognition may be incorporated in the HEP assigned to the human error of a specific task type, but they still lack cognition influence on human behaviors 14,35 . Specifically, Hollnagel indicated that the dichotomy classification of human behaviors, like success and failure, or error of commission and error of omission, makes it hard to perform a more detailed classification.…”

Reliability assessment of man‐machine systems subject to probabilistic common cause errors

“…Machines are directly affected by the environment or personnel during operation, 20 which may lead to independent or common‐cause failures of components, 21–24 thus directly affecting the reliability of the system. Meanwhile, human as one of the critical factors affecting system reliability, 25 the environment and machine will affect the HEP by influencing the performance shaping factors of the personnel. With the advancement of research, the study of system reliability has evolved from discussing the effects of machines and the environment to a comprehensive examination of the human‐machine‐environment interaction 26–28 .…”

“…HE is one of the most significant contributors to the reliability of the system in MMSs. 60%−90% of MMS accidents are related to HEs, 25 which may result from performing tasks out of sequence, operating at the wrong time, applying the wrong force or direction, etc. Many studies have assessed the human reliability in the reliability assessment of MMS 26–28 .…”