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The sources of human error
(2017)
Perfect flawless performance does not exist. Yet we expect people in organisations with high safety and reliability demand to perform at their best so that the systems designed, operated and maintained by people do not fail. Still, even the best guarded systems fail. The goal of the study of human factors is avoiding the negative effects of the interaction between humans and technology as well as decreasing them to increase the well-being of people, functioning of the systems, and safety. This is achieved by identifying human performance problems, by applying human knowledge to the design of the system, and by utilizing gained knowledge to other similar situations that exist currently or will occur in the future.
This presentation will outline the definition, classification and misconceptions about human error and discuss the differences between traditional and contemporary understanding and prevention of human error. Practical examples from own research, highlighting the importance of identifying risks and appropriately dealing with them, will be given.
The field of human factors has been concerned with prevention of organisational accidents and the maintaining of the highest safety standards in organisations with high hazard potential since its beginnings. Whereas it is known that human error has contributed to some well-known accidents and events in various safety-critical applications, as well as in railway, and that human factors have an impact on how reliable our non-destructive inspections are, very little has been done so far to address human factors, especially in the railway sector.
The first steps in addressing human factors in the inspection of railway axles has been carried out by analysing the results of manual ultrasonic inspection of the railway axles during requalification in the education centre of the German Society for Non-Destructive Testing (DGZfP). In addition to the inspection, 160 participants were asked to fill out a questionnaire with the aim of identifying potential factors influencing their performance. The results showed that no correlation between the possible influencing factors (i.e. experience, level of qualification, satisfaction with the conditions during the re-qualification as well as in the daily practice and mental workload) and the inspection results. The explanation for this result was found in the fact that questionnaires can be used only to identify indirectly influencing factors. The only way to identify directly influencing factors and establish cause-effect relationships is by experimental study. The limitation of this study was the inability to influence the participants in any way during the requalification examination. Another angle used to identify potential influencing factors was the use of human-oriented Failure Modes and Effects Analysis. Carried out together with 4 experts from the field practice, two lecturers and two scientists, this analysis provided with an extensive list of possible failures, their causes, consequences and possible barriers. The largest benefits for the reliability of manual ultrasonic railway axle inspections in the practice can be found in attending to the organisational aspects of the inspection (e.g. processes, procedures, communication, education, supervision etc.).
Over the past couple of decades Non-Destructive Testing (NDT) has seen a significant increase in the use of automation. In addition to increased reliability, objectivity, consistency, repeatability, productivity, and so on, automating parts of the process is expected to decrease the potential for human error. However, the literature on human-automation interaction suggests that automation is not only associated with benefits, but also with new risks and risk sources. First, this paper will present the methodology used to identify—for the first time—possible risks associated with mechanised data acquisition and corresponding data evaluation. Moreover, it will highlight possible risks, their causes, consequences, and ways of preventing them. Second, those preventive measures will be further analysed by examining new risks that can arise from their implementation, i.e. potential for failure that can arise from (a) working with automated defect-detection and sizing aids, (b) implementing human redundancy, and (c) improvement of the inspection procedures without due consideration of the procedure users. And third, some optimisations strategies will be provided. The purpose of this work is to show that mechanised testing is associated with potential for failure and that the sources of those risks go beyond single inspectors and need to be looked at in the interaction of people with other systems, i.e. the technology, the team and, most importantly, the organisation.
Reliability of NDT depends not only on the intrinsic capability of the measuring systems and on the application factors (the conditions under which NDT is applied), but also—and to a great extent—on human factors and the organisational context under which each inspection is carried out.
Adoption of a systematic approach to the identification and prevention of risks.
Critical defects could be missed, even if the inspection process is semi-automated. The causes of that risk lie in the technology, people and in the organisation. Currently installed preventive measures are insufficient to prevent from risks New preventive measures could be installed, e.g. further automation, installing alarms, implementing human redundancy, developing software and hardware solutions, optimising procedures, etc.
Human factors studies are not only essential for the operation but also during the development process.
The General Guidance in the Swedish regulations state that the safety assessment for a final repository for spent nuclear fuel should be 1 million years after closure. SKB developed the KBS-3 method, according to which the spent nuclear fuel is protected by three barriers. It is encapsulated in canisters with a diameter of 1 metre and a length of 5 metres. The canister consists of a cast iron insert surrounded by a 5 centimetre thick shell of copper. The canisters are disposed in the bedrock at a depth of about 500 meters surrounded by bentonite clay. In order to assess the safety over this extremely long period, an extensive quality control programme is applied to the canisters before deposit. In this programme, the use of
non-destructive testing (NDT) is vital. The safety assessment of the canister in turn places high demands on the coverage, detectability, and reliability of the applied NDT inspections of the canister parts, i.e. cast iron insert, copper base, tube and lid, and the copper friction stir welds (FSW). This paper presents the extensive full-scale inspection development programme that runs at the Canister Laboratory in Oskarshamn (Sweden). In order to fulfil the high demands, phased array ultrasonic inspection techniques are developed using practical trials aided by ultrasonic modelling. The techniques apply, for example, different frequencies, inspection angles, focus depths, and both longitudinal and shear waves. Increased inspection reliability of the FSW is achieved by applying digital X-ray technique using a 9 MeV linear accelerator and a line detector. To complete the coverage, complementary surface inspections methods, i.e. eddy current array, magnetic flux sensor techniques and magnetic particle inspection, are applied. The canister safety assessment was the driving force to include reliability studies during the NDT development. Initially, the technical reliability was considered, resulting in development of advanced POD models (probability of detection). In combination with human factors studies, these models were implemented as tools in the development of the NDT techniques. Human factors studies were also applied to improve the inspection procedures to be more user-friendly enabling reliable inspections.
Ultrasonic phased array is, currently, the technology which is being applied as the solution to a lot of inspection problems. The perceived benefits are seen to be worth the outlay on equipment and specialised personnel. Yet, there is a source of knowledge, freely available, which can also deliver immediate benefits, through more reliable inspection results, and consequently increased client confidence, but which is largely ignored by the greater part of the NDT community. This talk will review the latest Human Factors knowledge and provide practical illustrations of how companies can use it to improve their competitive edge.
In comparison to manual NDT methods, mechanized NDT is considered to be more reliable for a number of reasons, one of which being that the role of the inspectors and, therewith, the potential for human error, have been reduced. However, human-automation interaction research suggests that in spite of its numerous benefits, automation can lead to new yet unknown risks. One of those risks is inappropriate reliance on automation, which can result in automation misuse and disuse. The aim of this study was to investigate the potential inappropriate use of automation (specifically - the automated aids) in NDT addressing therewith the prevalent belief in the high reliability of automation held by the NDT community. To address this issue, 70 NDT trainees were asked to control the results of an eddy current data evaluation, allegedly provided by an automated aid, i.e. indication detection and sizing software. Seven errors were implemented into the task and it was measured to what extent the participants agreed with the aid. The results revealed signs of both misuse (agreeing with the aid even though it is incorrect) and disuse (disagreeing with the aid even though it is correct) of the aid that can affect the reliability with which inspections are carried out. Whereas misuse could be explained by a lower propensity to take risks and by a decreased verification behaviour-possibly due to bias towards automation and complacent behaviour-, disuse was assigned to problems in establishing the sizing criterion or to general difficulties in sizing. The implications of these results for the NDT praxis including suggestions for the decrease of automation bias are discussed.
Non-destructive testing (NDT) is regarded as one of the key elements in ensuring quality of engineering systems and their safe use. A failure of NDT to detect critical defects in safetyrelevant components, such as those in the nuclear industry, may lead to catastrophic consequences for the environment and the people. Therefore, ensuring that NDT methods are capable of detecting all critical defects, i.e. that they are reliable, is of utmost importance. Reliability of NDT is affected by human factors, which have thus far received the least amount of attention in the reliability assessments. With increased use of automation, in terms of mechanised testing (automation-assisted inspection and the corresponding evaluation of data), higher reliability standards are believed to have been achieved. However, human inspectors, and thus human factors, still play an important role throughout this process, and the risks involved in this application are unknown. The overall aim of the work presented in this dissertation was to explore for the first time the risks associated with mechanised NDT and find ways of mitigating their effects on the inspection performance. Hence, the objectives were to (1) identify and analyse potential risks in mechanised NDT, (2) devise measures against them, (3) critically address the preventive measures with respect to new potential risks, and (4) suggest ways for the implementation of the preventive measures. To address the first two objectives a risk assessment in form of a Failure Modes and Effects Analysis (FMEA) was conducted (Study 1). This analysis revealed potential for failure during both the acquisition and evaluation of NDT data that could be assigned to human, technology, and organisation. Since the existing preventive measures are insufficient to defend the system from identified failures, new preventive measures were suggested. The conclusion of the study was that those preventive measures need to be carefully considered with respect to new potential risks, before they can be implemented, thus serving as a starting point for further empirical studies. To address the final two objectives, two preventive measures, i.e. human redundancy and the use of automated aids in the evaluation of NDT data, were critically assessed with regard to potential downfalls arising from the social interaction between redundant individuals and the belief in the high reliability of automated aids. The second study was concerned with the potential withdrawal of effort in sequential redundant teams when working collectively as opposed to working alone, when independence between the two redundant individuals is not present. The results revealed that the first redundant inspector, led to believe someone else will conduct the same task afterwards, invested the same amount of effort as when working alone. The redundant checker was not affected by the information about the superior experience of his predecessor and—instead of expected withdrawal of effort—exhibited better performance in the task. Both results were in contradiction to the hypotheses, the explanations for which can be found in the social loafing and social compensation effects and in the methodological limitations. The third study examined inappropriate use of the aid measured in terms of (a) agreement with the errors of the aid in connection to the frequency of verifying its results and in terms of (b) the overall performance in the task. The results showed that the information about the high reliability of the aid did not affect the perception of that aid’s performance and, hence, no differences in the actual use of the aid were to be expected. However, the participants did not use the aid appropriately: They misused it, i.e. agreed with the errors committed by the aid and disused it, i.e. disagreed with the correct information provided by the aid, thereby reducing the overall reliability of the aid in terms of sizing ability. Whereas aid’s misuse could be assigned to low propensity to take risks and reduced verification behaviour because of a bias towards automation, the disuse was assigned to the possible misunderstanding of the task. The results of these studies raised the awareness that methods used to increase reliability and safety, such as automation and human redundancy, can backfire if their implementation is not carefully considered with respect to new potential risks arising from the interaction between individuals and complex systems. In an attempt to minimise this risk, suggestions for their implementation in the NDT practice were provided.