Human error case studies

The book begins with a discussion of the theories of error causation and then goes on to describe the various ways in which data can be collected, analyzed, and used to reduce the potential for error. Case studies are used to teach the methodology of error reduction in specific industry operations. Finally, the book concludes with a plan for a plant error reduction program and a discussion of how human factors principles impact on the process safety management system. 

The occurrence of human errors in anesthesia has become an important issue because in recent years many anesthesia-related deaths are considered to be the result of human error. A study of 589 anesthesia-related deaths revealed that human error was an important factor in 83% of the cases [7,8]. Additional facts and figures directly or indirectly concerned with human error in anesthesia are available in Ref. [2]. 

There is increasing interest in human factors issues in the CPI. Kletz (1991), Lorenzo (1990) and Mill (1992) address human error in the CPI, Kletz (1994) addresses human factors through case studies. 

The book provides a comprehensive set of examples and case studies that cover a wide variety of process plant situations. Some of these are intended to illustrate the range of situations where human error has occurred in the CPI (see Appendix 1). Other examples illustrate specific techniques (for example. Chapter 4 and Chapter 5). Chapter 7 contains a number of extended case studies intended to illustrate tedmiques in detail and to show how a range of different techniques may be brought to bear on a specific problem. 

Despite the lack of interest in human factors issues in the CPI in the past, the situation is now changing. In 1985, Trevor Kletz published his landmark book on human error in the CPI An Engineer s View of Human Error (revised in 1991). Several other books by the same author e.g., Kletz (1994b) have also addressed the issue of human factors in case studies. Two other publications have also been concerned specifically with human factors in the process industry Lorenzo (1990) was commissioned by the Chemical Manufacturers Association in the USA, and Mill (1992), published by the U.K. Institution of Chemical Engineers. In 1992, CCPS and other organizations sponsored a conference on Human Factors and Human Reliability in Process Safety (CCPS, 1992c). This was further evidence of the growing interest in the topic within the CPI. 

APPENDIX CASE STUDIES OF HUMAN ERROR LEADING TO ACCIDENTS OR FINANCIAL LOSS... 

The intention of this section is to provide a selection of case studies of varying complexity and from different stages of chemical process plant operation. The purpose of these case studies is to indicate that human error occurs at all stages of plant operation, and to emphasize the need to get at root causes. The case studies are grouped under a number of headings to illustrate some of the commonly recurring causal factors. Many of these factors will be discussed in later chapters. 

Insights into the human causes of accidents for a specific category of process plant installations are provided by the Oil Insurance Association report on boiler safety (Oil Insurance Association, 1971). This report provides a large number of case studies of human errors that have given rise to boiler explosions. 

The first set of case studies illustrates errors due to the inadequate design of the human-machine interface (HMI). The HMI is the boundary across which information is transmitted between the process and the plant worker. In the context of process control, the HMI may consist of analog displays such as chart records and dials, or modem video display unit (VDU) based control systems. Besides display elements, the HMI also includes controls such as buttons and switches, or devices such as trackballs in the case of computer controlled systems. The concept of the HMI can also be extended to include all means of conveying information to the worker, including the labeling of control equipment components and chemical containers. Further discussion regarding the HMI is provided in Chapter 2. This section contains examples of deficiencies in the display of process information, in various forms of labeling, and the use of inappropriate instrumentation scales. 

Because most research effort in the human reliability domain has focused on the quantification of error probabilities, a large number of techniques exist. However, a relatively small number of these techniques have actually been applied in practical risk assessments, and even fewer have been used in the CPI. For this reason, in this section only three techniques will be described in detail. More extensive reviews are available from other sources (e.g., Kirwan et al., 1988 Kirwan, 1990 Meister, 1984). Following a brief description of each technique, a case study will be provided to illustrate the application of the technique in practice. As emphasized in the early part of this chapter, quantification has to be preceded by a rigorous qualitative analysis in order to ensure that all errors with significant consequences are identified. If the qualitative analysis is incomplete, then quanhfication will be inaccurate. It is also important to be aware of the limitations of the accuracy of the data generally available... 

An extension of the tree of causes, called variation diagrams (Leplat and Rasmussen, 1984) was developed to answer some of these criticisms. In this method, the Rasmussen stepladder model of human error (see Chapter 2) is applied to analyze causal factors at each node of the tree. A detailed example of the use of this technique is provided in Chapter 7 (Case Study 1). 

During the PHEA stage, the analyst has to identify likely human errors and possible ways of error detection and recovery. The PHEA prompts the analyst to examine the main performance-influencing factors (PIFs) (see Chapter 3) which can contribute to critical errors. All the task steps at the bottom level of the HTA are analyzed in turn to identify likely error modes, their potential for recovery, their safety or quality consequences, and the main performance-influencing factors (PIFs) which can give rise to these errors. In this case study, credible errors were found for the majority of the task steps and each error had multiple causes. An analysis of two operations from the HTA is presented to illustrate the outputs of the PHEA. Figure 7.12 shows a PHEA of the two following tasks Receive instructions to pump and Reset system. 

Equipment Cracking Failure Case Studies Equipment fails either alone or in combination with other factors, including substandard materials, improper material selection, poor design, equipment abuse, unexpected stresses or environmental conditions, and poor maintenance practices and/or neglect. Many failures, in one way or another, involve human error to some extent. 

Abstract. This paper introduces an agent-hased approach to analyze the dynamics of accidents and incidents in aviation. The approach makes use of a number of elements, including formahzation of a real world scenario, agent-based simulation of variations of the scenario, and formal verification of dynamic properties against the (empirical and simulated) scenarios. The scenario formalization part enables incident reconstruction and formal analysis of it. The simulation part enables the analyst to explore various hypothetical scenarios under different circumstances, with an emphasis on error related to human factors. The formal verification part enables the analyst to identify scenarios involving potential hazards, and to relate those hazards (via so-called interlevel relations) to inadequate behavior on the level of individual agents. The approach is illustrated by means of a case study on a runway incursion incident, and a number of advantages with respect to the current state-of-the-art are discussed. 

Even if a technical failure precedes the human action, the tendency is to put the blame on an inadequate response to the failure by an operator. Perrow claims that even in the best of industries, there is rampant attribution of accidents to operator error, to the neglect of errors by designers or managers [155], He dtes a U.S. Air Force study of aviation accidents demonstrating that the designation of human error (pilot error in this case) is a convenient classification for mishaps whose real cause is uncertain, complex, or embarrassing to the organization. 

Investigations of industrial accidents reveal that most are caused by human error. The twentieth century s worst industrial disasters—Bhopal, Three Mile Island, and Chernobyl—helped clarify the complex chain of system problems that lead to human error. System problems are problems caused by a process system with built in design and operating deficiencies. The accidents provided numerous checklists and case studies for control room and equipment design. A partial list of some of the problems found at the industrial sites mentioned above are ... 

There is, however, a lot that can be learned from the published reports of famous failures and we shall return to this in the next chapter. It will be instructive though, before considering some case studies, to discuss in some detail the nature of human error and the common themes we might look for in such accounts. Those are the central purposes of this chapter. 

It is fundamental for assessing human error in systems analyses to identify and describe the human acts with importance for the event sequence under analysis (qualitative assessment). This corresponds to the task analyses, which are characteristic of ergonomic studies. Firstly, the important actions, the moment in time at which they are required and the time period available for their execution have to be determined. Furthermore, the requirements for the action, the information necessary, respectively available, the possibilities of correction in case of omission or faulty execution must be estabhshed. Additionally, other factors of important influence on human reliabihty such as the state of knowledge on the process in question, ergonomically favourable or disadvantageous layout of the workplace, the tools or the environment are identihed. On the basis of this task analysis reliability data (normally failure probabilities on demand) are assigned to the tasks identified. They stem from existing data collections (cf. Table 9.21). 

People and the jobs they do play an important safety role. Nowhere is this made more clear than in the study of aviation disasters, where, in more than two out of three cases, accident investigators are driven to conclude that human error played a major role (Edwards, 1988). These errors are not usually due to sudden illness, suicidal tendencies, wilful neglect or lack of basic abilities. More typically, they arise from temporary breakdown in skilled performance because, in many instances, system designers and managers have paid insufficient attention to human characteristics and skills, or not properly accounted for enviromnental stressors, workload and other reasonably foreseeable distractions. 

The case studies have illustrated how fundamental assumptions can he proved wrong and how multiple-level redundant systems can fail, especially when applied to human behaviour. Application software is seen to be particularly vulnerable in this regard, as was shown at Milton Keynes. Most if not all of the techniques and measures aimed at systematic failure avoidance involve human behaviour, where error rates ( failures ) are known to be much greater than those for physical devices. In the author s opinion this is where the effort should be directed. 

A study revealed that a Hong Kong teaching hospital administered 16,000 anesthetics in one year and reported 125 related incidents [16]. A subsequent investigation of these incidents clearly indicated that human error was a factor in 80% of the cases [16]. 

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