Error Causal Factors

Literature has many theories and concepts discussing human reliability and associated human error causal factors that always trigger incidents and accidents within safety-critical systems. The main - by definition - characteristics of such safety occurrences are their randonmess, rare predictability, sophisticated, yet vague sequence of propagation. Such characteristics can basically allow for the retrospective analysis of these occurrences and their causes at various sectors and levels within industry such that re-occurrence margins are reduced if not totally eliminated. The major drawback of such reactive treatment... 

AMMP works in two complementary folds Design and manufacturing as well as workplace and maintainers orientations. Consequently, the process is intended to effectively monitor the seen and/or inherent existence of maintenance human errors causal factors... 

Safety professionals will do a better job in giving counsel on serious injury prevention if they are aware of human error causal factors. Focusing on improving management systems to meet ZIO provisions and minimizing serious injuries, this chapter ... 

This is a highly recommended text. Chapter 6 is titled Data Collection and Incident Analysis Methods. Elsewhere, comments are made on types of human error causal factors, their nature, and how to identify and analyze them. 

In addition to these formal studies of human error in the CPI, almost all the major accident investigations in recent years, for example, Texas City, Piper Alpha, Phillips 66, Feyzin, Mexico City, have shown human error as a significant causal factors in design, operations, maintenance or the management of the process. Figures 4.4-1 and 4.4-2 show the effects of human error on nuclear plant operation. 

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. 

There will be strong emphasis on the collection of data on possible causal factors that could have contributed to an accident. The specific data that are collected may be based on an error model such as that shown in Figure 6.2. However, this model will usually be modified depending upon the extent to which it fits the data collected over a period of time. The systems approach is therefore dynamic rather than static. 

It should be emphasized that it is usually necessary to develop the data collection specification on an incremental basis and to utilize feedback from the system to modify the initial model relating causal factors to error types. This dynamic approach provides the best answer to the problem that no predefined error model will be applicable to every situation. 

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). 

In the second case study, variation tree analysis and the events and causal factors chart/root cause analysis method are applied to an incident in a resin plant. This case study illustrates the application of retrospective analysis methods to identify the imderlying causes of an incident and to prescribe remedial actions. This approach is one of the recommended strategies in the overall error management framework described in Chapter 8. 

The human factors audit was part of a hazard analysis which was used to recommend the degree of automation required in blowdown situations. The results of the human factors audit were mainly in terms of major errors which could affect blowdown success likelihood, and causal factors such as procedures, training, control room design, team communications, and aspects of hardware equipment. The major emphasis of the study was on improving the human interaction with the blowdown system, whether manual or automatic. Two specific platform scenarios were investigated. One was a significant gas release in the molecular sieve module (MSM) on a relatively new platform, and the other a release in the separator module (SM) on an older generation platform. 

Once the evidence has heen collected and a timeline or sequence diagram developed, the next phase of the investigation involves identifying the causal factors. These causal factors are the negative occurrences and actions that made a major contrihution to the incident. Causal factors involve human errors and equipment failures that led to the incident, hut can also he undesirable conditions, failed harriers (layers of protection, such as process controls or operating procedures), and energy flows. Causal factors point to the key areas that need to he examined to determine what caused that factor to exist. 

Find the facts in the main sequence on the Causal Factor Chart that describe a component failure or a human error. Ensure the fact is not describing a management system failure (i.e., ensure the fact is not a root cause, near root cause, or root cause category). The identified negative events/conditions are candidate causal factors. Any candidate causal factor that is not dependent on another candidate causal factor is a valid causal factor. 

Once the timeline or sequence diagram based upon the actual scenario has been developed, the next phase of the investigation involves identifying the causal factors. Causal factors involve human errors and equipment failures that led to the incident, but can also be undesirable conditions and... 

Therefore, in using the classification, the following fixed order is proposed (as indicated from top to bottom in figure 5,1.) to arrive at the best-fitting error category for causal factors of accidents and near misses first K-B errors, then R-B and finally S-B errors. In this way the above mentioned... 

A more careful comparison has also been made. JAXA (the Japanese Space Agency) and MIT engineers compared the use of STPA on a JAXA unmanned spacecraft (HTV) to transfer cargo to the International Space Station (ISS). Because human life is potentially involved (one hazard is collision with the International Space Station), rigorous NASA hazard analysis standards using fault trees and other analyses had been employed and reviewed by NASA. In an STPA analysis of the HTV used in an evaluation of the new technique for potential use at JAXA, all of the hazard causal factors identified by the fault tree analysis were identified also by STPA [88]. As with the BMDS comparison, additional causal factors were identified by STPA alone. These additional causal factors again involved those related to more sophisticated types of errors beyond simple component failures and those related to software and human errors. 

Certainly, operator errors may be causal factors in accident occurrences. But, consider Ted Ferry s comments on this subject as expressed in Modern Accident Investigation and Analysis An Executive Guide. 

Chapanis message is this If the design of the work is error-provocative, you can be certain that errors will occur, in the form of accident causal factors. 

It is illogical to conclude in an incident investigation that the principal causal factor is the unsafe act of the worker if the design of the workplace or the work methods is error-provocative. In such cases, the error-provocative aspects of the work should be considered primary. (A few organizations are giving courses on Preventing Human Error which focus on how to identify and prevent what they are calling error-likely work situations. This is a recent development.)... 

Note the terminology numerous failures, and a series of apparently unrelated breakdowns and errors. An aspect of many incidents that result in severe injury is the cascading effect of multiple causal factors acting in sequence — sometimes in multiple and parallel sequences—toward an undesirable end. 

A practice of safety based principally on the many extensions of the causation model represented by the domino sequence developed by H. W. Heinrich that focus on the so-called unsafe act or human error as the principal causal factor will be ineffective in relation to the actuality of causal factors. 

Use of Heinrich s ideas has led to oversimplification and has encouraged identifying a single causal factor for incidents focusing on employee error. Johnson makes these statements about accident causation in MORT Safety Assurance Systems ... 

But, there has been a significant and appropriate change in the MORT literature concerning the identification of causal factors. In a November 1994 publication titled Guideline to Use of the Management Oversight and Risk Tree, this appears under Performance Errors ... 

This is a serious subject. For incident causal factors that are actions or inactions of individuals, their so-called errors may be programmed into the work system created for them. And a causation model has to address the programming sources. 

Kletz also suggested that we should do away with the term human error, since it gets in the way of inquiry to determine real causal factors (p. 182). 

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