Causal factor analysis conditions

Events and Causal Factor Analysis identifies the time sequence of a series of tasks or actions and the surrounding conditions leading to an occurrence as well as determines the causal factors. (See Chapter 9.)... 

This questioning should then be repeated for each and every event and condition, where applicable, and reviewed by others to ensure that nothing has been overlooked. Once everyone has agreed on all the results of the questioning, then your Causal Factor Analysis is complete. 

Events and causal factor analysis Use for multifaceted problems with long or complex causal factor chain Provides visual display of analysis process. Identifies probable contributors to the condition Time consuming and requires familiarity with process to be effective Requites a broad perspective of the event to identify unrelated problems. Helps to identify where deviations occurred from acceptable methods... 

Event and causal factors analysis includes charting, which depicts the logical sequence of events and conditions (causal factors that allowed the accident to occur), and the use of deductive reasoning to determine the events or conditions that contributed to the accident. 

Analysis, that can assist with the identihcation of causal factors. The concepts of incident causation encompassed in these tools are fundamental to the majority of investigation methodologies. (See Chapter 3 for information about the Domino Theory, System Theory, and HBT Theory.) The simplest approach involves reviewing each unplanned, unintended, or adverse item (negative event or undesirable condition) on the timeline and asking, Would the incident have been prevented or mitigated if the item had not existed If the answer is yes, then the item is a causal factor. Generally, process safety incidents involve multiple causal factors. 

Change analysis o) (also known as Change Evaluation/Analysis, CE/A) is another tool that can assist the identification of causal factors. It is useful for brainstorming about what has changed since conditions were safe, or perceived as safe. It may also be used for hypothesizing potential contributory factors to a hazardous condition or action. 

Event and causal factors charts are graphic representations that basically produce a picture of an accident—both the sequence of events that led to the accident and the conditions that were causal factors. This tool works very well in conjunction with PET or MORT analysis and is used widely in the Department of Energy. 

The event and causal factors chart is developed and expanded as new evidence and information become available. It should also be developed in conjunction with other analyses (change analysis and PET or MORT analysis), and information should be cross-checked (Fig. 19-2). Conditions that are causal factors on the event and causal factors chart should be identified as less than adequate areas on the PET, MORT, or mini-MORT chart. 

The Causal Factors Chart is a formal, and systematic, incident investigation and root cause analysis technique. The technique depicts the events and conditions leading up to an incident. It combines critical thinking, logical analysis, and graphic representations to analyze and depict an incident event scenario. It helps strncture the analysis and data gathering processes to ensure necessary and snfficient information is collected. The CFC also has been applied to Root Cause Analysis. The CFC is sometimes referred to as the Events and Causal Factors (ECF) chart. The ECF chart depicts the necessary and sufficient events and causal factors associated with a specific incident scenario. 

Software Fault Tree ( Soft Trees ) The soft tree technique is used to determine what software event, failure, or combination of each will result in a real or hypothetically loss event (a top event). This top-down analytical approach, which assumes a problem and then evaluates affecting conditions backward to determine causal factors, also takes into consideration any influencing environmental factors. It is concerned primarily with the analysis of any hardware-software interfaces that deal directly with the operation of mechanical components. 

The Significant Events and the Events and Conditions that allowed the Significant Events to occur are the accident s Causal Factors. Once all the significant events have been identified and all the Events and Conditions that do not belong in the analysis have been excluded, then an examination of the Events and Conditions preceding the significant event should be examined by asking a series of questions. 

A Fault Tree Analysis (FTA) is a top-down, deductive logic model that traces the failure pathways for a predetermined, undesirable condition or event, called the TOP Event. An FTA can be carried out either quantitatively or subjectively. The FTA generates a fault tree (a symbolic logic model) entering failure probabilities for the combinations of equipment failures and human errors that can result in the accident. Each immediate causal factor is examined to determine its subordinate causal factors until the root causal factors are identified. 

Causal factor chain. This is a cause and effect sequence where a specific action creates a condition that contributes to or results in an event. This creates new conditions that, in turn, result in another event, etc. Figure 12-1 summarizes a root cause analysis flow chart [2]. 

Since human errors consist the almost portion of causal factors of incidents in the target domain, the system provides the supports based on the Common Performance Conditions (CPCs), which is the description framework for the context of human performance adopted in the Cognitive Reliability and Error Analysis Method (CREAM) (Hollnagel 1998). 

A unique feature of the work in Groth and Mosleh (2012) is the use of empirical data to inform the BBN development, both for the graphical and quantitative parts data analysis (correlation and factor analysis) allows identifying the causal relationships among the PSF, their interaction to produce errors and some of the BBN conditional probabilities. The uniqueness relates to the fact that, as mentioned in the introduction, the typical approach for BBN applications in field with poor data availability is to use expert judgment for building the structure of the networks and then the available data for quantifying the relationships. 

Fault Tree Analysis employs an analytical tree to display the results of an analysis (Suokas and Rouhiainen, 1993). It starts with the top event (injury or damage). The analysis proceeds backwards in order to identify all events and conditions that have caused the injury or damage. Logical relations (necessary and/or sufficient conditions) are estabhshed. Fault-tree analysis is not an accident model per se and gives limited support in the identification of causal factors. 

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