Intentional errors

The actions mentioned above are composed of one or several tasks or steps. Intentional errors such as sabotage are normally not addressed, since their probability can virtually not be determined. 

The scope of this chapter in restricted to unintentional errors only and does not extend to intentional errors or sabotage. 

Intentional Errors (also referred to as violations). An intentional error does not include sabotage. The difference is in the motive. It concerns an action committed or omitted deliberately, because of a perception that there is a better or equally effective way to perform the task or step. Not following prescribed procedures is often a shortcut that may not be recognised as a mistake until other conditions arise that result in a noticeable problem. 

Errors caused by insufficient special preparation, training, and instruction workers do not know what to do, or they think they do, but they really do not. These errors are called the incorrect intent errors. 

Reason [2] indicates that human error is intimately related to the concept of "intent . Error is only a meaningfiil term when lied to intended (plamied) actions that fiiil to achieve the desired goal without the intervention of some chance or unforeseeable agency. Thus, non-intentional, involuntary and spontaneous actions are not errors. Reason identifies two basic types of error sups and mistakes. 

Another type of intentional error is categorized in Figure 8.1 as a violation. Someone in authority deliberately decides not to follow a rule because, in his or her judgment, doing so will lead to safer or better operations. For example, an operations supervisor may choose to ignore a lab result or an instrument reading and not take the actions that those results would suggest he or she take, either because he or she does not believe the result or because he or she thinks that there is a better method of operation. 

As the feed composition approaches a plait point, the rate of convergence of the calculation procedure is markedly reduced. Typically, 10 to 20 iterations are required, as shown in Cases 2 and 6 for ternary type-I systems. Very near a plait point, convergence can be extremely slow, requiring 50 iterations or more. ELIPS checks for these situations, terminates without a solution, and returns an error flag (ERR=7) to avoid unwarranted computational effort. This is not a significant disadvantage since liquid-liquid separations are not intentionally conducted near plait points. 

For single rings (i.e. mononuclear systems) up to ten atoms in size, there is no question but that Hantzsch-Widman names are overwhelmingly the most widely used, and specialists can be presumed to recognize them readily. However, when one of the trivial names of Table 1 can be used, it prevails almost exclusively. Thiophene will be immediately understood by specialists and most nonspecialists, whereas thiole will distract the reader s attention from the chemistry while he considers the writer s intention is the Hantzsch-Widman system indeed being used, or is it a typographical error Chemical Abstracts also uses these trivial names in its indexes. 

INTENT Human error rate assessment for INTENTion-based errors I Gertman ct al., 1992... 

Returning to the standard, this clause also only addresses the correction and prevention of nonconformities, i.e. departures from the specified requirements. It does not address the correction of defects, of inconsistencies, of errors, or in fact any deviations from your internal specifications or requirements. As explained in Part 2 Chapter 13, if we apply the definition of nonconformity literally, a departure from a requirement that is not included in the Specified Requirements is not a nonconformity and hence the standard is not requiring corrective action for such deviations. Clearly this was not the intention of the requirement because preventing the recurrence of any problem is a sensible course of action to take, providing it is economical. Economics is, however, the crux of the matter. If you include every requirement in the Specified Requirements , you not only overcomplicate the nonconformity controls but the corrective and preventive action controls as well. 

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. 

With regard to mistakes, two separate mechanisms operate. In the rule-based mode, an error of intention can arise if an incorrect diagnostic rule is used. For example, a worker who has considerable experience in operating a batch reactor may have learned diagnostic rules that are inappropriate for continuous process operations. If he or she attempts to apply these rules to evaluate the cause of a continuous process disturbance, a misdiagnosis could result, which could then lead to an inappropriate action. In other situations, there is a tendency to overuse diagnostic rules that have been successful in the past. 

In the skill-based mode, recovery is usually rapid and efficient, because the individual will be aware of the expected outcome of his or her actions and will therefore get early feedback with regard to any slips that have occurred that may have prevented this outcome being achieved. This emphasizes the role of feedback as a critical aspect of error recovery. In the case of mistakes, the mistaken intention tends to be very resistant to disconfirming evidence. People tend to ignore feedback information that does not support their expectations of the situation, which is illustrated by case study 1.14. This is the basis of the commonly observed "mindset" syndrome. 

Task analysis is a fundamental methodology in the assessment and reduction of human error. A very wide variety of different task analysis methods exist, and it would be impracticable to describe all these techniques in this chapter. Instead, the intention is to describe representative methodologies applicable to different types of task. Techniques that have actually been applied in the CPI will be emphasized. An extended review of task analysis techniques is available in Kirwan and Ainsworth (1993). 

The approach is not a satisfactory method of identifying mistaken intentions or diagnostic errors. 

The intention of this chapter has been to provide an overview of analytical methods for predicting and reducing human error in CPI tasks. The data collection methods and ergonomics checklists are useful in generating operational data about the characteristics of the task, the skills and experience required, and the interaction between the worker and the task. Task analysis methods organize these data into a coherent description or representation of the objectives and work methods required to carry out the task. This task description is subsequently utilized in human error analysis methods to examine the possible errors that can occur during a task. 

Advocates of the global approach would argue that human activities are essentially goal-directed (the cognitive view expressed in Chapter 2), and that this cannot be captured by a simple decomposition of a task into its elements. They also state that if an intention is correct (on the basis of an appropriate diagnosis of a situation), then errors of omission in skill-based actions are imlikely, because feedback will constantly provide a comparison between the expected and actual results of the task. From this perspective, the focus would be on the reliability of the cognitive rather than the action elements of the task. 

Mistakes Errors arising from a correct intentions that lead to incorrect action sequences. Such errors may arise, for example, from lack of knowledge or inappropriate diagnosis. 

Slips Errors in which the intention is correct but failure occurs when carrying out the activity required. Slips occur at the skill-based level of information processing. 

Violation An error that occurs when an action is taken that contravenes known operational rules, restrictions, and/or procedures. The definition of violations excludes actions taken to intentionally harm the system (i.e., sabotage). 

My views on this subject obviously have been influenced by the literature of the field, and my citations to this literature can serve as acknowledgment of this debt less obviously my views have also been influenced by teachers, colleagues, and students, to whom I express my thanks. Where I have strayed, intentionally or in error, from accepted interpretations, I accept responsibility and hope that students may be led to think independently by such deviant notions. 

Accidental explosions arc potentially the most dmigcrous Uiey arc a major concern for any industrial plant that deals with either pressurized or flammttble gases. An accidental explosion occurs not by design and tliercforc is not similar to an intentional e.xplosion, where the conditions are planned and can be controlled. Accidental e.xplosions usuttlly arc the result of equipment failure or operator error. Although accidental explosions are by definition unforeseen events, tlie procedures discussed in the ne.xt chapter may be implemented either to minimize tlieir effects or to prevent tlicm entirely. 

Validation of the data management system is typically done in two rounds. First, correctly completed data forms are entered to ensure that the system is not flagging any good data. In the second round, completed data forms with intentional data errors are entered. All errors must be identified by the system. 

Thus, to further the goals of quality and good analytical practice for which RMs are intended, EQA schemes should combine some aspects of both objectives according to the political purposes for which the scheme is being organized. Whether used for educational or licensing purposes, the ultimate intention is to ensure a certain standard of analysis is achieved and maintained in order that the user of results may be protected against errors which could be costly, in financial or human terms. 

If the basis set is mathematically complete, then the equation holds precisely. In practice, one has to work with an incomplete finite basis set and hence the equality is only approximate. Results close to the basis set limit (the exact HF solutions) can nowadays be found, but for all practical intents and purposes, one needs to live with a basis set incompleteness error that must be investigated numerically for specific applications. 

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