Human error generally

It should be noted that the second step Intends to overcome the "human error". Generally such problems can be solved by using technical procedures. Hawever this is not recommended because human-beings are error prone. 

Minimal cut sets are then ranked. Two factors are considered in the ranking procedure. The first factor considers stmcture, ie, a one-event minimal cut set is more important than a two-event minimal cut set. The implication is that one event is more likely to occur than two events, two events are more likely than three events, and so on. The second factor considers ranking within equal-size minimal cut sets. The general ranking rules consider the probabihty of human error, active equipment failure, and passive equipment failure (73). 

In general, the risk of human error ean he redueed hy properly designing the equipment, proeedures, and the work environment and hy proper staffing, training, and implementation of management eontrols. 

A major reason for the neglect of human error in the CPI is simply a lack of knowledge of its significance for safety, reliability, and quality. It is also not generally appreciated that methodologies are available for addressing error in a systematic, scientific manner. This book is aimed at rectifying this lack of awareness. 

Measures to reduce human error are often implemented at an existing plant, rather than during the design process. The decision to conduct an evaluation of the factors that can affect error potential at an existing plant may be taken for several reasons. If human errors are giving rise to unacceptable safety, quality or production problems, plant management, with the assistance of the workforce, may wish to carry out a general evaluahon or audit of the plant in order to identify the direct causes of these problems. 

These various aspects of evaluating, predicting, and reducing human error form part of a general strategy for managing error which will be described in Chapter 5. 

HFAM has 20 groups of factors instead of the 10 general failure types of the TRIPOD approach. The reason for this is that all of the 10 TRIPOD GFTs would be applied in all situations, even though the actual questions that make up the factors may vary. In the case of HFAM, it would be rare to apply all of the factors unless an entire plant was being evaluated. HFAM uses a screening process to first identify the major areas vulnerable to human error. The generic factors and appropriate job specific factors are then applied to these areas. For example, control room questions would not be applied to maintenance jobs. 

In addition to their descriptive fimctions, TA techniques provide a wide variety of information about the task that can be useful for error prediction and prevention. To this extent, there is a considerable overlap between Task Analysis and Human Error Analysis (HEA) techniques described later in this chapter. HEA methods generally take the result of TA as their starting point and examine what aspects of the task can contribute to human error, hr the context of human error reduction in the CPI, a combination of TA and HEA methods will be the most suitable form of analysis. 

Although OSDs can be used to optimize general operator performance, they are limited to the extent that they can identify human errors. 

The decomposition approach is used, it is necessary to represent the way in which the various task elements and other possible failures are combined to give the failure probability of the task as a whole. Generally, the most common form of representation is the event tree (see Section 5.7). This is the basis for THERP, which will be described in the next section. Fault trees are only used when discrete human error probabilities are combined with hardware failure probabiliHes in applications such as CPQRA (see Figure 5.2). 

The overall conclusion that can be drawn from a survey of CPI data collection systems is that the better systems do attempt to address the causes of human error. However, because of the lack of knowledge about the factors which influence errors, the causal information that is collected may not be very useful in developing remedial strategies. General information in areas such as severity, work control aspects and the technical details of the incident will be required in all data collection systems. However, in almost all cases a structured process for causal analysis is lacking. Some of the requirements for causal analysis are set out in the following sections. 

The general approach that has been advocated in this chapter is that it is the responsibility of an organization, through its safety management policies, to create the systems, environment, and culture that will minimize human error and thereby maximize safety. 

Some general types of Human Errors are also included. 

Appendix III contains failure rate estimates for various genetic types of mechanical and electrical equipment. Included ate listings of failure rates with range estimates for specified component failure modes, demand probabilities, and times to maintain repair. It also contains some discussion on such special topics as human errors, aircraft crash probabilities, loss of electric power, and pipe breaks. Appendix III contains a great deal of general information of use to analysts on the methodology of data assessment for PRA. 

A human error or reliability analysis (HRA) can be performed to identify points that may contribute to an accidental loss. Human errors may occur in all facets of a the hydrocarbon industry. They are generally related to the complexity of the equipment, human-equipment interfaces, hardware for emergency actions, and procedures for operations, testing and training. The probabilities of certain types of errors occurring are normally predicted as indicated in Table 29. Individual tasks can be analyzed to determine the probability of an error occurring. From these probabilities, consequences can be identified which detemline the risk of a particular error. 

There are several approaches to cleaning. The favored approach is clean-in-place (CIP), in which cleaning solutions are piped to the vessel under computer control. In cases where CIP is not suitable, clean-out-of-place (COP) is used. This approach is mostly for smaller items. COP may be carried out manually or with automated tanks. A third approach is manual cleaning, although this is prone to human error and is not generally adopted. 

Microprocessors boards are used on smaller RO units that require minimum input/output (I/O) function. In general, standard manufactured microprocessor boards, inexpensive are used. Troubleshooting a microprocessor board can be difficult without proper documentation and experience. In many cases, it would be quicker and more cost effective to replace a mal-functioning control board. Damage is usually caused by human errors on field wiring. 

In this chapter we will rephrase, summarise and extend the set of practical aspects related to designing and implementing near miss reporting systems. First five general factors will be listed, followed by a more detailed discussion of two of these data collection, and acceptability. Also the overall important factor of training will be briefly outlined, Finally the relationship between an organisation s prevailing view of human error and its safety culture will be discussed. 

The authors have checked with sources believed to be reliable in their efforts to provide information that is complete and generally in accord with the standards of practice that are accepted at the time of publication. However, in view of the possibility of human error or changes in medical sciences, neither the authors, nor the editor and publisher, nor any other party who has been involved in the preparation or publication of this work warrants that the information contained herein is in every respect accurate or complete, and they are not responsible for any errors or omissions or the results obtained from the use of such information. Readers are encouraged to confirm the information contained in this book with other sources. 

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