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An ethnic or society-based culture is based on the norms for the ethnic or society group. A cultural human factor, for example, might be that people in the U.S. read from left to right while some other cultures read from right to left. Another one is that some societies prefer group consensus over individual action.
Human factors also can be situational, that is, how humans interact with a particular situation or set of conditions. For example, in one plant an arrangement of process equipment may be a particular way, while in a very similar plant the arrangement may be slightly different. Or simply, the number of people involved in a situation at a given instant might be different, which could affect how a situation is reacted to.
Not All Human Factors Are Bad
There are bad human factors and good human factors. Human factors that facilitate error or poor performance are bad ones, while human factors that minimize errors or improve performance are good human factors.
Some common human factors to consider that can cause human errors are management systems (communication, training, scheduling, culture, style, work load, etc.), procedures (response to upset, operational procedures, plant practices, etc.), physical factors (ergonomics), organization (presentation, order, structure, etc.), and facility design (equipment, controls, environment, etc.).
Some other human factors to consider are how humans process information--how much information can a human process at a time, how fast we can process information, short-term and long-term memory, how humans handle complex situations, mindset, human interaction, group think (opposite of synergy--i.e., the sum of the parts is less than the whole.
Human factors exist everywhere in the lifecycle of an instrument system. Anything that makes things difficult in the implementation, operation, and maintenance of instrument systems can lead to human factor-facilitated errors. Design, operation, and maintenance procedures, practices, and systems that ignore how people really work can facilitate errors and poor performance. Examples are failure to do the upfront design properly, a poor change management system, overly complex instrument operation, complex procedures, an instrument location that makes it hard to work on, overly complex work procedures, poor supervision, etc.
Many human errors are due to or facilitated by human factors. The Battelle study of incidents in refineries indicated that 19% of the incidents involved random human error, while 81% involved human factors. Many times there is a rush to blame “human error” (meaning a particular individual making an error) because it is an easy out and does not place any blame on the company while underlying human factors are ignored. This is sometimes known as the scapegoat syndrome.
Human factors are a significant aspect when designing, operating, and maintaining instrument systems to minimize human errors. Their effect and consideration of human factors should be part of the lifecycle of any instrument system.
Human factors should be considered in all designs, procedures, and practices as a value-added practice and in some cases a matter of law. In fact, the importance of this is recognized by OSHA regulation 29 CFR 1910.119, Process Safety Management (PSM), which requires that the process hazards analysis (PHA) address human factors.
Human Errors In Safety Systems
Errors may also be classified on the basis of safety or not. Safety errors may result in an accident, a near miss or an accident waiting to happen. Safety errors caused by humans in safety instrumented systems (SIS) are called “systematic” errors.
In a commonly reported Health and Safety Executive (U.K.) study on failure of control and safety systems, 85% of the failures were attributed to failure to get the proper specification, changes after commissioning, installation and commissioning, and design and implementation, while only 15% were associated operation and maintenance.
Approaches to Human Error Reduction
There are a number of approaches for dealing with human error. Some of the main ones are prevention, anticipation, tolerance, mitigation, and lifecycle approach.
1. Prevention: Errors can be viewed in different context. One context is: an error is an error when the error is made; while another context is: an error is not really an error until the error causes an effect. These two contexts lead to two different approaches to error prevention.
In first context, we can only prevent error if the error is not made at all. This is obviously an efficient (but many times difficult) means of keeping errors out of a system; it falls under the often-used quality statement “Do it right the first time, every time.” This is a front-end process. Primary methods used to reduce this type of error are highly motivated, competent people and the reduction of human factors-facilitated errors.
In the second context, we assume errors will enter the system but we wish to catch the error before it has a negative effect. For example, an error was made on specifying the range of a transmitter but it does not have any effect until the transmitter is put into service. If we can catch the error before the transmitter is put into service, we can then catch the error before it has a negative effect. This is a back-end process and is less efficient than the first context. Review and supervision processes are commonly used to reduce this type of error. Unfortunately, many times these processes are somewhat informal, have no organized methodology in reducing errors, and seldom consider human factors.
2. Anticipation: This is where a potential error is identified and the opportunity for the error is minimized or eliminated. Human factors that facilitate an error can be changed to minimize the possibility of the error occurring. An administrative or engineering control can be used to minimize the potential for error.
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