When an atom or molecule combines with oxygen, it tends to give up electrons to the oxygen in forming a chemical bond. Similarly, when it loses oxygen, it tends to gain electrons. Such changes are now described in terms of changes in the oxidation number, or oxidation state, of the atom or molecule (see valence). Thus oxidation has come to be defined as a loss of electrons or an increase in oxidation number, while reduction is defined as a gain of electrons or a decrease in oxidation number, whether or not oxygen itself is actually involved in the reaction.
In the formation of magnesium oxide from magnesium and oxygen, the magnesium atoms have lost two electrons, or the oxidation number has increased from zero to +2. This is also true when magnesium reacts with chlorine to form magnesium chloride. In solution, ferrous iron (oxidation number +2) may be oxidized to ferric iron (oxidation number +3) by the loss of an electron. In the reduction of cupric oxide the oxidation number of copper has changed from +2 to zero by the gain of two electrons. The two processes, oxidation and reduction, occur simultaneously and in chemically equivalent quantities. In the formation of magnesium chloride, for every magnesium atom oxidized by a loss of two electrons, two chlorine atoms are reduced by a gain of one electron each.
Oxidation-reduction reactions, called also redox reactions, are most simply balanced in the form of chemical equations by arranging the quantities of the substances involved so that the number of electrons lost by one substance is equaled by the number gained by another substance. In such reactions, the substance losing electrons (undergoing oxidation) is said to be an electron donor, or reductant, since its lost electrons are given to and reduce the other substance. Conversely, the substance that is gaining electrons (undergoing reduction) is said to be an electron acceptor, or oxidant.
Common reductants (substances readily oxidized) are the active metals, hydrogen, hydrogen sulfide, carbon, carbon monoxide, and sulfurous acid. Common oxidants (substances readily reduced) include the halogens (especially fluorine and chlorine), oxygen, ozone, potassium permanganate, potassium dichromate, nitric acid, and concentrated sulfuric acid. Some substances are capable of acting either as reductants or as oxidants, e.g., hydrogen peroxide and nitrous acid.
The corrosion of metals is a naturally occurring redox reaction. Industrially, many redox reactions are of great importance: combustion of fuels; electrolysis (oxidation occurs at the anode and reduction at the cathode); and metallurgical processes in which free metals are obtained from their ores.
HEART method is based upon the principle that every time a task is performed there is a possibility of failure and that the probability of this is affected by one or more Error Producing Conditions (EPCs) – for instance: distraction, tiredness, cramped conditions etc. – to varying degrees. Factors which have a significant effect on performance are of greatest interest. These conditions can then be applied to a “best-case-scenario” estimate of the failure probability under ideal conditions to then obtain a final error chance. This figure assists in communication of error chances with the wider risk analysis or safety case. By forcing consideration of the EPCs potentially affecting a given procedure, HEART also has the indirect effect of providing a range of suggestions as to how the reliability may therefore be improved (from an ergonomic standpoint) and hence minimising risk.
HEART was developed by Williams in 1986 [1]. It is a first generation HRA technique, yet it is dissimilar to many of its contemporaries in that it remains to be widely used throughout the UK. The method essentially takes into consideration all factors which may negatively affect performance of a task in which human reliability is considered to be dependent, and each of these factors is then independently quantified to obtain an overall Human Error Probability (HEP), the collective product of the factors.
1. The first stage of the process is to identify the full range of sub-tasks that a system operator would be required to complete within a given task.
2. Once this task description has been constructed a nominal human unreliability score for the particular task is then determined, usually by consulting local experts. Based around this calculated point, a 5th – 95th percentile confidence range is established.
3. The EPCs, which are apparent in the given situation and highly probable to have a negative effect on the outcome, are then considered and the extent to which each EPC applies to the task in question is discussed and agreed, again with local experts. As an EPC should never be considered beneficial to a task, it is calculated using the following formula:
4. A final estimate of the HEP is then calculated, in which the identified EPC’s play a large part in the determination of. Only those EPC’s which show much evidence with regards to their affect in the contextual situation should be used by the assessor [2].
A reliability engineer has the task of assessing the probability of a plant operator failing to carry out the task of isolating a plant bypass route as required by procedure. However, the operator is fairly inexperienced in fulfilling this task and therefore typically does not follow the correct procedure; the individual is therefore unaware of the hazards created when the task is carried out
There are various assumptions that should be considered in the context of the situation:
A representation of this situation using the HEART methodology would be done as follows:
From the relevant tables it can be established that the type of task in this situation is of the type (F) which is defined as ‘Restore or shift a system to original or new state following procedures, with some checking’. This task type has the proposed nominal human unreliability value of 0.03.
Other factors to be included in the calculation are provided in the table below:
| Factor | Total HEART Effect | Assessed Proportion of Effect | Assessed Effect |
|---|---|---|---|
| Inexperience | x3 | 0.4 | (3.0-1) x 0.4 + 1 =1.8 |
| Opposite technique | x4 | 1.0 | (6.0-1) x 1.0 + 1 =6.0 |
| Risk Misperception | x6 | 0.8 | (4.0-1) x 0.8 + 1 =3.4 |
| Conflict of Objectives | x2.5 | 0.8 | (2.5-1) x 0.8 + 1 =2.2 |
| Low Morale | x1 | 0.6 | (1.2-1) x 0.6 + 1 =1.12 |
The final calculation for the normal likelihood of failure can therefore be formulated as:
[1] WILLIAMS, J.C. (1985) HEART – A proposed method for achieving high reliability in process operation by means of human factors engineering technology in Proceedings of a Symposium on the Achievement of Reliability in Operating Plant, Safety and Reliability Society. NEC, Birmingham.
[2] Kirwan, B. (1994) A Guide to Practical Human Reliability Assessment. CPC Press.
[3] Humphreys. P. (1995). Human Reliability Assessor’s Guide. Human Reliability in Factor’s Group.
[4] Kirwan, B. (1996) The validation of three human reliability quantification techniques - THERP, HEART, JHEDI: Part I -- technique descriptions and validation issues. Applied Ergonomics. 27(6) 359-373.
[5] Kirwan, B. (1997) The validation of three human reliability quantification techniques - THERP, HEART, JHEDI: Part II - Results of validation exercise. Applied Ergonomics. 28(1) 17-25.
[6] Kirwan, B. (1997) The validation of three human reliability quantification techniques - THERP, HEART, JHEDI: Part III -- practical aspects of the usage of the techniques. Applied Ergonomics. 28(1) 27-39.
[7] http://www.hf.faa.gov/Portal/ShowProduct.aspx?ProductID=90