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1. Introduction This coursework is designed to look at the design and monitoring within organisations to ensure disasters dont happen. There have been many disasters in recent history such as Three Mile Island, Bhopal, Challenger, Chernobyl and the Herald of Free Enterprise. All calamitous events that represent loss of human lives, damage to the environment and loss in financial terms. Obviously, great care is taken to avoid such occurrences and this essay concentrates on the processes that address these issues. With the natural expansion and development of the global marketplace companies are under increasing competition to perform.
Management is subsequently under pressure to introduce enhanced processes and technology to deliver improvements in operational efficiency. From such developments transpire new and unknown human-machine interfaces and the role of humans in operating these systems. This is where the vital role of governance lies, and defines the manner in which design processes and operation are undertaken within an organisation. Governance also looks at understanding of the information contained within their system and the dispersion of this information and knowledge throughout the organisation. Disasters can be caused by a variety of sources such as technical or environmental but this focuses on the human factors, and desired elimination of, in causing such catastrophic system failures.
By its very nature human error is impossible to eliminate in totality. It is useless to attempt to change human nature; progress is made in designing the system to safely operate with humans as an integral part of the process. I believe it impossible to ensure no disasters will occur in the future, but this essay will look at the methods used to keep the possibilities of such disasters occurring to a minimum. I will look at the processes and principles applied to design and monitoring within organisations, where appropriate highlighting relevant case studies to illustrate my points. 2. Why disasters happen Disasters are more likely to occur with progression in technology and the complexity of systems. Over the past 30 to 40 years a technological revolution has occurred in the design and control of high-risk systems.
This has brought about radical and still little understood changes in the tasks that the human operator is expected to perform. There are several factors affecting human performance in such systems and different types of human error need to be recognised. 2. 1 Types of Errors Each disaster has various contributory factors but it is has been stated that 60 - 90 % of major accidents in complex systems have human error as a primary cause. Making errors is an integral part of our human nature demonstrated by a survey that showed skilled operators in word-processing select inefficient commands 30 % of the time. Defining error types is important to identify the cognitive state of the operator at the instant the erroneous action was undertaken.
This classification then allows processes to be formed that try to mitigate the effects of such error types reoccurring. 2. 1. 1 Error Classification A good classification of human error from an engineers viewpoint was defined by Klotz T. He separated errors into four broad classes. These are included here as a basis for discussion later into case studies. Mistakes: These are classed as errors made where the operator doesnt know what action to take or worse still, believes he is undertaking the correct action that is in fact wrong. These can be caused by either cognitive errors or because of the application of a rule that does not fit. Violations (Non- Compliance): These are where the operator knows what to do but doesnt.
Though often called violations the operator often believes a departure from the rules is justified, so a more appropriate name is non-compliance. Mismatches: Here the task was beyond the physical or mental ability of the operator. Slips: Here the intention is right but the action is wrong. 2. 1. 2 Latent and Active Errors In considering the human contribution to system disasters it is important to distinguish between two kinds of error: active and latent. The effects of active errors are felt almost immediately, whereas the adverse consequences of latent error can lie dormant within the system for some time, only becoming evident when they combine with other factors to breach the system defences. Active errors are generally associated with the front-line operators of a system such as control room operators. Latent errors are likely to originate in activities that are removed in both time and space from the direct control interface such as designers and maintenance personnel.
Analysis of recent disasters has revealed latent errors to be the greatest threat to safety in a complex system. One example of latent errors been the primary cause is the Bhopal incident where a gas leak from a small pesticide plant devastated the central Indian city of Bhopal. It could be argued here that the most significant error with respect to the entire incident was in locating such a high-risk plant so close to a densely populated area. This was a classical example of a latent error where the problem lied dormant from plant manufacture until the catastrophic incident where other contributory errors combined. This highlighted the latent error originating in government/ management that underpinned the disastrous effects on the local population. This is just one example of many for Bhopal and highlights the requirement of the governance body to spend time and money addressing such issues.
All types of errors learnt from incidents should be monitored and classified in order to learn from them, and reduce the possibility of such reoccurring in the future. 2. 2 Sources of Error Types of error have been outlined above but these errors can originate from a variety of areas. When analysing any serious disaster it is likely a contribution of several errors combined with tragic consequences. It should be acknowledged that these errors are not solely in the operators and design but also flow right up to managerial and government levels. In order to prevent disasters the causes need to be recognised so a case study looking at Chernobyl is undertaken in section 3. Obviously different incidents have different causes but Chernobyl covers the majority of such. 2. 3 Increased Automation in Complex Systems A remarkable development of recent years has been the extent to which human operators have become increasingly remote from the processes they nominally control. Machines of growing complexity now intervene between the human and the physical task.
The most profound changes to complex systems operations came with the advent of cheap computing power. This effectively introduced a human-computer interface (HCI) lying between the operator and the system. This interface now permits only limited interaction between the human and the now remote process. With the introduction of these systems driven by the governance body to improve efficiencies (and expected safety benefits), the system operates more effectively within normal system tolerances. However, in normal operation the human is purely in a supervisory role, loosely defined as initiating, monitoring, and adjusting processes in systems that are otherwise automatically controlled (Sheridan and Hennessy V 1984).
The problems arise when the human operator is required to take over when the system state drifts outside of this safe operational range. This type of supervisory role for the human operator is represented in the following diagram: Fig. 1 - The Basic Elements of Supervisory Control This sort of increasingly common control system has brought about a radical transformation of the human-system relationship. It can be seen that the computer rather than the human performs as the central actor. The main reason for the human operators continued presence is to apply the humans unique powers of knowledge-based reasoning to cope with system emergencies. Ironically, this task is particularly ill suited to the facets of human cognition. The problem lies in emergency scenarios that may be so alien and complex that humans perform badly making errors of judgement.
The generic probability of human error rises dramatically under stressful conditions and unfamiliar tasks: h Simple, frequently performed task, minimal stress 0. 001 h More complex task, time constraints, some care necessary 0. 01 h Complex unfamiliar task, little feedback, some distraction 0. 1 h Highly complex task, considerable stress, l...
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Research essay sample on Human Error Complex Systems
