Statistics control/safety

Dr. Frank P. Lees s Loss Prevention in the Process Industries Hazard Identification, Assessment and Control, Second Edition, ISBN 0750615478. This is a three-volume set published by Butterworth-Heinemann, Oxford, UK, 1996. Dr. Frank Lees s epic three-volume masterpiece is without a doubt the premier source of practical and statistical process safety reference material. Within the 3,962 pages of valuable facts, nearly every aspect of process safety is covered. The information is useful to process safety engineers, engineers in the process industries, insurance professionals,... 

Bringing processes into or near a state of statistical control will improve processes by making them less variable, centered closer to target, and allow the manufacturer to make a product that will more consistently meet product specifications. This benefits both the manufacturer and the consumers who use their products. The use of SPC methods to evaluate and to improve processes not only can be applied to product characteristics such as tablet weight and tablet hardness, but also to product performance measures such as consumer complaints, line down time, and industrial safety measurements. An SPC approach to process improvement can also lead to reductions in fill overages, reductions in waste, as well as reductions in batch failures. By eliminating special cause variability, it becomes easier to monitor a process to ensure that new special causes do not find their way into the process. 

One consideration for all statistical adjustment techniques in drug safety evaluation studies is the danger of the statistical adjustment itself introducing bias (Greenland and Morgenstern 2001). Statistical control can sometimes either increase bias or decrease precision without affecting bias and can thereby produce less reliable effect estimates (Schisterman et al. 2009). For example, bias can also be induced if an analysis improperly stratifies on a collider variable (Cole et al. 2010), that is, a variable that is itself directly influenced by two other variables. As a result, care is necessary in any evaluation study to develop a parsimonious model that achieves an appropriate balance between bias and variance. 

Miner s safety performance recognition, circa 1920s 20 The systems model of health and safety management 24 The size of mobile mine equipment continues to increase 27 Simple model of outcomes dependent on culture and systems 32 Statistical control chart with incident rate variation 33 Universal Copper and Metals Mine accident frequency rate control chart 55... 

The U chart is a critical tool for avoiding the overmanagement of a system that is in statistical control. It has been our experience that the U chart is frequently successful in helping traditional managers understand that accidents are produced by the process not by incompetent or unmotivated employees. These managers can then begin to look at safety improvement with a longer-term view and a systems perspective. 

The successes of the traditional approach have largely been obtained in the area of occupational safety, where statistical evidence is readily available concerning the incidence of injuries to individuals in areas such as tripping and falling accidents. Such accidents are amenable to behavior modification approaches because the behaviors that give rise to the accident are under the direct control of the individual and are easily predictable. In addition, the nature of the hazard is also usually predictable and hence the behavior required to avoid accidents can be specified explicitly. For example, entry to enclosed spaces, breaking-open process lines, and lifting heavy objects are known to be potentially hazardous activities for which safe methods of work... 

Quality Management system priorities to consider are management responsibility, quality system principles, auditing, contract review, design control, corrective action, document control, quality records, training, product safety and liability, and statistical techniques, because these are critical aspects of the Quality Management system where Xmple Inc. already has some systems in place. 

In a modern society, the investment in fire safety depends on the informed risk. Reliable risk must be based on complete statistics. An important motivator of the US government s interest to address the large losses due to fire in the early 1970s was articulated in the report of the National Commission on Fire Prevention and Control (.America Burning [1]). It stated that the US annually sustained over 11 billion in lost... 

The objective of clinical trials is to demonstrate the safety and effectiveness of the drug compared to placebo or control. The statistical method normally used is known as hypothesis testing. 

Sample sizes for clinical trials are discussed more fully elsewhere in this book and should be established in discussion with a statistician. Sample sizes should, however, be sufficient to be 90% certain of detecting a statistically significant difference between treatments, based on a set of predetermined primary variables. This means that trials utilising an active control will generally be considerably larger than placebo-controlled studies, in order to exclude a Type II statistical error (i.e. the failure to demonstrate a difference where one exists). Thus, in areas where a substantial safety database is required, for example, hypertension, it may be appropriate to have in the programme a preponderance of studies using a positive control. 

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