Quality control statistics

Cornell J.A., How to Apply Response Surface Methodology. Basic References in Quality Control Statistical Techniques, Vol. 8. Milwaukee American Society for Quality Control, 1985. 

No recent pharmacopeia was issued without notable contributions by the Pharmaceutical Research Manufacturers of America through its standing technical committees in quality control, statistics, and biologi-cals. Careful reference to the PF also will reveal many contributions by scientists from individual member companies. 

Chemical process control—Statistical methods. 2. Chemical industry—Quality control—Statistical methods. 1. Palazoglu, Ahmet. 11. Kayihan,... 

Evaluate well-to-well assay performance by testing entire plates containing negative (no inhibition) and positive (100 % inhibition) controls, and calculating assay statistics, including S/B, S/N and Z -factor. Desired quality control statistics are S/B >5, S/N>10, and Z >0.6. Repeat the experiment on at least one more day to evaluate day-to-day performance. 

CORNELL, J. A. How to apply response surface methodology, in The ASQC basic references in quality control statistical techniques. SHAPIRO, S. S. and MYTCYTKA, E. F. (eds.), Milwaukee, WI, American Society for Quality Control, EUA, 1990a. 

American Society for Quality Control Statistics Division, Glossary and Tables for Statistical Quality Control, American Society for Quality Control, 1996. 

The written directives of a quality control program are a necessary, but not a sufficient, condition for obtaining and maintaining an analysis in a state of statistical control. Although quality control directives explain how an analysis should be properly conducted, they do not indicate whether the system is under statistical control. This is the role of quality assessment, which is the second component of a quality assurance program. 

Quality control encompasses all activities used to bring a system into statistical control. The most important facet of quality control is written documentation, including statements of good laboratory practices, good measurement practices, standard operating procedures, and protocols for a specific purpose. 

Statistical quality control is used to first measure and then continuously improve product quality. For example, The Dow Chemical Company s average 1989 performance compared to the typical sales specification were purity, = 99.65 wt % color, APHA = 4 acid (as HCl) = 7.3 ppm and water = 26 ppm. Averages of properties were based on rail car and tank tmck shipment samples during 1989. 

More details on statistical process control are available in several textbooks (Grant and Leavenworth, Statistical Quality Control, McGraw-HiU, New York, 1980 Montgomery, Introduction to Statistical Quality Control, Wiley, New York, 1985). 

Historical DataBase Subsystem We have discussed the use of on-hne databases. An historical database is built similar to an on-line database. Unlike their on-line counterparts, the information stored in a historical database is not normally accessed directly by other subsystems for process control and monitoring. Periodic reports and longterm trends are generated based on the archived data. The reports are often used for long-term planning and system performance evaluations such as statistical process (quality) control. The trends may be used to detect process drifts or to compare process variations at different times. 

Several methods have evolved to achieve, sustain, and improve quality, they are quality control, quality improvement, and quality assurance, which collectively are known as quality management. This trilogy is illustrated in Figure 2.1. Techniques such as quality planning, quality costs, Just-in-time , and statistical process control are all elements of... 

Statistical process control (SPC) is an important on-line method in real time by which a production process can be monitored and control plans can be initiated to keep quality standards within acceptable limits. Statistical quality control (SQC) provides off-line analysis of the big picture such as what was the impact of previous improvements. It is important to understand how SPC and SQC operate. 

In passing we remark that there are well-known statistical methods of hypothesis testing and parameter estimation used in decisionmaking. Sequential analysis is a method of sampling used to decide whether to accept or reject a lot with defective items, or whether to continue sampling. Also, there are various statistical methods used in quality control of a manufacturing process, to decide on how much the quality should be improved to be acceptable. 

The Production Department was not amused, because lower values had been expected. Quality Control was blamed for using an insensitive, unse-lective, and imprecise test, and thereby unnecessarily frightening top management. This outcome had been anticipated, and a better method, namely polarography, was already being set up. The same samples were run, this time in duplicate, with much the same results. A relative confidence interval of 25% was assumed. Because of increased specificity, there were now less doubts as to the amounts of this particular heavy metal that were actually present. To rule out artifacts, the four samples were sent to outside laboratories to do repeat tests with different methods X-ray fluorescence (XRFi °) and inductively coupled plasma spectrometry (ICP). The confidence limits were determined to be 10% resp. 3%. Figure 4.23 summarizes the results. Because each method has its own specificity pattern, and is subject to intrinsic artifacts, a direct statistical comparison cannot be performed without first correcting the apparent concentrations in order to obtain presumably true... 

Rodbard, D. et al. Statistical Quality Control of Radioimmunoassays.. 1. Clin. Endocrinol, and Metab. (1968),... 

Rodbard, D. Statistical Quality Control and Routine Data... 

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