Statistical process controls, quality management

Rollo JL, Fauser BA. Computers in Total Quality Management Statistical process control to expedite stats. Arch Pathol Lab Med 1993 117 ... 

Quality systems/statistical process control Toll chemistry Management of change Logistics Invoicing... 

Quality SPC (Statistical Process Control) or TQM (Total Quality Management) used to manage all quality processes... 

Quality in Japan. Japanese economic prowess has been attributed variously to such quahty improvement activities as quahty circles, statistical process control (SPG), just-in-time dehvery (JIT), and zero defects (ZD). However, the real key to success hes in the apphcation of numerous quahty improvement tools as part of a management philosophy called Kaizen, which means continuous improvement (10). 

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... 

Many of the quality improvement goals for implementation of PAT in the pharmaceutical industry have been achieved by companies in other industries, such as automobile production and consumer electronics, as a direct result of adopting principles of quality management. The lineage of modern quality management can be traced to the work of Walter Shewhart, a statistician for Bell Laboratories in the mid-1920s [17]. His observation that statistical analysis of the dimensions of industrial products over time could be used to control the quality of production laid the foundation for modern control charts. Shewhart is considered to be the father of statistical process control (SPC) his work provides the first evidence of the transition from product quality (by inspection) to the concept of quality processes [18,19]. 

To accomplish this, we must collect data. But how we collect that data is as important as the data themselves. Some data are worthless, some are priceless. The conditions and procedures used to find data ultimately determine their value. Statistical quality control (SQC), statistical process control (SPC), total quality management (TQM), and six sigma are all passive approaches to data collection. These procedures only observe and report what is happening. They cannot find the analytical cause-and-effect relationships needed for true process understanding and for controlling the sources of variability. 

Depending on the chosen approach (see Section 3.1) service quality can be measured from the customer s and the service provider s point of view. Measuring from the service provider s point of view involves gathering data that are internally available, such as performance measures or quality cost (Eversheim 1997). They can be analyzed using well-known methods from quality management in manufacturing processes, such as statistical process control (Gogoll 1996). In addition, service quality can be assessed indirectly by an overall analysis of the quality system, which is done by a... 

Variable probability method (utility function assessment), 2193, 2194 Variable state activation theory (VSAT), 2209 Variable tasks, 740 Variance(s), 2367 homogeneity of, 2255 and hypothesis testing, 2249-2252 hypothesis testing for equality of means and, for k populations, 2255-2256 reduction of, 2492-2493 residual, 2270-2271 and testing for mean value, 2244-2249 Variant process-planning systems, 475-477 Variation, 1828-1855, 2266. See also Statistical process control (SPC) common vs. special causes of, 1828-1832 and improvement of quality, 1831-1832 in management of processes, 1830-1831 measurement, process tolerances vs., 1986-1987... 

The recent trend towards total quality management (TQM) has generated a great deal of interest in statistical process control (SPC). This technique has been applied with good success in the discrete parts manufacturing industries. In the chemical process industries experience has been mixed, partly because of misunderstandings about its applicability to chemical processes and its interrelation to conventional process control. 

Statistical process controls (cause-and-effect diagrams, control charts, etc.), as applied in quality management, can serve as performance measures for safety, if they are used prudently and with caution. 

Safety professionals involved in quality management have had to become informed on statistical process control methods. I suggest that a broader application of those methods by our profession to measure safety performance would be beneficial. 

Gauge repeatability and reproducibility study Brainstorming and the traditional seven tools of quality Problem-solving methods The seven tools of management Failure mode and effect analysis Statistical process control Control charting... 

Quality Alert Institute (QAI), an internationally known firm specializing in total quality management and statistical process control training and implementation systems, offers a comprehensive seminar on the failure mode and effect analysis (FMEA) technique. 

Quality management including inspection and testing, laboratory results, and statistical process control. 

Variation is the fluctuations that can occur based on inconsistent environmental, human actions, equipment, tools, etc. Fluctuations of injuries and behaviors occur due to these variations in actions and conditions in the workplace. The statistical process control (SPC) (used in quality management) can aid in the review of injuries and observations, the organization can show the variations in its system. The SPC show whether the system is out of control and needs specific issues addressed or if it is in control but requires major across the broad safety program improvements (Daniels and Daniels, 2004 Deming, 1986). 

Chisholm, R. S. (2001),TQMS, statistically based in-process control with real time quality assurance, the AstraZeneca total quality management strategy, paper presented at the Science Board Presentations to FDA, Rockville, MD. 

When the analytical laboratory is not responsible for sampling, the quality management system often does not even take these weak links in the analytical process into account. Furthermore, if sample preparation (extraction, cleanup, etc.) has not been carried out carefully, even the most advanced, quality-controlled analytical instruments and sophisticated computer techniques cannot prevent the results of the analysis from being called into question. Finally, unless the interpretation and evaluation of results are underpinned by solid statistical data, the significance of these results is unclear, which in turn greatly undermines their merit. We therefore believe that quality control and quality assurance should involve all the steps of chemical analysis as an integral process, of which the validation of the analytical methods is merely one step, albeit an important one. In laboratory practice, quality criteria should address the rationality of the sampling plan, validation of methods, instruments and laboratory procedures, the reliability of identifications, the accuracy and precision of measured concentrations, and the comparability of laboratory results with relevant information produced earlier or elsewhere. 

Quality by Design is a systemic approach that applies the scientific method to the process. QbD theory contains components of management, statistics, psychology, and sociology. The FDA s new century has identified the QbD approach as its key component based on process quality control before industry end results [3,17]. 

The principles and concepts of TQM have been formalized into a quality management process, as illustrated in Figure 19-3. The traditional framework for managing quality in a healthcare laboratory has emphasized the establishment of quality laboratory processes (QLPs), QC, and quality assessment (QA). A QLP includes analytical processes and the general poHcies, practices, and procedures that define how all aspects of the work get done. QC emphasizes statistical control procedures but also includes nonstatistical check procedures, such as linearity checks, reagent and standard checks, and temperature monitors. QA, as currently applied, is primarily concerned with broader measures and monitors of laboratory performance, such as turnaround time, specimen identification, patient identification, and test utility. Quality assessment is the proper name for diese activities rather than quality assurance. Measuring performance does not by itself improve performance and often does not detect problems in time to prevent harmful effects. Quality... 

At the production line in question, the profiles surface quality and cross-section geometry deviation was already analyzed and recorded by online optical quality inspection systems. These camera based systems usually mark defective profile sections visibly, to separate them out for the operating personnel [910]. In some cases, this data was analyzed to quantify the amount and kind of failures statistically to control the rate of production faults. For an integrated management of process, user interaction, and fault information, and quantitative quality data, the records of these inspection systems also had to be integrated. 

In the air quality management approach, emission standards ate set in an attempt to achieve a previously set air quality standard (Fig. 4). This requires an allocation step, which apphes emission standards of different stringency to different processes to achieve the air quality standard goal. It should be noted that Fig. 4 shows a short-term statistical pathway to control air pollution episodes (Fig. 5). There has been less success with this... 

Quality assurance refers to activities that demonstrate that a certain quality standard is being met. This includes the management process that implements and documents effective QC. Quality control refers to procedures that lead to statistical control of the different steps in the measurement process. So QC includes specific activities such as analyzing replicates, ensuring adequate extraction efficiency, and contamination control. 

A laboratory QA/QC program is an essential part of a sound management system. It should be used to prevent, detect, and correct problems in the measurement process and/or demonstrate attainment of statistical control through QC samples. The objective of QA/QC programs is to control analytical measurement errors at levels acceptable to the data user and to assure that the analytical results have a high probability of acceptable quality. 

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