Quality engineering QII
Quality technology QII is called a quality technology in quality management, which among other things can lead to a reduction in error costs . In addition to the quality methods of the Seven Quality Tools (Q7) and the Seven Management Tools (M7), there is the QII quality technique.
Quality engineering QII
The statistical methods of quality management (QII) are quality techniques which, in addition to the basic statistical methods, analyze and evaluate measurement results, recognize cause- and -effect relationships and thus derive measures to improve processes and increase product reliability. With these techniques, the user is able to select and apply those suitable for quality optimization from a wide range of methods of statistical test planning.
History of statistical quality assurance
Statistics are the basis of today's quality methodical thinking and acting. It was in particular the First World War , and later the Second World War , that led to the use of scientifically based statistical methods in the context of quality assurance.
In Germany there were attempts to establish statistical methods in German industry as early as the beginning of the 20th century. Among other things, the work "Applications of mathematical statistics on problems in mass production" appeared in 1927 , although it did not attract much attention in industry. In addition, it was the head of the research institute of the Rheinische Stahlwerke in Düsseldorf, Dr. Karl Daeves, who was a pioneer in the use of statistical methods in industry. As early as 1922, after experiments on the frequency distribution in iron casting, he published a work on the "large number research" method . Further publications followed in 1948. As a result of the impressive results, a technical statistics department was created in the "Association of German Ironworkers" (VDEh).
In the USA, Walter Shewart, a physicist from the Bell Telephone Company, tried to successfully establish statistical methods in US industry. His basic work, Economic Control of Quality of Manufactured Product, was published in 1931, but his findings date back to 1924. The US industry was also not very fond of statistics, but the military procurement offices of the US Army were convinced of Shewart's findings. Shewart graphically entered the mean values and ranges of samples from an ongoing production process in chronological order on a form. That was the beginning of his "Control Chart" (in German " Quality Control Chart "). With the outbreak of World War II, the armaments industry was forced to introduce the quality control card. The armaments industry, in turn, demanded the use of the quality control card from the suppliers, which led to its spreading in American industry. The reason for the success of the quality control card, in addition to its widespread use, was primarily that with this statistical method the trend towards the occurrence of an error in an ongoing production process can be recognized, which allows timely countermeasures in terms of quality assurance.
Methods of statistical quality engineering QII
The statistical methods of quality management listed below do not claim to be exhaustive, but are the most frequently used methods.
- Quality planning: Quality Function Deployment ( QFD )
- Product realization: Statistical supplier evaluation in the sense of an incoming or outgoing goods inspection according to DIN ISO 2859 and 3951, process control with quality control cards
- Quality evaluation: machine and process capability study
- Quality improvement: Failure mode and effects analysis ( FMEA ), statistical test planning ( Design of Experiments )
Individual evidence
- ↑ Digitized at Googlebooks
- ↑ A. Schulze, E. Dietrich: Statistical procedures for machine and process qualification. Carl Hanser, Munich 2008.
- ↑ Linß, G. (2006). Statistics training in quality management. Munich [including: Fachbuchverl. Leipzig im Carl Hanser Verl.], Page 4
- ↑ Graebig, K. (2006). German Society for Quality, DGQ volume "Collection of formulas for the statistical methods of quality management". Berlin: Beuth.