Quality Control and Genetic Algorithms: Control, Algorithm, Null Hypothesis, Statistical Hypothesis Testing, Boolean Algebra (Logic), Mean, Standard Deviation, Programming

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. The combination of quality control and genetic algorithms led to novel solutions of complex quality control design and optimization problems. Quality control is a set of activities intended to ensure that quality requirements are actually being met. Quality is the degree to which a set of inherent characteristics fulfils a need or expectation that is stated, general implied or obligatory. Genetic algorithms are search algorithms, based on the mechanics of natural selection and natural genetics. Alternative quality control (QC) procedures can be applied on a process to test statistically the null hypothesis, that the process conforms to the quality requirements, therefore that the process is in control, against the alternative, that the process is out of control.