Statistical methods in material manufacturing and evaluatio

The implementation of statistical quality and process control methods in the manufacture and the evaluation of composite and noncomposite materials is presented. First, the evolution of modern statistical quality and process control techniques and philosophies is discussed. The use of statistical quality and process control methods in all material and nonmaterial industries is then presented in detail. Additionally, the applications of other types of process control technologies, such as artificial intelligence, both in conjunction with and in lieu of statistical and process control in material and nonmaterial manufacturing sectors is described. The use of statistical methods with nondestructive evaluation and characterization techniques, both for defect categorization and process control feedback, is also presented. Previous work in the study of the effects of environmental factors on composite part manufacture and for methodologies for the implementation of statistical process and quality control in material and nonmaterial manufacturing industries is discussed.;Experimental work was then performed to establish the use of statistical methods for the testing, evaluation, and analysis of external supplier composite and metal alloy material parts; material testing, comparison, evaluation and statistical analysis of both external supplier and composite part manufacturer composite material test result data; and the introduction of the use of risk analysis and variation reduction for the evaluation of an internal supplier composite part manufacturing process. Lastly, the application of this work to cyclic closed-loop statistical quality and process control on both an internal and an external supplier basis is discussed with respect to the highest impact on process improvement and cost reduction.;The results of this work show that statistical methods can be successfully applied to existing material manufacturing and evaluation processes for the improvement of quality and process control. It was also shown that statistical methods have many potential applications in the improvement of the robustness of composite and noncomposite material processes, and in destructive and nondestructive material evaluation.