Certificate in Statistical Quality Engineering: Advanced Quality Concepts
-- ViewingNowThe Certificate in Statistical Quality Engineering: Advanced Quality Concepts is a comprehensive course that equips learners with essential skills for career advancement in quality engineering. This program delves into advanced quality concepts, emphasizing statistical methods and techniques for process improvement.
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⢠Statistical Process Control (SPC): Monitoring, controlling, and improving processes using statistical methods. Understanding and interpreting control charts, capability analyses, and process capability indices.
⢠Measurement Systems Analysis (MSA): Examining the accuracy, precision, and stability of measurement systems. Identifying and quantifying measurement errors, biases, and variation sources. Implementing strategies to improve measurement systems.
⢠Hypothesis Testing and Experimental Design: Applying statistical inference for decision making. Designing experiments, planning for data collection, and analyzing results to establish process improvements.
⢠Design of Experiments (DoE): Utilizing designed experiments to evaluate multiple factors simultaneously. Identifying optimal settings and interaction effects between factors.
⢠Multivariate Analysis: Examining the relationships between multiple variables and understanding the impact on process outcomes. Applying principal component analysis, factor analysis, and discriminant analysis.
⢠Reliability Engineering: Predicting and improving the reliability of products and systems using statistical methods. Implementing reliability testing, failures analysis, and maintenance strategies.
⢠Acceptance Sampling: Evaluating product quality based on random samples. Implementing acceptance sampling plans, establishing quality standards, and making informed process decisions.
⢠Quality Tools: Utilizing statistical and graphical tools to analyze and visualize data. Implementing cause-and-effect diagrams, Pareto charts, scatter plots, control charts, and histograms.
⢠Six Sigma Methodology: Applying Six Sigma tools and techniques to reduce variation, improve quality, and increase process efficiency. DMAIC (Define, Measure, Analyze, Improve, Control) framework and project management.
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