This Course is available in the following format:
Industrial Statistics Training Course Description
This Industrial Statistics Training course brings together important concepts that allow engineering and operations organizations to understand industrial statistics concepts. The focus is on applying these concepts to optimize processes, implement statistical process control, and use statistical concepts in assessing product and process performance. The Industrial Statistics Training course utilizes real-life case studies to help you understand these technologies. At the end of the Industrial Statistics Training course, you will have an understanding of the key industrial statistics tools, technologies, terminology, and capabilities.
• If you are familiar with some aspects of this Industrial Statistics Training course, we can omit or shorten their discussion.
• We can adjust the emphasis placed on the various topics or build the Industrial Statistics Training course around the mix of technologies of interest to you (including technologies other than those included in this outline).
• If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policy-maker), and present the Industrial Statistics Training course in manner understandable to lay audiences.
Industrial Statistics Training – Related Courses:
Industrial Statistics Training – Objectives:
• Work together in an effective team environment to implement industrial statistical concepts.
• Use the technologies presented in this course to identify key product design and manufacturing process tolerances and control limits.
• Reduce or eliminate areas of specification non-compliance.
• Proactively design test and inspection approaches that are consistent with product and process capabilities.
Industrial Statistics Training – Course Content:
Basic Probability and Statistics
•Deterministic versus probabilistic thinking
•The normal curve: Its history and mathematics
•The nature of variability
•Means and standard deviations
•Using normal curves, means, and standard deviations to predict probabilities of occurrence
•Product and process design
•Identifying sources of variability
•Identifying potential key performance parameters
•The concept of a capable process
•Approaches for minimizing variability
Basic Statistics Test Approaches
•Analysis of variance (ANOVA)
•Fractional factorial experiments and Taguchi testing
Detection versus Prevention Process and Design Approaches
•Collecting and using nonconformance data
Test and Inspection
•The nature of inspection
•The fallacy of redundant inspection
•Statistical process control
•Statistical process control implementation
•Development, qualification, and acceptance testing
•Probabilities of passing receiving, in-process, and final acceptance testing
•Operating characteristic curves
•Product nonconformance considerations
•Improving processes with statistical tools
•Using Excel’s built in statistical analysis features