Quality Control And Design - Experimental Design Process
Published 3/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.88 GB | Duration: 2h 35m
Part 6 of 8 Course Series On Quality Control and Design[/center]
What you'll learn
Introduction- What is an Experiment, terms associated with Experimentation
Basic Principles of Experimental Design, Experimental Design Methods
Completely Randomized Experimental Design, Reference to Variations in Randomized Experimental Design
Factorial Experiments, Numerical Exercises
Factorial Experiment, Fractional Factorial Experiment
Requirements
none
Description
This eight-course series on Quality Control and Design is a valuable investment for anyone involved in manufacturing, product development, or quality assurance. This course appears to cover a comprehensive range of topics related to quality control and management, with a focus on statistical analysis and process improvement.Recommended Path:Introduction to Quality Control and DesignQuality Control and Design - Quality Management & TQMQuality Control and Design - Statistical Process ControlQuality Control and Design - Process capability & analysisQuality Control and Design - Acceptance samplingQuality Control and Design - Reliability DesignQuality Control and Design - Experimental designQuality Control and Design - Taguchi method and robust designThe course starts with a brief Introduction to quality control and design management, which is an essential foundation for understanding modern quality management systems. It then moves on to cover Quality Management & TQM, including topics such as quality planning, control, and improvement.The next course is dedicated to statistical process control, which is a critical tool for identifying and correcting quality issues in manufacturing processes. Students will learn how to use statistical process control charts and techniques to monitor and improve process performance.Process capability & analysis is the next course, which involves determining the inherent variation in a process and comparing it to the desired specifications. This analysis is essential for ensuring that a process is capable of meeting customer requirements.The next course covers acceptance sampling, which is a statistical technique used to determine whether a batch of products meets a particular quality standard. Students will learn how to design and implement acceptance sampling plans to ensure that products are of consistent quality.Reliability Design is the next topic, which is the process of designing products to meet or exceed customer reliability requirements. This includes topics such as stress testing, failure analysis, and design optimization.The next course covers quality by experimental design, which involves designing experiments to test the impact of different factors on product quality. This technique is useful for identifying the most significant factors affecting product quality and optimizing product design.Finally, the course ends with a section on the Taguchi method and robust design, which is a powerful technique for optimizing product design and minimizing the impact of variability in the manufacturing process.Overall, this course provides a comprehensive overview of quality control and management, with a particular emphasis on statistical analysis and process improvement. Graduates of this course will be well-equipped to implement effective quality control systems and improve product quality in a wide range of industries.
Overview
Section 1: Introduction
Lecture 1 Introduction- What is an Experiment, terms associated with Experimentation
Lecture 2 Introduction- What is an Experiment, terms associated with Experimentation pt2
Lecture 3 Basic Principles of Experimental Design, Experimental Design Methods
Lecture 4 Completely Randomized Experimental Design
Lecture 5 Completely Randomized Experimental Design Part 2
Lecture 6 Factorial Experiments, Numerical Exercises
Lecture 7 Factorial Experiments, Numerical Exercises Part 2
Lecture 8 Fractional Factorial Experiment
Supply Chain Managers. Working in Operations, Manufacturing or Service sectors, Production and Industry,Logistics, Purchasing, Customer Relationship Managers,Financial Controllers, Accountants, Business Analysts & Consultants,Small Business Owners & Operations Managers,Ambitious Self-Starters who want to have a Bigger Impact at work, Improve Things and Get Noticed
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