QUALITY ENGINEERING (3 Credits)

Learning Outcomes :

On successful completion of this course, student will be able to: Explain quality management concepts (for example but not limited to ISO, TQM, MBQA, Six Sigma, and Quality Cost) and their relation to the application of AI in Production-Operation Management; Differentiate quality tools include various basic techniques for developing AI systems to identify trends, anomalies, and opportunities for process improvement in quality engineering; Use statistical quality control and machine learning techniques as well as the related software for data analysis;  Propose process improvement utilizing quality tools; Apply design of experiment for continuous improvement.

Topics :

Introduction to Quality, A System for Quality, AI Applications in Production-Operation Management, Planning for Quality, AI for Understanding Customer, Statistical Process Control, Control Chart, Process Capability Analysis, AI in Quality Assurance and Inspection, Quality in Procurement, Basic Experimental Design for Quality Improvement, Quality Improvement Project, Tutorial 1: Statistical Process Control, Tutorial 2: Control Chart, Tutorial 3: Process Capability Analysis, Tutorial 4: Quality in Procurement, Tutorial 5: Basic Experimental Design for Quality Improvement, Tutorial 6: Basic Experimental Design for Quality Improvement