QA & QE Training
All about Quality Assurance & Quality Engineering
1. Statistical Process Control (SPC) Training (Advanced)
Statistical concepts, Normal, Binomial and Poisson distributions and their applications. Acceptance sampling as a method of detection, Process control as a method of prevention. Control charts (C, U, X-bar and R, Moving range and moving average, CUSUM and trend charts).
2. Design of Experiment (DOE) Training
Statistical concepts, attributes data, variable data, one factor, two and multiple factors experiments, data transformation, interactions, linear graphs, process paramenter optimization, central composite design, and RSM.
3. FMEA (Failure Mode and Effects Analysis) Training
What is failure mode & effects analysis, Categories of FMEA: Design FMEA, Process of FMEA Elements of FMEA: Failure Mode Analysis, Failure Effect Analysis, Failure Criticality Analysis: The main steps in a FMEA: identify, list all possible system components and their modes, determine the effect, rate the probability of occurrence, calculate the Risk Priority Number (RPN), identify the corrective actions, Responsibility for preparation of the FMEA: Analysis of failure data, Applications of FMEA, FMEA Implementation : Do & Don’t.
4. QFD (Quality Function Deployment) Training
Need for QFD, QFD benefits, QFD methodology, Four Phases of QFD: Product Planning (Phase I), Part Deployment (Phase II), Process Planning (Phase III), Product Planning (Phase IV), Toyota Rust Case Study, Managing the QFD Process, Planning and Organization QFD Projects, QFD in Product Development, Workshops/Forms.
5. Gage R and R (Gage Repeatability & Responsibility) Training
Data Sheet, d2 values for the distribution of the average range, Gage R and R Average and Range Method, Gage Study (Range Method), Gage Study (Range Method), Gage Repeatability and Reproducibility Data Sheet, Gage Repeatability and Responsibility Report, Confidence Interval for the Average and Range Gage Study, Estimate of Variance Components, 5.15 Sigma Spread, Variance Component CL with o x p Significant, Variance Component CL with o x p Insignicant, Analysis of Variance (ANOVA), Gage R and R ANOVA Method, Attribute Gage Study, Short Method.
6. Basic Statistical Tools Training
Introduction to elementary statistics and statistical distributions Complete coverage on acceptance sampling by attributes (Mil Std 105) Introduction to acceptance sampling by variables (Mil Std 414) Introduction to Control Charts (C, U, X-bar and R charts)