course content
The first part: Brief introduction of lean six-horse management.
Lecture 1: History of Quality Management Development
1, quality inspection stage
2. Statistical quality control stage
3, total quality management stage
4, the new development of total quality management
Lecture 2: the origin and basic concepts of lean six sigma
1, the origin of lean six horses
The emergence of lean six sigma
Popularization of lean six-fit horse
New development of lean six-fitness horse
Integration of lean six-horse management with existing management system
2. The basic concept of lean six-horse.
Statistical significance of lean six-fitness horse
The meaning of lean six sigma management
Strategic significance of lean six-horse management
Lecture 3: lean six-horse management organization and method
1, leader
2. Organizational structure of six-horse management
3. Construction of six suitable horse teams
4. Six Sigma Management Methodology
5. Improved Six Sigma -DMAIC model
Lecture 4: Process Analysis and Project Selection
1, process identification
Program definition
Determine the core process
Macroscopic process analysis
2. The voice of customers
Customers and customer requirements
customer satisfaction
Collect customer information
Analyze customer information
Changes in key customer needs
3. Operating results
Process performance measurement index
Horizontal contrast
Financial income
Lecture 5: Lean Six Sigma Project Management
1, Six Sigma Project Selection
6. Principles for selecting suitable horse events.
Six sigma project selection process
Problems in Six Sigma Project Selection
2. Six Sigma Project Management
Goals and plans of six suitable horse projects
Six sigma team building
Six sigma team development stage
Motivation and performance of the six-horse team
Six sigma project control
Progress of Six Sigma Project
3. Six planning and management tools for Hummer projects
Six smart team tools
Six Management and Planning Tools for Suitable Horse Projects
Part II: Definition-Lean Six Sigma Definition Stage
Sixth lecture: the process of confirming and determining customer demand
1. Confirm customer requirements
2.SIPOC analysis and charts
3. Determination of key process variables
Lecture 7: Making and Perfecting the Project Plan
1, operating conditions
2. Statement of problems/opportunities and objectives
3. Project scope, limitations and assumptions
4. Mission and task of the team
5. Expected project plan
6. Identify key stakeholders
Lecture 8: Determining Project Metrics
1, establish measurable indicators.
2. The current baseline horse fitness level in the measurement process.
3. Analyze and determine the inferior cost.
Lecture 9: Types and Composition of Enterprise Costs —— Quality Cost Analysis
1, mass loss function
2, the relationship between quality cost and profit
3. Prevention costs
4. Appraisal fee
5. Defect cost
6. The corresponding relationship between capability value and quality cost
The third part: measurement-lean six sigma measurement stage
Lecture 10: process analysis and documentation
1, flow chart
2. Causality diagram and causality matrix
3. Other process analysis tools and documents
Lecture 11: Fundamentals of Probability and Mathematical Statistics
1, basic knowledge of probability theory
2. Random variables and their distribution
3. Mathematical expectation, mean and variance
4, commonly used discrete distribution
5, commonly used continuous delivery
6. Central limit theorem
7. Statistics and sampling distribution
Lecture 12: data collection and arrangement
1, data type and measurement scale
2. Methods of data collection
3. Sampling method
4. Descriptive statistical methods
5. Icon method of data
Lecture 13: Measurement System Analysis (MSA)
1, basic concept
2. Measure the resolution of the system
3. Measure the deviation, linearity and stability of the system.
4. Repeatability and reproducibility of measurement system
5. Measurement system analysis of destructive test.
6, discontinuous data measurement system analysis
7. Calibration and verification of measuring instruments
Lecture 14: process capability analysis
1, process capability indices Cp and Cpk.
2. Process capability indices Cpm and Cpmk
3. Process performance indexes pp and ppk
4. The relationship between process capability and defect rate
5, long-term ability and short-term ability
6. Transformation of non-normal data
7. Process capability estimation of discontinuous data.
Lecture 15: Potential Failure Mode and Impact Analysis (FMEA)
Definition and application of 1 and FMEA
2. The background and types of 2.FMEA.
3. Risk priority number
4. Eight steps of 4.FMEA production
5. Example 3: FMEA case making exercise and explanation
Lecture 16: Instruction of MINITAB, a special software for Six Sigma.
1, functions, windows and basic operations of MINITAB
2. Introduction of 2.MINITAB statistical analysis tools
3.MINITAB practical operation drill
The fourth part: analysis-lean six sigma analysis stage
Lecture 17: exploratory data analysis and process analysis
1, exploratory data analysis
2. Process analysis
3. Regression analysis and correlation analysis
4. Point estimation and interval estimation
Lecture 18: Hypothesis Test
1, the basic concept of hypothesis testing
2. Hypothesis test of mean, variance and ratio
3. Paired data test
4, goodness of fit test
5, continuous data hypothesis testing
6. Hypothesis test of discrete data
Lecture 19: analysis of variance
1, one-way analysis of variance
2. Two-factor analysis of variance
Lecture 20: contingency table
1, the concept of independence test
2, contingency table independence test method
Lecture 2 1: nonparametric test
1, symbol test
2, the median sign test method
3. Mann-Whitney-Wilcock test.
4.Wilcoxon signed rank test
5. Kruskal-Wallis test
Example: case analysis and practice
Part V: Improvement-Six Sigma improvement stage.
Lecture 22: Fundamentals of Experimental Design
1, a basic term in experimental design
2. Basic principles of experimental design
3. Necessity of experimental design
4. Types of experimental design
5. Plan and arrangement of experimental design
6. Basic steps of experimental design
Lecture 23: Design and Analysis of Single Factor and Total Factor Experiments
1, single factor experimental design and analysis
One-way classification design
Polynomial regression
2. Total factor design and analysis
Overview of two-level total factor test
All-factor design plan
Total factor design analysis
All-factor design example
3, part of the implementation factor test
Part of the realization is due to the introduction of the experiment.
Part of the implementation is due to the test plan.
Examples of testing and analysis of some implementation factors
Plackett-Burman design-alternative screening factor design
Analysis of three-level partial implementation factor test
Lecture 24: Design and Analysis of Response Surface
Brief introduction of response surface design.
2. Response surface design scheme
3. Analysis and examples of response surface design.
Lecture 25: Robust Parameter Design and Hybrid Design
1, robust parameter design
Robust parameter design model
Robust parameter design scheme
Example analysis of robust parameter design
2. Mixed design
Introduction to mixed design
Mixed test plan
Mixed experimental analysis
Part VI: Control —— Six stages of horse control.
Lecture 26: Overview of Control Phase
1, document improvement process
2. Establish a process management plan
3. Implement continuous process measurement and control.
4. General control chart
Lecture 27: SPC statistical process control theory
1, control introduction
2, statistical thought and control chart
3. Type and selection of control chart
4. Preparation before using the control chart
Lecture 28: Statistical Process Control of Quantitative Data and Statistical Process Control of Counting Data
1, measurement data SPC
Types and uses of survey data control charts
Making and Application of Control Chart of Surveying Data
Process capability analysis of measurement data control chart
Four types of measurement data control charts
Example: Practice and explanation of making measurement control chart
2. Counting data SPC
Types and uses of counting data control charts
Making and Application of Counting Data Control Chart
Process capability analysis of counting data control chart
Four kinds of counting data control charts
Example: Practice and explanation of making counting control chart
Lecture 29: Share the Successful Cases of Lean Six Sigma
1, a case of an enterprise in Lean Six Sigma
2. A case introduction of an enterprise promoting lean six sigma project as a whole.
Part VII: Course review, examination and free communication.
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