Course objectives:

• Understand the importance of process orientation
• Apply Six Sigma DMAIC (Define, Measure, Analyse, Improve, Control) methodology
• Experience the negative effects of variation, see ways to measure and reduce it
• Find out different types of process factors: dependent, independent, controlable or not
• Ask the right questions to get to the root cause of problems
• Identify potential problems before they actually take place
• Apply this methodology and tools to one's own process with an improvement project

1. Define

• What is important? What is the problem?
• Project Scheduling
• Project charter: Goals, objectives, scope, justification, project participants
• Current status: go to Gemba
• Problem definition: SMART
• The voice of the customer: translate it to process specs
• Process map and flow chart: SIPOC
• Process Value Stream Map with MS Excel.

2. Measure

• What to measure?: Voice of the customer, Voice of the process, Business results
• Process metrics: Throughput, Yield, WIP, DPU, DPMO
• Test/ inspection: Coverage and First Pass Yield
• Operator and machine cycle times, Takt time and Lead time
• Data collection and validation
• Timestamp collection
• Basic statistics with Excel Data Analysis and Minitab
• Run charts and histograms 
• Process capability: Cp, Cpk, sigma capability
• Attributes: Pareto
• Data stratification with Excel pivot tables 
• Measurement system analysis

3. Analyze

• What to improve? Analyze the current process Value Stream Map
• Process inputs and process internal metrics (X)
• Source of defects, delays, waiting queues
• Bottleneck and waste identification 
• Root cause: Cause and effect diagram
• IS - IS NOT methodology 
• Test of hypothesis for variables and attributes 
• Input variables (X) and output (Y): correlation and regression
• Analysis of variance (ANOVA)
• Sample size and confidence interval

4. Improve

• Process documentation: procedures and work instructions
• Prevention: Failure Mode and Effects Analysis (FMEA)
• Throughput, Work-In-Process and Lead Time 
• Bottlenecks due to capacity, yield loss or variation
• Process impact of variation
• Process simulation with Excel 
• Value Stream simulation
• 5S methodology
• Poka-Yokes (fail proof)
• Optimization with constraints: Theory Of Constraints
• Shared resource optimization: job scheduling
• Design of Experiments (DOE)
• DOE with Excel
• Response Surface Design of Experiments

5. Control

• Control plan design and implementation
• Statistical process control (SPC)
• Control charts for variables and attributes
• Western Electric rules: Interpretation
• Discrimination, repeatability, reproducibility
• Real-time operator feedback
• Out of control: Who does what?
• Corrective actions: 8 discipline (8D) methodology