Statistical Process Control

Seminar Content

Is your organization data rich and action poor? This seminar teaches participants how to analyze data in a way that clarifies those actions that need to be taken in order to reduce the variation in products and services. It addresses how to determine the “natural variation” of the process or product, how to chart the data to maintain control of the process, how to interpret the chart, and how to respond to the data in order to reduce the variation.

Objectives of this training are to:

• Learn how to create the right environment to make statistical process control (SPC) successful;
• Understand the types of variation in products and services and what actions are appropriate to minimize that variation;
• Learn specific techniques in analyzing data and taking actions that are indicated by the analysis:
• Strategies to eliminate special cause variation;
• Basic tools to minimize common cause variation;
• X-bar and R charts to evaluate variable data;
• P, np, c, and u charts to evaluate attribute data.
• Understand how to interpret what the charts are saying about the process;
• Learn how to calculate the financial impact of quality improvements.

The scope, length, and specific content of the class are always customized to meet the individual needs of the attendees and the organization. The standard agenda addresses:

• Implementing SPC in an Environment of Total Quality Management
• Long-term vs. short-term thinking
• Creating loyal customers vs. meeting specifications
• Systems focus vs. individual performance
• Creating a team environment vs. individual competition
• Eliminating fear vs. creating fear
• Continual improvement vs. “if it isn’t broken, don’t fix it”
• Understanding variation vs. reacting on single points
• Decisions based on data vs. gut-feel decisions
• Understanding Variation
• Special cause variation and actions to eliminate it
• Common cause variation and actions to minimize it
• Using Basic Quality Tools to Minimize Common Cause Variation
• Setting Up the Chart
• Establishing the right environment
• Defining the process
• Identifying characteristics to be controlled
• Defining the measurement system and understanding its variation
• Control Charting for Variable Data
• X-bar and R charts
• Individual and moving range charts
• Moving-average and moving-range charts
• Selecting the subgroup size
• Creating the chart
• Interpreting the chart
• Control Charting for Attribute Data
• p charts
• np charts
• c charts
• u charts

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