Evaluating the Quality of Data

All data are subject to various sources of measurement variation. The first step in “Measurement Systems Optimization” and “ Process Capability Evaluation” is identifying and knowing which sources of measurement variation to reduce. In this session learn how to perform “Measurement Systems Analysis” (MSA). Through MSA the sources of measurement variation may be quantified and prioritized for continuous improvement.

• Statistical Process Control & Six Sigma Capability/Performance

All processes are subject to static and dynamic disturbances that shift the process mean from time to time. Such sources of variation are not predictable however they are known to exist. Using statistical process control methods learn how to quantify such disturbances and create specifications that are designed to meet Six Sigma capability and performance.

• Process Management By Data

The quality of a product is largely determined by a number of processes. How those processes are managed determines the quality of the product. In this session learn how to interpret process capability and performance indicators, apply variation reduction algorithms, and determine the effective cost of production. This framework creates the foundation for an effective process management system that drives the continuous improvement of the business process.

• Multi-Vari Analysis & Graphical Techniques for Continuous Improvement

The variation in the product from a process is the sum of the many sources of variation present in the process. In this session learn how to partition the variation in the output as a function of the variation present in the process. This is a critical step in the identification of special cause variation. Once special cause variation has been identified it can be reduced or eliminated resulting in superior process performance and product quality.