Statistical process control (SPC) is a method of quality control which uses statistical methods. SPC is applied in order to monitor and control a process. Monitoring and controlling the process ensures that it operates at its full potential. At its full potential, the process can make as much conforming product as possible with a minimum (if not an elimination) of waste (rework or scrap).
SPC can be applied to any process where the "conforming product" (product meeting specifications) output can be measured. Key tools used in SPC include control charts; a focus on continuous improvement; and the design of experiments. An example of a process where SPC is applied is manufacturing lines.
The overall objective of this course is to teach you how to effectively apply SPC techniques and calculations in the MEASURE, ANALYZE, and CONTROL phases of a process improvement project.
After completing this course, you should be able to:
Following are the roles for whom training is suitable.
A measurement systems analysis (MSA) is a specially designed experiment that seeks to identify the components of variation in the measurement.
Just as processes that produce a product may vary, the process of obtaining measurements and data may have variation and produce defects. A measurement systems analysis evaluates the test method, measuring instruments, and the entire process of obtaining measurements to ensure the integrity of data used for analysis (usually quality analysis) and to understand the implications of measurement error for decisions made about a product or process. MSA is an important element of Six Sigma methodology and of other quality management systems.
MSA analyzes the collection of equipment, operations, procedures, software and personnel that affects the assignment of a number to a measurement characteristic. A measurement systems analysis considers the following:
Common tools and techniques of measurement systems analysis include: calibration studies, fixed effect ANOVA, components of variance, attribute gage study, gage R&R, ANOVA gage R&R, destructive testing analysis and others. The tool selected is usually determined by characteristics of the measurement system itself.
This interactive and practical course will provide delegates with a basic knowledge of the principles of MSA and the methodologies for performance of measurement systems studies with respect to bias, linearity and stability. Our course is highly practical and avoids detailed knowledge or discussion of statistics.
Key Skills / Learning Objectives
Through the combination of interactive tutorials and workshops, our course will enable the delegates to:
Practical workshops are designed to reinforce the discussions and topics. This style of delivery makes the course both memorable and enjoyable for participants, ensuring long-term learning.
Following are the roles for whom training is suitable.
