Statistical process control (SPC), MSA and capability 1

To stay in compliance and achieve a competitive advantage, many companies are forced to change their approach in regards of process monitoring and control. This course will enable you to use process data for statistical analysis and gaining control by detecting and acting on process variation and drift.

Course description

This is an introductory course and the first of three within the topic of process monitoring. In this module, you will learn the classical approach to statistical process control with focus on measurement system analysis, control charts, and process capability indices. The classical example of these tools can only be used for normal distributed processes in statistical control which rarely exists outside of textbooks. Therefore, you will be introduced to practical applied statistical tools, such as fitting with a smooth curve, and using pre-summarize control charts, which you will be able to use in your daily work.

Target group

This course is relevant if you are working with qualification of measurements and production processes, process performance, production trending, and batch release. Or if you wish to learn the statistical concepts behind measurement system analysis, control charts and process capability indices.

Your benefits

After participating in this course, you will be able to:

  • Evaluate measurement uncertainty relative to the tolerance
  • Evaluate sampling uncertainty
  • Evaluate if a normal distributed process is predictable and capable
  • Understand the “voice of the process” and the different types of variations you might experience in your process
  • Use practical applied statistical tools

This course incorporates theory with practical exercises and active participation with the intent of providing you with a basic understanding of textbook data driven process performance and capability analysis.

 Content

  • Measurement system analysis (MSA) using precision tolerance ratio
  • Control charts on normal distributed data
  • Capability for normal distributed data

Advanced courses

This module only covers how to use the mentioned practical tools and not why you should use them. If you wish to understand why these practical tools works and how you can justify their application, then we strongly recommend you to participate in the more advanced modules. These advanced courses will also provide you with more applied statistical tools needed when working with data heavy tasks and projects.

If you want to devote more focus on the development of performance and processes, you can get inspiration from other courses such as Data-driven root cause analysis and Design of Experiments (DoE) 1.

Learning Method

Classroom training with exercises in the statistical software JMP® from SAS.

Practicalities

Venue: NNE's headquarters, Nybrovej 80, 2820 Gentofte, Denmark

Price: DKK 5,000 + VAT (includes course materials, refreshments and lunch)

Language of instruction: The course will be held in English unless all participants speak and understand Danish

Duration: 1 day
08.30-16.30

Course dates in 2018

  • February 28
  • May 16
  • September 5
  • November 14

Sign up for the course