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Statistical Process Control (SPC)

Statistical Process Control (SPC)

Headshot photo of Predictum consultant, Nick Burn.

Nick, Burn, Course Author

Principal Statistician at Predictum Inc.

Duration
1 day, delivered as 2 half-day sessions
Delivery
On-premises or virtual
Pricing
Available on request

About This Course

Manufacturing processes are continually subjected to both common and special cause sources of variation. Understanding these sources of variation, striving to eliminate special cause sources, and continuous monitoring of common cause sources helps drive efforts for continuous improvement to achieve better product and process results.

The monitoring of the statistical behaviour of stable manufacturing processes to detect signal changes in the process is important to ensure the consistency and capability of outputs for the customer.

Statistical Process Control (SPC) provides participants with the basic tools for implementing statistical process control charting techniques on the manufacturing floor. A working knowledge of basic statistics and of SAS JMP statistical software is assumed.

  1. SPC Concepts 
         1.1 Introduction 
         1.2 Control Chart Concepts 
         1.3 Statistical Concepts 
         1.4 Rational Subgroups 
         1.5 General SPC Process
  2. Variables Control Charts 
         2.1 X-bar/Range 
         2.2 X-bar/Standard Deviation 
         2.3 Individual/Moving Range 
         2.4 Considerations
  3. Attributes Control Charts 
         3.1 Attributes versus Variables 
         3.2 p and np Charts for Nonconforming Units 
         3.3 c and u Charts for Nonconformities
  4. Control Chart Rules 
         4.1 Out-of-control Signals 
         4.2 Trends 
         4.3 Control Chart Zones 
         4.4 Warnings 
         4.5 Out-of-control Action Plans
  5. Process Capability
         5.1 Introduction
         5.2 Process Capability Indices
        
    5.3 Estimating the Process Mean and Standard Deviation 
         5.4 Comparing the Indices

Optional Add-ons:

  • Laney p’ and c’ Charts Average Run Lengths,
  • Average Run Lengths, CUSUM and EWMA Charts
  • Non-normal Probability Limits
  • Customization with client data

Instructors

Headshot photo of Predictum consultant, Nick Burn.
Principal Statistician

Nick Burn

Nick specializes in statistical analysis, measurement system assessment, statistical process control, and design of experiments. He has extensive experience in the design, development, and delivery of courses in statistics serving both industry and academia.

Nick is a Principal Statistician at Predictum. He specializes in statistical analysis, measurement system assessment, statistical process control, and design of experiments. He has extensive experience in the design, development, and delivery of courses in statistics serving both industry and academia.
Nick worked at Nortel (14 years) in various manufacturing operations of high-tech components, as an independent consultant (5 years) providing training to automotive and high-tech companies, and at Abbott Laboratories (18 years) as a quality engineer supporting manufacturing and as a principal statistician supporting clinical studies in R&D. Nick was presented with an Abbott Chairman’s Award in 2007 as a team member for the successful FDA submission of waived status for a flagship product.

Nick is a part-time professor in the Department of Chemical and Biological Engineering at the University of Ottawa where he teaches undergraduate and graduate courses in the design of experiments, statistical process control, and statistical analysis of clinical study data. Nick has been recognized with several commendation letters from the Dean of Engineering for the high-quality teaching he has provided to his students.

Nick holds a B.A.Sc. in Chemical Engineering from the University of Ottawa, an M.Eng. in Chemical Engineering from McMaster University, and an M.Sc. in Mathematics Specialization in Biostatistics from the University of Ottawa.

“I really liked how organized the course was. I learned a lot about DOE which is very important in the field I want to work in.” Student, uOttawa.

“Nick Burn’s expertise in statistics has been invaluable to our team at Redlen. His deep understanding of statistical concepts, coupled with years of practical application, has greatly benefited everyone involved.” S.R., Redlen Technologies.

Who Should Attend

Engineers, scientists and technicians responsible for product and process development

Duration

1 day, delivered as 2 half-day session

Delivery Methods

On premises or virtual

Prerequisites

Familiarity with computers and spreadsheet software, such as Microsoft Excel.

JMP is required if you want to actively participate in the course. If you do not have JMP you can get a free trial version to install on your work or personal computer.

Pricing

Individual and group pricing available on request

Contact Predictum Training


Angela Mingo
amingo@predictum.com

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Statistical Process Control (SPC)


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