Statistical Process Control Training:

Statistical Process Control Training Course (Online, Onsite, and Classroom Live!)

This is a comprehensive and intensive 3-day Statistical Process Control Training course that presents the essential elements of an effective Statistical Process Control program. The Statistical Process Control Training course focuses on understanding the basics, identifying objectives, SPC implementation, and realizing the benefits this magnificent process management system offers. The Statistical Process Control course develops and presents a results-oriented roadmap for implementing an effective Statistical Process Control program.

Tailored Classes

Onsite classes can also be tailored to meet your needs. You might shorten a 5-day class into a 3-day class, or combine portions of several related courses into a single course, or have the instructor vary the emphasis of topics depending on your staff and site’s requirements.

What’s Included?

• 3 days of Statistical Process Control Training with an expert instructor
• Statistical Process Control Training Electronic Course Guide
• Certificate of Completion
• 100% Satisfaction Guarantee

Resources:

Related Courses

Objectives:

After completing this Statistical Process Control course, attendees will be able to:

• Develop an effective Statistical Process Control system.
• Objectively identify Statistical Process Control opportunities.
• Work together to implement and improve your Statistical Process Control program.

Course Syllabus:

Day 1:  Course Overview and Introductory Concepts

Course Overview

• Course outline
• Introductions

The Industrial Revolution

• Mass production
• Division of labor
• Taylorism
• Typical engineering drawing and specification practices
• Engineering tolerances historical contexts
• Typical engineering drawing tolerance responsibilities

Manufacturing Processes

• Process capabilities
• Process capability versus engineering tolerances

Deterministic versus Probabilistic Thinking

• Typical test and inspection approaches
• Typical build-and-inspect approaches
• The psychology of inspection
• Product quality responsibilities
• The sampling approach and its pitfalls
• Detection versus prevention management philosophies
• Driving blindfolded

Introduction to Statistics and Probability

• The nature of variability
• Shewhart’s formative work
• Frequency distributions
• Histograms
• The normal curve, means, and standard deviations
• Normal curve mathematics
• Averages of averages and the central limit theorem

Statistical Process Control

• SPC Overview
• SPC basic concepts
• SPC control in World War II
• The US rejection of SPC after World II
• Japan’s SPC acceptance after World War II
• SPC success stories
• Placing product quality responsibility in the operator’s hands

Statistical Process Control Concepts

• Inspection shortfalls
• Attributes versus variables data
• Placing quality responsibility in the hands of the operator
• x_bar:r charts
• SPC capabilities
• Class exercise

Day 2:  SPC Implementation

Training

• Management training
• Supervisor training
• Operator training

Selecting Processes for SPC application

• Variables data opportunities
• Optimizing early successes
• Defining the process
• Flowcharting
• Assessing existing test and inspection points
• Selecting critical characteristics for SPC application
• Identifying critical dimensions
• Identifying sources of variability
• Ishikawa charts
• Minimizing variability
• Case study
• Class exercises

Gathering SPC Preliminary Data

• Collecting data for establishing upper and lower control limits
• Calculating upper and lower control limits
• Defining subgroups and calculating averages
• Class exercise

Preparing, Maintaining and Using Charts

• Xbar charts
• Typical x_bar:r charts required information
• Collecting individual data points
• Calculating average values
• Finding the range
• Defining nominal and upper and lower control limits
• Plotting averages, ranges, and the grand average
• Finding the standard deviation
• Using Excel to simplify x_bar:r calculations
• Finding the average range
• Finding upper and lower control limits for the range
• Simplified approaches for determining upper and lower control limits
• Class exercises

p-Charts

• Attributes data applicability
• Converting attributes data to variables data
• The nature of p
• Finding the average p
• Finding p upper and lower control limits
• Using the average p and upper and lower control limits to create a p chart
• Class exercises

Day 3:  Putting SPC To Work For Your Organization

Using SPC Charts

• Plotting process data on SPC charts
• Noting process changes
• Identifying trends
• Shifting responsibility to the operator
• Class exercise

SPC Trend Analysis

• No trend
• Subgroup averages trending upward or downward
• Multiple points above or below the average
• Cyclical patterns
• Range changes
• Calling for help when trends are recognized
• Class exercise

SPC Implementation Challenges

• Resistance to change
• Inspector job security
• Seeking input from affected personnel
• Selecting initial SPC-implementation points
• Maintaining momentum
• Publicizing success

Course Review and Wrap-Up

• Wrap-up.
• A suggested Statistical Process Control implementation roadmap.
• Course critique.

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