SPC Workbook v3.0

GOALS & OBJECTIVES
After this course, you will know how to: • Classify data • Identify common and special causes of variability • Setup and interpret control charts • Conduct a process capability and performance analysis • Use statistics to evaluate manufacturing processes, measurement systems, and suppliers
• Improving Quality will cost more money
• People will always make mistakes • Our business is different. SPC does not apply.
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Introduction and Overview
WHY IS IT THAT PRODUCTIVITY INCREASES AS QUALITY IMPROVES?
Productivity
Quality
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Introduction and Overview
15-40% Of Total Productive Capacity is Made up of Mistakes & Errors
Team Exercise
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Form teams
Identify top three expectations Name your team Introduce team and report expectations
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Introduction and Overview
EXPECTATIONS OF THE PARTICIPANTS
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Introduction and Overview
BRIEF HISTORY OF SPC
In the early 1920’s, Dr. Walter A. Shewhart, of Bell Laboratories, formulated his theory of process variation as follows: while every process displays variation, some processes display controlled variation, while others display uncontrolled variation. If a process displays only controlled variation, then its performance will be predictable, within limits. If the variability is uncontrolled, then we will see surplus variability beyond those limits, or unexpected variability within the limits. • In 1924, Dr. Shewhart developed the first known control chart • In the late 1930s W. Edwards Deming worked with Shewhart to bring control charts to the U.S. Department of Agriculture • Following WWII, Deming became a consultant for Japanese Industries, and used control charts and other tools to help them rebuild their industries • Today, almost every company uses statistical methods and SPC in one form or another. Most consider SPC critical in maintaining their competitive advantage
There is a general belief that:
• Quality and production are incompatible • If we push quality, we fall behind in production • If we push production, then quality will suffer
CONTENTS
Introduction and Overview…………………………….. 1 Understanding Variability………………………………. 2 Subgrouping and Data Collection…….……………….. 3 Control Charts………………………………………….. 4 Average and Range Charts……………………………..5 Individual and Moving Range Charts ………………….6 Process Capability and Performance Analysis……... 7 Proportion Charts………………………………………. 8 Analysis of Means (ANOM)…………………………... 9 Measurement Systems Analysis.……………….…….. 10
DEFINITIONS
A process is identified by a series of steps that converts inputs to outputs. Consistency is evaluated using data and statistical tools. Only when measures show consistent behavior can performance be described. Quality can be described using several dimensions. -
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Customer returns Scrap and reworking products Unattainable schedules Chronic overtime
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Introduction and Overview
THE DEMING CHAIN REACTION
Costs decrease because of less rework, fewer mistakes, fewer delays, snags, better use of machine time & materials
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Introduction and Overview
TRADITIONAL BELIEFS
SPC has been around since the 1920s. Why is a quality improvement tool like SPC not in wide use throughout the Coca-Cola System?
• Ask Questions • Participate • Be a teacher • Share Experiences • Work hard • Work as a Team • Have fun
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Hale Waihona Puke Introduction and Overview
WARNING!!!
Control charts and other quality improvement methods introduced in this training are just tools. They do not fix or solve problems. They only indicate whether or not a problem exist.
Based on this definition, how would you define Quality Improvement?
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Introduction and Overview
TYPES OF DATA
The first and most important step in using data is to figure out what data are needed. This is not a statistical question. The next step is to determine what kind of data you have chosen. The two primary classifications of data are outlined on the following pages.
Statistical Process Control
From Concept to Application
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Quality Systems Department Maj.
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Attributes
Variables
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Introduction and Overview
DATA TYPE EXERCISE
Determine the type of data in each situation listed. Individual Observation • A shipment is late or on time • The number of errors on an invoice • The dollar amount by which a month’s expenditures deviated from the budget • Fill weight of a 330ml can • The removal torque of a closure • A bottle has a label or does not. • Temperature of a filled product. • Whether or not fill temperature meets requirements. • The oBrix of Coca-Cola Classic Data Type