Lecture 7 Quality Control Process Charts Learning Objectives

Lecture 7 Quality Control Process Charts

Learning Objectives In this lecture, you learn: § How to construct various control charts § Which control charts to use for different types of data § How to determine when a process is out of control

Statistical Control Charts Counting Data p chart c chart Measuring Data Mean and Range charts Individual and Moving Range charts

Theory of Control Charts § A process is a repeatable series of steps leading to a specific goal (A store opening) § Control Charts are used to monitor variation in a measured value from a process (How long it takes to open the store)

Total Process Variation Total Process Common Cause Special Cause = + Variation is often due to differences in: § People § Machines § Materials § Methods § Measurement § Environment

Common Cause Variation Total Process Common Cause Special Cause = + Variation Common cause variation § naturally occurring and expected § the result of normal variation in materials, tools, machines, operators, and the environment

Special Cause Variation Total Process Common Cause Special Cause = + Variation Special cause variation § abnormal or unexpected variation § has an assignable cause § variation beyond what is considered inherent to the process

Control Limits Forming the Upper control limit (UCL) and the Lower control limit (LCL): Mega. Stat will do this. UCL = Process Mean + 3 Standard Deviations LCL = Process Mean – 3 Standard Deviations UCL +3σ Process Mean - 3σ LCL time

Control Chart Basics First Rule of Special Cause Variation: Range of unexpected variability UCL Common Cause Variation: range of expected variability +3σ Process Mean - 3σ LCL time UCL = Process Mean + 3 Standard Deviations LCL = Process Mean – 3 Standard Deviations

Process Variability First Rule of Special Cause of Variation: A measurement this far from the process mean is very unlikely if only expected variation is present UCL ± 3σ → 99. 7% of process values should be in this range Process Mean LCL time UCL = Process Mean + 3 Standard Deviations LCL = Process Mean – 3 Standard Deviations

Process Not in Control Three Rules § One or more points outside control limits § 8 or more points in a row on one side of the center line § 8 or more points moving in the same direction

Examples of Process Not in Control § One or more points outside control limits § Eight or more points in a row on one side of the center line UCL Process Mean LCL § Eight or more points moving in the same direction. UCL Process Mean LCL

Out-of-control Processes § When the control chart indicates an out-ofcontrol condition (a point outside the control limits or exhibiting trend, for example) § The special causes of variation must be identified § If detrimental to the quality, special causes of variation must be removed § If increases quality, special causes must be incorporated into the process design

Problem Recognition Statistical Control Charts p chart 1. Counting type data. 2. Proportions = count/sample size are available.

Problem Recognition Statistical Control Charts C chart 1. Counting data 2. Only counts are available (no sample size).

Problem Recognition Statistical Control Charts Mean and Range charts 1. Measurement data (time, lengths, areas, volumes, etc. ) 2. You have multiple measurements period.

Problem Recognition Statistical Control Charts Individual and Moving Range charts 1. Measurement data (time, lengths, areas, volumes, etc. ). 2. You have only 1 measurement per time period.

Lecture 7 Summary § Discussed theory of control charts § Discussed the rules for when a chart is out of control § Discussed which types of control charts to use depending upon what the data looks like