Chapter 35

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# Chapter 35 - PowerPoint PPT Presentation

Chapter 35. Statistical Process Control. Objectives. Define and describe the objectives of Statistical Process Control (SPC). Select and use control charts in various situations. Interpret control charts. Special versus Common Causes. Every process has variation.

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### Chapter 35

Statistical Process Control

Objectives
• Define and describe the objectives of Statistical Process Control (SPC).
• Select and use control charts in various situations.
• Interpret control charts.
Special versus Common Causes
• Every process has variation.
• The sources of process variation can be divided into two categories: special and common.
• Common causes (natural variation) are those inherent in the process and generally not controllable by process operators – example: Variation in raw material.
• Special causes include unusual events that the operator can adjust – example: tool wear, broken equipment.
• The principal purpose of control charts is to help the operator recognize the presence of special causes so that corrective action can be taken in a timely manner.
Selection of Variables
• When a control chart is to be used, a variable must be selected for monitoring.
• The variable is a leading indicator of special causes - one that detects special causes before others do.
• The selection of the variable(s) to be charted depends on experience and judgement.
Rational Sub grouping
• The method used to select samples for the control chart must be logical.
• For example, suppose a candy making process uses 40 pistons to deposit 40 gobs of chocolate on a moving sheet of waxed paper in a 5 x 8 array, as shown in fig 35.2, page 361.
• A good choice would be to pick upper left hand chocolate in 5 consecutive arrays as shown in fig 35.3 because they are all formed by the same piston.
• The choice of sample size depends on resources available – the larger the sample size, the more sensitive the chart.
Variables Chart
• The X bar – R chart is called a variables chart because the data results from measurements on a variable or continuous scale (R = range).
• The X bar – R chart is typically used when sample subgroup size is less than 10. See example 35.1 on page 363.
• The X bar – s chart is another variables chart. With this chart the sample standard deviation s is used to indicate dispersion.
• The standard deviation is a better measure of spread when the sample size is large. See example 35.2 on page 365.
• Control Limits: They are set at +- 3 σ. The upper control limit is designated UCL and lower control limit LCL.
Control Chart Selection
• Individual and Moving Range Chart: Sample size of one.
• For slow processes or destructive tests. Example 35.3, page 366.
• Attribute Charts: Attribute charts are used for count data where each data element is classified in one of two categories, such as good or bad. P charts (example 35.4, page 368) and np charts (example 35.5, page 371)are used to plot percentage or proportion defective, and c charts (example 35.6, page 373) and u charts (example 35.7, page 375) are used to plot counts of defects.
Control Chart Selection
• Short run Control Charts: Short run control charts should be considered when data are collected infrequently. Example 35.8, page 381.
• Moving Average and Moving Range Control Charts (MAMR): the MAMR charts may be suitable when data are collected periodically or when it takes time to produce a single item. Example 35.9, page 385.
Control Chart Analysis
• The control chart limits set at +- 3σ cover approximately 99.73% of the data.
• Points falling within the limits are due to common cause variations.
• Points falling outside the limits are due to special or assignable cause variations. Such points should be investigated immediately.
Analyzing Control Chart Behavior
• A process log may be a separate document or may be a part of the control chart.
• Entries in the process log should be identified by date and time and include all changes to the process and process environment.
• Such changes might include the occurrence of preventive or corrective maintenance, tool replacement, new parts, etc.
Analyzing Control Chart Behavior
• Some rules to test out of control conditions:
• 1. One point more than 3σ from the center line (either side).
• 2. Nine points in a row on the same side of a center line.
• 3. Six points in a row, all increasing or decreasing.
• Possible reasons for out of control conditions:
• Table 35.10, page 391.
• The six sigma professional might make additional tests for particular situations.
• For example if an increase in values represents a safety hazard, it is not necessary to wait of 6 points to take action.
Summary
• Every process has variation.
• The principal purpose of control charts is to help the operator recognize the presence of special causes so that corrective action can be taken in a timely manner.
• The method used to select samples for the control chart must be logical.
• The control chart limits set at +- 3σ cover approximately 99.73% of the data.
• Points falling within the limits are due to common cause variations.
• Points falling outside the limits are due to special or assignable cause variations. Such points should be investigated immediately.
• Entries in the process log should be identified by date and time and include all changes to the process and process environment.
• Such changes might include the occurrence of preventive or corrective maintenance, tool replacement, new parts, etc.
Home Work
• 1. What is the principle purpose of control charts?
• 2. What variable is selected for monitoring in a control chart?
• 3. Why do we need to investigate points falling outside the control limits of +- 3σ?
• 4. How should process log entries be identified and what types of entries must be recorded?