exam 1: statistical quality control

Statistical Quality Control (SQC)

• The quantitative aspects of quality management

• Processes usually exhibit some variation in their output

Assignable variation

• Variation that is caused by factors that can be identified and managed

Common variation

• Variation that is inherent in the process itself (often called random variation)

Upper specification

the maximum acceptable value for a characteristic

Lower specification

the minimum acceptable value for a characteristic

Process Capability

The ability of a process to consistently produce a good or deliver a service with a low probability of generating a defect

Specification limits

range of variation that is considered acceptable by the designer or customer

Process limits

range of variation that a process is able to maintain with a high degree of certainty

not

Process control limits exceed specification limits – process is ____ capable of meeting requirements

mean

the process can have a ____ shift away from the desired center (i.e., away from the desired mean).

In this case, the process remains capable even though the mean shifted, which is not desired.

Process Capability Index (Cpk)

Ratio of the range of values allowed divided by the range of values produced

• Shows how well the parts being produced fit into the range specified by the design specifications

• Cpk larger than one (Cpk > 1) indicates process is capable

• When the two numbers are not close, indicates mean has shifted

Statistical process control

Testing a sample of output to determine if the process is producing items within a preselected range

Attributes

Quality characteristics that are classified as either conforming or not conforming

Variable

Characteristics that are measured using an actual value

p-chart

process control measurement:

Used when an item (or service) is either good or bad (a yes-no decision)

Creating p charts

1. Calculate the sample proportions p for each sample.

2. Calculate the average of the sample proportions.

3. Calculate the standard deviation of the sample proportion.

4. Calculate the control limits.

5. Plot the individual sample proportions, the average of the proportions, and the control limits

c-chart

X-bar and R-Charts

Variable measurement process control charts:

1. Size of samples: Preferable to keep small (usually around 5 units)

2. Number of Samples: Each sample plotted on chart. Use about 25 samples to set up chart

3. Frequency of samples: Trade-off between cost of sampling and benefit of adjusting the system

4. Control limits:  For simplicity in this class, use z = 3 (unless told otherwise)

Creating X-Bar & R-Charts

1. Calculate the sample statistics (i.e., the sample average and range) for each sample.

2. Calculate the average across all samples to find the overall mean (also called the “grand mean” or ”) and the overall range (”).

3. Find the A2 , D3 , and D4 factors from the control limits chart.

4. Calculate the UCL and LCL for each chart.

5. For the X-bar chart, plot the individual sample means, the overall average (as a guideline), and the control limits.

6. For the R-chart, plot the individual sample ranges, the overall average range (as a guideline), and the control limits.

Acceptance sampling

-Executed through a sampling plan

-Results include accept, reject, or retest

-Performed on goods that already exist to determine what percentage of the products conform to specifications:

• Determine quality level

• Ensure quality is within predetermined level