Chapter 6 Statistical Quality Control

Question 1

solution to quality problems are important to…

Answer 1

companies, stakeholders, employees, customers

Question 2

Statistical quality control (SQC)

Answer 2

the term used to describe the set of statistical tools used by quality professionals.

Question 3

SQC categories: descriptive statistics

Answer 3

are used to describe quality characteristics and relationships.
Included are statistics such as the mean, the standard deviation, the range, and a measure of the distribution of data.

Question 4

SQC categories: Statistical process control (SPC)

Answer 4

involves inspecting a random sample of the output from a process and deciding if it falls within range and whether the process is functioning properly.

Question 5

SQC categoties: Acceptance sampling

Answer 5

is used to randomly inspect a batch of goods to determine acceptance/rejection.

Question 6

what is the difference between SPC and acceptance sampling?

Answer 6

SPC is looking at the statistical process to see if it’s within the functional range. Whereas acceptance sampling is taking the end product, a batch of the goods, evaluating if they are acceptable or rejecting.

Question 7

Sources of Variation has 2 categories

Answer 7

Common causes of variation, Assignable causes of variation

Question 8

Sources of Variation: Common causes of Variation definition

Answer 8

Common causes of variation are based on random causes that we cannot identify. These types of variation are unavoidable and are due to slight differences in processing.

Question 9

Sources of Variation: Assignable sources of variation

Answer 9

can be observed involves those where the causes can be precisely identified and eliminated

Question 10

SQC - descriptive statistics, mean:

Answer 10

A statistic that measures the central tendency of a set of data.

Question 11

SQC - descriptive statistics, range:

Answer 11

The difference between the largest and smallest observations in a set of data.

Question 12

SQC - descriptive statistics, standard deviation:

Answer 12

A statistic that measures the amount of data dispersion around the mean.

Question 13

SQC - descriptive statistics, Distribution of data shape:

Answer 13

normal/Bell shape, When a distribution is symmetric, there are the same number of observations below and above the mean. This is what we commonly find when only normal variation is present in the data.

skewed: When a disproportionate number of observations are either above or below the mean, we say that the data have a skewed distribution.

Question 14

SQC - Statistical Process Control methods (SPC), control chart:

Answer 14

(also called process chart or quality control chart) is a graph that shows data plotted on a graph with a center line (CL), upper control limit (UCL), and lower control limit (LCL)
Control charts for variables are used to monitor characteristics that can be measured, e.g., length, weight, diameter, time.
Control charts for attributes are used to monitor characteristics that have discrete values and can be counted, e.g., percent defective, number of flaws.

Question 15

SQC - SPC, control chart shows - out of control:

Answer 15

when a plot of data reveals that one or more samples fall outside the control limits.

Question 16

types of control charts

Answer 16

variable and attribute

Question 17

Type of Control Chart: Variable

Answer 17

A product characteristic that can be measured and has a continuum of values (e.g., height, weight, or volume):
x-bar charts
R-charts

Question 18

Type of Control chart, Attribute:

Answer 18

A product characteristic that has a discrete value and
can be counted, yes/no or pass/fail:
p-charts
c-charts

Question 19

control charts, variable: x-bar charts

Answer 19

to monitor the changes in the mean of a process
(central tendencies)
System can show acceptable central tendencies but unacceptable variability.

Question 20

control charts, variable, R-charts:

Answer 20

Use R-charts to monitor the dispersion or variability of the process.
System can show acceptable variability but unacceptable central tendencies.

Question 21

control charts for attributes, p-charts:

Answer 21

Use p-charts for quality characteristics that are discrete and involve yes/no or good/bad decisions.
P-charts measure the proportion of items in a sample that are defective:
• proportion of broken cookies in a batch
• proportion of cars produced with a misaligned fender
P-charts are used when both the total sample size and the number of defects can be computed.

Question 22

control charts for attributes, C-charts:

Answer 22

Use c-charts for discrete defects when there can be more than one defect per unit.
Actual number of defects.
Number of flaws or stains in a carpet sample cut from a production run. o Number of complaints per customer at a hotel.
C-charts are used when you can compute only the number of defects but not the proportion that is defective.

Question 23

process capability

Answer 23

The ability of a production process to meet or exceed preset specifications.

Question 24

product specifications

Answer 24

Preset ranges of acceptable quality characteristics.
often called tolerances
preset ranges of acceptable quality characteristics, such as product dimensions
Example: bottle fill might be 16 oz. ± 0.2 oz. (15.8oz.–16.2oz.)
based on how product is to be used or what the customer expects

Question 25

Measuring Process capabilities, Process capability index (Cp)

Answer 25

Process capability is measured by the process capability index, Cp, which is computed as the ratio of the specification width to the width of the process variability.
Cp assumes that the process is centered in the specification
range.

Question 26

Measuring Process capabilities, Cpk

Answer 26

helps to address a possible lack of centering of the

process.

Question 27

six sigma quality

Answer 27

A high level of quality associated with approximately 3.4 defective parts per million.

Question 28

Six Sigma Approach, DMAIC

Answer 28

Define
Measure
Analyze
Improve 
Control

Question 29

Six Sigma Approach, DMAIC, Define:

Answer 29

Define the quality problem of the process

Question 30

Six Sigma Approach, DMAIC, Measure:

Answer 30

measure the current performance of the process

Question 31

Six Sigma Approach, DMAIC, Anaylyze:

Answer 31

Analyze the process to identify the root causes of the quality problem

Question 32

Six Sigma Approach, DMAIC, Improve:

Answer 32

Improve the process by eliminating the root cause of the problem

Question 33

Six Sigma Approach, DMAIC, Control:

Answer 33

control the process to ensure the improvements continue

Question 34

Acceptance sampling:

Answer 34

the third branch of statistical quality control, refers to the process of randomly inspecting a certain number of items from a lot or batch in order to decide whether to accept or reject the entire batch. What makes acceptance sampling different from statistical process control is that acceptance sampling is performed either before or after the process, rather than during the process. Acceptance sampling before the process involves sampling materials received from a supplier, such as randomly inspecting crates of fruit that will be used in a restaurant, boxes of glass dishes that will be sold in a department store, or metal castings that will be used in a machine shop. Sampling after the process involves sampling finished items that are to be shipped either to a customer or to a distribution center

Question 35

Goal of acceptance sampling

Answer 35

to determine the criteria for acceptance or rejection based on:
size of the lot (N)
size of the sample (n)
number of defects above which a lot will be rejected (c) o number of samples that will be taken

Question 36

single , double, multiple sampling plans

Answer 36

Which one to use is based on cost involved, time consumed, and cost of passing on a defective item.
Can be used with both variable and attribute measures, but is more commonly used for attributes.