ASQ CQA – Questions With Verified Solutions
Save Groups
Terms in this set (341)
Distributions patterns of variation in data
Histograms Vertical bar chart of a frequency distribution used to
show number of times a given discrete piece of
information occurs in the data set
Bell-Shaped Distribution Normal distribution in Histograms
Deviations may indicate presence of complicating
factors or outside influences - should be investigated
but are not necessarily bad
Plateau Distribution in histograms
Flat top with no distinct peak and slight tails on either
side
May be a result of many different bell-shaped
distributions with centers spread evenly throughout
the range of data
May sometimes naturally occur, or may have several
overlapping populations causing a plateau, or there
is a problem with measurement system
Comb Distribution in histograms
High and low values alternating in a regular fashion
o Error in measurement, in the way data was
grouped, or systematic bias in how data was rounded
,Skewed Distribution in histograms
o Asymmetrical shape in which the peak is off center
in the range, and tails off sharply on one side but
gently on the other.
o Negatively skewed: tails towards left
o Positively skewed: tails towards right
o If you have a hard boundary, and data piles up
against that boundary but drags on toward the limit
o Naturally occurring phenomenon
Truncated Distribution in histograms
o Asymmetrical shape in which the peak is at or near
the edge of the range, and distribution ends very
abruptly on one side but tails off gently on the other.
o May indicate a problem - Ex, data was removed
from the set
Isolated-peakd Distribution in histograms
o Small separate group of data in addition to the
larger distribution. Similar to double-peaked but the
short bell shape indicates something that doesn't
happen very often.
Edge-peaked Distribution in histograms
o Large peak appended to an otherwise smooth
distribution. Similar to Comb in that an error was
probably made in the data.
SIPOC supplier-input-process-output-customer
· Cannot improve a process without understanding
how it functions from a process management
perspective
,PDCA Plan-Do-Check-Act
· Plan: identify opportunity for improvement
o Define activities to be performed: data collection,
RCA, stakeholder meeting,
· Do: perform a trial run to see if project is running in
the right direction or not
· Check: compile and analyze results from Do stage -
readjust if necessary
o May change the plan, adopt it in procedure,
abandon the idea, changing the scope, etc. then
starting over
· Act: Implement actions / OR Adjust plan and take
another trip
o Must monitor results
RCA 7 Step problem-solving model 1. Identify the problem - use data analysis tools such
as flowcharts, etc.
2. List possible root causes - all invested groups
should weigh in
3. Search out/investigate the most likely root or
probable cause
4. Identify potential solutions
5. Select and implement a solution
6. Followup to evaluate effectiveness of the solution
a. Control charts, frequency distributions can help
show effectiveness
7. Standardize the process if it was proven to be
successful
a. Revise procedures, construct production device,
etc.
, Six Sigma · Statistical methodology that focuses on reducing
variation and defects and mistake-proofing a process
· 6sigma:
o Measure variation in products relative to
specifications
o Operating at a 6sigma level indicates products are
99.9997% defect free
o To what extent a product/process varies from
perfection
o Process for structuring improvement goals by
using DMAIC
Save Groups
Terms in this set (341)
Distributions patterns of variation in data
Histograms Vertical bar chart of a frequency distribution used to
show number of times a given discrete piece of
information occurs in the data set
Bell-Shaped Distribution Normal distribution in Histograms
Deviations may indicate presence of complicating
factors or outside influences - should be investigated
but are not necessarily bad
Plateau Distribution in histograms
Flat top with no distinct peak and slight tails on either
side
May be a result of many different bell-shaped
distributions with centers spread evenly throughout
the range of data
May sometimes naturally occur, or may have several
overlapping populations causing a plateau, or there
is a problem with measurement system
Comb Distribution in histograms
High and low values alternating in a regular fashion
o Error in measurement, in the way data was
grouped, or systematic bias in how data was rounded
,Skewed Distribution in histograms
o Asymmetrical shape in which the peak is off center
in the range, and tails off sharply on one side but
gently on the other.
o Negatively skewed: tails towards left
o Positively skewed: tails towards right
o If you have a hard boundary, and data piles up
against that boundary but drags on toward the limit
o Naturally occurring phenomenon
Truncated Distribution in histograms
o Asymmetrical shape in which the peak is at or near
the edge of the range, and distribution ends very
abruptly on one side but tails off gently on the other.
o May indicate a problem - Ex, data was removed
from the set
Isolated-peakd Distribution in histograms
o Small separate group of data in addition to the
larger distribution. Similar to double-peaked but the
short bell shape indicates something that doesn't
happen very often.
Edge-peaked Distribution in histograms
o Large peak appended to an otherwise smooth
distribution. Similar to Comb in that an error was
probably made in the data.
SIPOC supplier-input-process-output-customer
· Cannot improve a process without understanding
how it functions from a process management
perspective
,PDCA Plan-Do-Check-Act
· Plan: identify opportunity for improvement
o Define activities to be performed: data collection,
RCA, stakeholder meeting,
· Do: perform a trial run to see if project is running in
the right direction or not
· Check: compile and analyze results from Do stage -
readjust if necessary
o May change the plan, adopt it in procedure,
abandon the idea, changing the scope, etc. then
starting over
· Act: Implement actions / OR Adjust plan and take
another trip
o Must monitor results
RCA 7 Step problem-solving model 1. Identify the problem - use data analysis tools such
as flowcharts, etc.
2. List possible root causes - all invested groups
should weigh in
3. Search out/investigate the most likely root or
probable cause
4. Identify potential solutions
5. Select and implement a solution
6. Followup to evaluate effectiveness of the solution
a. Control charts, frequency distributions can help
show effectiveness
7. Standardize the process if it was proven to be
successful
a. Revise procedures, construct production device,
etc.
, Six Sigma · Statistical methodology that focuses on reducing
variation and defects and mistake-proofing a process
· 6sigma:
o Measure variation in products relative to
specifications
o Operating at a 6sigma level indicates products are
99.9997% defect free
o To what extent a product/process varies from
perfection
o Process for structuring improvement goals by
using DMAIC
