These Six Sigma Black Belt multiple-choice questions and their answers will help you strengthen your grip on the subject of Six Sigma Black Belt. You can prepare for an upcoming exam or job interview with these 70+ Six Sigma Black Belt MCQs.
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A. The average of the mean and median
B. Then mid point of a distribution
C. The arithmetic balance point of a distribution
D. The most frequently occuring data point in a set of observations
A. Reduce variation to be within the customer's specification limits, and to center the process mean to align with the customer's target.
B. Reduce variation to be within the customer's specification limits.
C. Eliminate all forms of waste (defects, waiting, over production, etc.)
D. Center the process mean to align with the customer's target.
A. With defects
B. Expensive
C. Low Quality
D. Mistake Proof
A. When Cp=pp
B. When the process is perfectly centered
C. When the standard deviation is less than 1
D. When the specification limits are wide
A. Repair Station
B. Ending
C. Beginning
D. Decision
A. 2
B. Negative
C. 0.5
D. 1
A. Contol charting
B. Benchmarking
C. Six Sigma improvement
D. Control defining
A. To give all team members a single, common view of the entire process
B. To reveal unnecessary, complex, and redundant steps in a process.
C. (All of these)
D. To compare the actual process, and all its variations, against the ideal process
A. Skew Chart
B. Control Chart
C. Pareto Chart
D. Bar Chart
A. B and C
B. C
C. A
D. A, B, and C
E. A and C
A. A critically weighted ranking of categories
B. An alphabetic based ranking of categories
C. A financially weighted ranking of categories
D. A frequency based ranking of categories
A. Visualize the process
B. Identify wastes
C. Rank costs
D. Prioritize delays
E. Improve takt time
A. Juran
B. Ishikawa
C. Deming
D. Okinawa
A. Range chart analysis
B. Variable Measurement
C. Attribute Measurement
D. Mean chart analysis
A. 3.4 defects per million opportunities
B. 0.34 defects per million opportunities
C. 340 defects per million opportunities
D. 34 defects per million opportunities
A. Charter
B. Analyze
C. Define
D. Initiation
A. Suppliers, Inputs, Procedure, Outputs, Customers
B. Suppliers, Inputs, Process, Outputs, Customers
C. Simple, Inputs, Procedure, Outputs, Constructs
D. Systems Inputs, Process, Outputs, Complex
A. <30%
B. <20%
C. <15%
D. <10%
A. Map all process steps and determine their average duration
B. Determine the mean and standard deviation of a population
C. Find the right settings for key process input variables, to optimize process performance
D. Establish the best graphing method to illustrate process performance
A. C
B. A, C, and D
C. D
D. A
E. B and C
A. Master Black Belt
B. Black Belt
C. Champion
D. Green Belt
A. Equipment failure
B. Reduced yields
C. Employee absenteeism
D. Setup and adjustment
A. the first pass inspection
B. the KPI
C. the first pass yield
D. the success yield
A. A, B, and C
B. A
C. C
D. A and B
E. B and C
A. 1
B. 1.5
C. 0.5
D. 2
A. Packaging
B. Distribution
C. Marketing
D. Retail Store
A. The lower control limit for the R chart is 0
B. The process is already in statistical control
C. The SPC is used for tracking transaction times at a warehouse
D. The control limits are wider than customer specification limits
A. Process chart
B. Data chart
C. Critical to Quality (CTQ) tree
D. Quality Control Plan
A. FTA
B. QFD
C. FMEA
D. Muka
A. To review errors
B. To analyze data
C. To study the equality of two means
D. To study the equality of two variances
A. X-bar and R
B. t-test, chi-square
C. AQL, p-bar
D. p, n
E. R, sigma
A. severity x risk x detection
B. severity x occurrence x risk
C. severity x occurrence x detection
D. occurrence x detection x control
A. Exponential
B. Normal
C. Poisson
D. Lognormal
A. Technical results driven process
B. A customer driven process
C. Parametric approach
D. Customer competitive assessment
E. Financial metrics approach
A. Groupthink
B. Cognition
C. Nominal Group Technique
D. Human Needs
E. The Skinner Box
A. Linear Regression
B. XY Diagram
C. Multivariate regression
D. Correlation coefficient
A. 1
B. 0.025
C. 0.05
D. 0.5
E. 0.02
A. There is limited data
B. There is a need to simplify the process
C. There is a need to plot multiple variables per chart
D. There is limited operator time
A. Defines Projects
B. Helps recruit team members/obtains resources
C. Provides technical six sigma expertise
D. Breaks down roadblocks
A. 5 sigma
B. 2 sigma
C. 3 sigma
D. 1 sigma
A. Process Capability
B. Poisson Test
C. Standard Deviation
D. Gage R&R
A. Average of median and mean
B. Average deviation of values from the mean of a data distribution
C. Average squared deviation of each individual data point from the mean
D. Difference between maximum and minimum value of a set of data points
A. Line management of improved processes, post-implementation
B. Training organisation staff in six sigma techniques and team work
C. Use analytics tools to identify root causes of problems
D. Applying Kaizen thinking to drive continuous improvement
A. Measure
B. Analyze
C. Improve
D. Define
A. Andon boards
B. Standard work instructions
C. Work cells
D. Queue times
A. Analyze
B. Improve
C. Define
D. Measure
A. 4 Sigma
B. 5 Sigma
C. 3.8 Sigma
D. 6 Sigma
A. To remove bad parts from the sample
B. To estimate whether or not the quality of the parts is acceptable
C. To estimate if the entire lot is of acceptable quality
D. To determine if every part in the lot needs to be tested or not
A. nU charts
B. MR Charts
C. Xbar charts
D. Z Charts
A. 3.4 defects per million opportunities
B. 233 defects per million opportunities
C. 6,210 defects per million opportunities
D. 66,810 defects per million opportunities