Six Sigma Black Belt Exam Cheat Sheet

The certified six sigma professional with a black belt can demonstrate Six Sigma theories, principles, supporting systems, and technologies. A black belt should lead by example, understand team dynamics, and gives roles and tasks to team members. According to Six Sigma principles, black belts have a complete mastery of all parts of the DMAIC model. They understand the basics of lean enterprise concepts, can spot non-value-added items and operations, and can employ particular six sigma tools.

Generally, Six Sigma is a set of techniques and tools that help businesses improve their processes. It's a problem-solving methodology that helps enhance business and organizational operations. It can also be defined in several other ways: A quality level of 3.4 defects per million opportunities, a rate of improvement of 70 % or better, a data-driven, problem-solving methodology of Define Measure Analyze Improve Control (DMAIC). Six Sigma is an initiative taken on by organizations to create bottom-line breakthrough change. You can take a lean six sigma black belt practice exam to get an idea of this exam’s question.

Six Sigma Black Belt Exam Cheat Sheet 

Applying the correct tools to your Six Sigma initiatives can help you achieve accurate, acceptable, and reusable results. Here's a quick rundown of the Six Sigma black belt exam cheat sheet. You can obtain your Six Sigma black belt certification to work as a professional in the top business firms. 

ANOVA 

It is a collection of statistical models and their associated procedures, in which the observed variance is partitioned into components due to different explanatory variables. In its most basic version, ANOVA is a statistical test that determines if the means of numerous groups are all similar and thus extends the student's two-sample test to even more than two groups. When comparing multiple groups, this is used for hypothesis testing. 

DoE (Design of Experiments) 

The use of statistical tools (such as ANOVA above and regression below) to identify the significance of different factors with a small quantity of data is known as the design of experiments. It's used when there are a lot of variables that could affect the outcome (like numerous x's in the conventional Y=f(x) calculation). 

 You don't have to research One Factor At a Time (OFAT) to separate which components have the most impact by gathering, organizing, and analyzing data using the DoE technique. DoEs are best performed with software created specifically for them (Minitab or JMP). 

The following are the essential ideas for DoE’s :

1. Orthogonality  

Orthogonality refers to the kind of comparisons (contrasts) that can be made legally and effectively. If the data is regular, comparisons can be expressed by vectors and pairs of orthogonal differences that are mutually independent and independently distributed. Because of this separation, each orthogonal treatment gives the others different information. If there are T treatments and T-1 orthogonal contrasts, the contrasts contain all the data extracted from the experiment. 

2. Blocking  

Structuring experimental units into groups (blocks) comparable to one another is blocking. Blocking eliminates identified but unimportant sources of variation across departments, allowing for a more precise estimation of the cause of variation during the investigation. 

3. Randomization  

Many mathematical theories investigate the ramifications of allocating units to treatments using random processes such as random number tables or randomization devices like playing poker or dice. The dangers associated with random allocation can be calculated and thus altered to an acceptable standard if the sample size is enough. Randomization does not imply chaos, and proper random procedures must be utilized with great care. 

4. Comparison  

It is challenging to duplicate measured results in many disciplines of study, and treatment evaluations are substantially more repeatable and are frequently preferred. Frequently, one is compared to a standard or conventional treatment that serves as a baseline. 

Step-by-Step Procedure 

In a successful experiment design, not every step may be required. Instructions on how to perform a DoE with a software program are generally available. 

• Choose a problem. 
• Choose a dependent and an independent variable (s). 
• Determine the many possibilities. 
• Compute the value of observations. 
• Randomize the design. 
• Observe ethical and legal guidelines. 
• Creating a mathematical model. 
• Gather information. 
• Data reduction. 
• Check the data. 

Regression 

Linear Regression 

Linear regression aims at establishing a formula for a variable (y) from one or more components using a straight line (Xs). 

A software package like Excel, Minitab, or JMP is best. The majority of linear regression applications are divided into two categories: 

Linear regression can be used to build a predictive model to an observed, collected data of y and X variables if the purpose is forecasting. If an added value of X is provided without its associated value of y after constructing such a model, the fitted model can be used to predict the value of y. 

We can use linear regression analysis to measure the significance of the association between y and the Xj. We can also use it to evaluate which Xj may have no connection with y and recognize which subgroups of the Xj encompass redundant data regarding y. This is done so that once one variable is known, the others are no longer helpful. 

Non-Linear Regression  

Non-linear regression tries to get an equation for a variable (y) from one or more factors (Xs). But it varies from linear regression. This way allows for a relationship that isn't a straight line. 

A software program such as an Excel add-on, Minitab, or JMP is ideal. Exponential functions, logarithmic functions, trigonometric functions, power functions, Gaussian functions, and Lorentzian curves are illustrations of non-linear functions. Some functions, such as exponential and logarithmic functions, can be turned into linear functions. 

Non-normal Distributions  

There are as many diverse groups as there are various distributions. 'There are no ideal models, but there are helpful models,' remarked Deming. Concerning your issue, the question is, 'What tools and strategies will work well with my population's allocation?' Because cycle time information cannot fall below zero, it is never perfectly normal. 

When a group has non-normal data, it can frequently be divided into parts with distributions that are close to normal. You can assume normalcy after identifying these subpopulations and extracting data from them to test independently. Evaluate how crucial distribution is for the technologies you intend to utilize. 

If the distribution is non-normal, the following tools in this cheat sheet are affected: 

• Confidence Intervals 
• Gage R&R 
• T-test 
• ANOVA 
• Pearson Correlation Coefficient 
• Design Of Experiments 
• Regression 
• Control Charts 
• Control Limits 
• Process Capability 
• Control Plans.

Weibull, Exponential, Log-norma, Gamma, Poisson, Chi-squared, Beta, Bi-modal, Binomial, and Student-t are more typical non-normal distributions.

Variance Inflation Factor (VIF)  

The VIF calculates how much the contact of independent variables influences the dependent variable. (In other words, how much do the various x's cooperate to decide Y in the Y = f(x) equation?) 

Life Testing & Reliability 

AQL  

The Acceptable Quality Limit (AQL) is the worst-case quality level that is still regarded tolerable, expressed as a percentage or ratio. A procedure is acceptable in quality assurance if the applicable data used to produce a control chart does not fall below the excellent quality standards. Alternatively, the process is said to be at a control level that can be rejected. 

AOQL  

A sample plan's Average Outgoing Quality Limit (AOQL) is the most outstanding value on the AOQ curve. It may be used to identify defective units, flaws per unit, and defects per quantity, and it is measured as faulty or defect rate. The AOQ curve plots mean outgoing value as a function of receiving quality.

QFD (Quality Function Deployment)  

QFD stands for the means to turn user needs into design quality, apply activities creating quality, deploy techniques for obtaining design quality into subsystems and constituent components, and finally to particular manufacturing process elements. QFD is intended to assist planners in focusing on features of a new or existing product or service from the perspectives of market segments, company needs, and technological development requirements. The method produces graphs and matrices. 

QFD Procedures  

1. Recognize customer and technical specifications.
2. Convert technical specifications into critical quality characteristics (CTQs) and work up to the CTQs.

When employing QFD, the most frequent tool in the House of Quality (HOQ).

Get ahead in project management with our PMP certification exam prep course. Start your journey to success now!

Top 10 Six Sigma Black Belt Questions & Answers 

Here is a list of the IASSC black belt exam questions to give you an idea of the exam. These examples of black belt exam questions and answers will assist in gaining confidence to take the certification exam. 

Q1. To determine if a process is under control or not, which of the control charts must show at least 20 subgroups of observed data? 

• R-Chart 
• P-Chart 
• C-Chart 
• Y-Chart 

Data is collected at regular intervals in an R-chart, and it is a measure of dispersion that evaluates the sample range over time. At least 20 subgroups of observed data must be present in the R-chart, with each subgroup holding 3 to 6 values. It's easy to see if the variance falls between the upper and lower control boundaries with this little set of observations. 

Q2.Which of the strategies below significantly reduces changeover times? 

• Continuous flow 
• Single minute exchange of dies (SMED) 
• Standard work 
• Work in process (WIP) 

Single-Minute Exchange of Dies (SMED) is a collection of strategies for substantially reducing the time it takes to execute a changeover. 

Q3. Correction, overproduction, inventory, and motion are all examples of? 

• Waste 
• 5S target areas 
• Noise 
• Value-added activities 

A waste is a loss that has no added value. Before the project's completion, waste should be removed or minimized. 

Q4. If the primary metric of a project is cost reduction, what would the secondary metric be? 

•  Reduced cycle time 
•  Reduced scrap rate 
•  Reduced set-up time
•  All the above
•  None of the above

The consequence measures include reduced cycle time, scrap time, and set-up time. 

Q5. Which of the following tools can detect waste or activities that provide no value? 

• Force yield analysis 
• Pareto analysis 
• Scatter diagram 
• Process map 

A process map is a precise pictorial portrayal of a process flow that systematically uses color-coded icons to display steps, events, and operations. This technique is quite helpful in determining waste and non-value-added activities. 

Q6. The term that is extremely close to the expected value is called? 

• Probabilistic model
•  mean
•  Markov value
• Regressive value

For random variables, the term "expected value" is quite similar to the word "mean." 

Q7. ASV refers to a system that provides items or services at the right time and in quantities. 

• Takt time 
• Kaizen 
• Just-in-time 
• Single-piece flow 

Just in time is committed to reducing waste. The principle of JIT is to manufacture the required products in the amount needed and at the time necessary. 

 Q8. Continuous, incremental progress is defined as which of the following? 

• Kanban 
• Kaizen 
• JIT 
• Kaikaku 

Kaizen is a long-term technique for systematically working to accomplish modest incremental improvements in processes to attain effectiveness and productivity. 

Q9. To create an extensive catalog of ideas about a subject, which of the following procedures is used? 

• Benchmarking 
• Brainstorming 
• Goal-setting 
• Problem-solving 

Brainstorming is a strategy for getting a comprehensive list of ideas from a group. Brainstorming is a valuable strategy in Six Sigma to define stages. 

Q10. In most cases, positional, cyclical, and temporal changes are investigated in?  

• SPC charts 
• Multi-vari charts 
• Cause and effect diagrams 
• Run charts 

The fluctuation pattern is graphically depicted in a multi-vari chart. Multi-vari charts are used to examine positional, cyclical, and temporal variations. 

Conclusion 

With Knowlegdehut Six Sigma Black Belt Certification, learn how to use the Lean Six Sigma technique to improve processes, save costs, and increase quality within your firm. You can build your quality toolkit by identifying and eliminating the causes of errors in business operations. You will oversee project teams as a Certified Lean Six Sigma Black Belt by identifying problems and areas that need improvement. This accreditation verifies your capacity to improve quality by streamlining processes.