General Flashcards
16 cards from real Lean Six Sigma Black Belt Certification practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 16 General flashcards as text
How is Total Process Variation (t) expressed in terms of Gage (m) and Part (p) Variation?
Answer: Squareroot of (ơm squared+ ơp squared)
Total Process Variation (σt) is expressed as the square root of the sum of the squares of its independent components, specifically Gage Variation (σm) and Part Variation (σp). This relationship, often represented as σt = √(σm² + σp²), assumes that the variation introduced by the measurement system (gage) and the actual variation in the parts being measured are independent sources of variability within the process.
In terms of Repeatability(?r) and Reproducibility(?o) variation, what is Gage Variation(?m)?
Answer: (ơr squared+ ơo squared)1/2
Gage Variation (σm), which represents the variability introduced by the measurement system, is calculated as the square root of the sum of the squares of Repeatability (σr) and Reproducibility (σo) variations. Repeatability refers to the variation when the same operator measures the same part multiple times, while Reproducibility refers to the variation between different operators measuring the same part. This root sum of squares formula combines these independent sources of measurement error.
What GRR percentage must be exceeded before the gage needs to be replaced?
Answer: 0.3
A GRR (Gage Repeatability and Reproducibility) percentage of 30% or more indicates that the measurement system is unacceptable. This threshold signifies that the measurement error is too large relative to the process variation, making the data unreliable for decision-making. Such a system needs significant improvement, repair, or replacement to ensure accurate measurements.
What guidelines should you follow while choosing a sample?
Answer: Determine sample size using a formula and base it on the tolerance and confidence interval expected and standard deviation or the current error rate of the population
Choosing a sample size is a critical statistical decision, not an arbitrary one. It must be determined using appropriate formulas that consider factors like the desired confidence level, the acceptable margin of error (tolerance), and the variability (standard deviation) or proportion of defects in the population. This rigorous approach ensures the sample is representative and provides statistically valid insights for process improvement.
Who is the process expert who rates the samples as acceptable, unacceptable, defective, etc.?
Answer: Master Appraiser
In a measurement system analysis or appraisal process, the Master Appraiser is the recognized expert. This individual possesses deep knowledge of the process and the measurement criteria, making them responsible for setting the standard and accurately rating samples. Their role is crucial for ensuring consistency and validity in the appraisal system, as they are the ultimate authority on sample classification.
SPC stands for?
Answer: Statistical Process Control
SPC stands for Statistical Process Control. It is a methodology used in Lean Six Sigma to monitor and control a process using statistical methods. SPC helps to identify and eliminate special cause variation, ensuring that a process remains stable and predictable over time.
SEM stands for?
Answer: Standard Error of Mean
SEM stands for Standard Error of the Mean. It is a statistical measure that quantifies the accuracy with which a sample mean represents the true population mean. A smaller SEM indicates that the sample mean is a more precise estimate of the population mean, reflecting less variability in sample means.
Which of the following is not a continuous data capability index?
Answer: Process Performance
Process Performance (Pp, Ppk) and Process Capability (Cp, Cpk) are specific indices used to assess process capability for continuous data. However, 'Process Performance' itself is not a continuous data capability index but rather a general term describing the overall performance of a process. The other options refer to specific, recognized statistical indices.
What is the equation used to determine Process Capability?
Answer: (USL-LSL)/(6 * ơ)
The equation used to determine Process Capability (Cp) is (USL - LSL) / (6 * σ). Here, USL is the Upper Specification Limit, LSL is the Lower Specification Limit, and σ (sigma) is the standard deviation of the process. This formula compares the width of the specification limits to the natural variation of the process, assuming the process is centered.
Once you know the values for Cpl and CPU, how do you calculate Process Capability Index (Cpk)?
Answer: min (Cpl, Cpu)
The Process Capability Index (Cpk) is calculated as the minimum of Cpl (Process Capability Lower) and Cpu (Process Capability Upper). Cpk accounts for both the process spread and its centering relative to the specification limits. By taking the minimum, Cpk reflects the worst-case scenario, indicating how close the process mean is to the nearest specification limit and thus its actual capability.
When is the Mean off-center?
Answer: Cpk < Cp
Cp measures the potential capability of a process, assuming it is perfectly centered between the specification limits. Cpk, however, considers both the process spread and its actual centering. If the process mean is off-center, Cpk will be less than Cp, as the process is not utilizing the full width of the specification limits effectively, indicating a shift from the ideal center.
Which of these tasks ought to ideally be completed first when implementing a Measure?
Answer: Checking Resolution
When implementing a measurement system, checking its resolution is typically the first crucial step. Resolution refers to the smallest increment a measurement system can detect. If the measurement system lacks sufficient resolution (e.g., it can't distinguish between parts that are truly different), then subsequent checks like precision, repeatability, or normality will be meaningless or misleading.
The GRR is typically 42% in a Measurement System Analysis activity, with Gage Variation and Part Variation each contributing equally. How would you respond?
Answer: Calibrate the equipment, check operator variation, and identify Part Variation.
A GRR of 42% is unacceptable, indicating significant measurement error. Since Gage Variation and Part Variation contribute equally, it suggests issues with both the measurement system itself (gage and operators) and potentially the inherent variability of the parts being measured. Therefore, calibrating the equipment addresses the gage, checking operator variation addresses reproducibility, and identifying Part Variation helps understand if the measurement system is even capable of distinguishing between parts.
You normally use the following tool to scope a project during the Measure stage:
Answer: SIPOC
The SIPOC diagram (Suppliers, Inputs, Process, Outputs, Customers) is a fundamental tool used in the Measure phase of Lean Six Sigma. It helps to define the boundaries of a process, identify key stakeholders, and understand the flow of inputs and outputs. This comprehensive overview is essential for scoping the project and ensuring everyone has a shared understanding of the process being improved.
Which of these is the most crucial antecedent to the calculation of capability?
Answer: Process Stability
Process stability is the most crucial antecedent to calculating process capability. Capability indices (like Cp, Cpk) are only meaningful for processes that are in statistical control, meaning they are stable and predictable over time. If a process is unstable, its future performance cannot be reliably predicted, rendering capability calculations misleading and unreliable.
Which chart type should you use when the sample size varies and each sample could include several occurrences of the specified condition?
Answer: U chart
The U chart is used for attribute data when the sample size varies and each sample can have multiple occurrences of the specified condition (e.g., defects per unit). It plots the number of defects per unit, making it suitable for situations where the opportunity for defects changes with each sample. This allows for effective monitoring of defect rates even with fluctuating sample sizes.