ICBB Practice Questions

Stakeholders are defined as individuals, groups, or organizations that have an interest in or are impacted by the execution and outputs of a process. In Lean Six Sigma methodology, stakeholders encompass internal and external entities, including customers, suppliers, process owners, employees, and management.

B. Senior management represents a specific subset of internal leadership, not the full spectrum of entities interested in process outputs.

C. Co-workers represent internal peers involved in process execution, constituting only a narrow group of overall stakeholders.

D. Process owners are individuals with specific authority to manage and improve a process, rather than the general set of output-interested parties.

1. Evans, J. R., & Lindsay, W. M. (2017). Managing for Quality and Performance Excellence (10th ed.). Cengage Learning. Chapter 3: Customer Focus, pp. 102–106.

2. ISO 9000:2015 Quality management systems — Fundamentals and vocabulary, Section 3.2.3 "Interested party / Stakeholder".

In Lean Six Sigma and Quality Management principles, customer purchasing behavior and decision-making criteria are broadly categorized into four primary dimensions: Features (product functionality and quality characteristics), Integrity (seller credibility and trust), Delivery (speed, availability, and lead time), and Expense (the total cost or price incurred by the customer).

Option A is incorrect because color is a specific product attribute falling under the broader category of Features, not one of the primary decision dimensions.

Option C is incorrect because season reflects market timing or environmental context rather than a primary customer decision evaluation criterion.

Option D is incorrect because Expense correctly identifies the cost dimension of the customer decision model.

1. Gryna, F. M., Chua, R. C., & Defeo, J. A. (2007). Juran's Quality Planning and Analysis for Enterprise Quality, 5th Ed., McGraw-Hill, Chapter 3: Customer Satisfaction and Quality, pp. 45–52.

2. Oakland, J. S. (2014). Total Quality Management and Operational Excellence: Text with Cases, 4th Ed., Routledge, Chapter 2: Customer-Supplier Relationships. https://doi.org/10.4324/9781315815541

In Design of Experiments (DOE), an interaction occurs when the effect of one input variable (factor) on the output response depends on the level of another input variable. This means the combined effect of the two inputs is greater (or different) than the sum of their individual main effects. Identifying interactions is a primary reason Lean Six Sigma practitioners use factorial designs rather than one-factor-at-a-time (OFAT) experimentation.

A. Dependency: This refers to general statistical dependence between variables but is not the specific DOE terminology for combined factor effects on an output.

B. Bimodal reaction: This refers to a statistical distribution with two distinct peaks, not the combined effect of input factors.

D. Amplified effect: This is a generic descriptive phrase, not a recognized statistical term in DOE for this specific phenomenon.

1. Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). John Wiley & Sons. (Section 5.1 Introduction to Factorial Designs, p. 184).

2. NIST/SEMATECH e-Handbook of Statistical Methods, Section 5.3.3.3. "How do you interpret interaction effects?".

In linear correlation analysis, a positive correlation exists when an increase in the independent variable (X) is directly associated with an increase in the dependent variable (Y). This relationship is quantified by a positive correlation coefficient (r > 0), indicating that the variables move in the same direction. When plotted on a scatter diagram, this relationship visually manifests as a trend line that slopes upward from left to right.

A. Negative: Incorrect because a negative correlation indicates that as X increases, Y decreases (an inverse relationship).

C. Monomial: Incorrect because a monomial is an algebraic expression with a single term, not a statistical classification for correlation.

D. Single alignment: Incorrect because this is a fabricated term and is not recognized in statistical correlation analysis.

1. Montgomery, D. C., & Runger, G. C. (2014). Applied Statistics and Probability for Engineers (6th ed.). John Wiley & Sons. (Section 11-8, Correlation, pp. 424-426).

2. MIT OpenCourseWare. (2014). Introduction to Probability and Statistics. Massachusetts Institute of Technology. (Lecture 14: Correlation and Regression).

A full factorial design with 5 factors at 2 levels consists of $2^5 = 32$ corner points (experimental runs). Since the design includes 2 replicates for each corner point and no center points, the total number of experimental runs is calculated by multiplying the number of corner points by the number of replicates. Therefore, $32 \times 2 = 64$ total experimental runs.

A. 10 is incorrect because it does not correspond to any standard $2^k$ factorial design calculation for 5 factors.

B. 128 is incorrect; this would be the number of runs for a 7-factor full factorial design ($2^7$) or a 5-factor design with 4 replicates.

C. 256 is incorrect; this represents an 8-factor full factorial design ($2^8$) without replicates.

- Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). John Wiley & Sons. Section 6.2, p. 234.

- NIST/SEMATECH e-Handbook of Statistical Methods, Section 5.3.3.3. "Full Factorial Designs".

Design of Experiments (DOE) is a core statistical tool belonging to the Six Sigma methodology, specifically utilized in the Improve phase of DMAIC to optimize processes, model interactions, and reduce variation. The Lean toolbox, conversely, focuses on eliminating waste and improving process flow using tools like Mistake Proofing (Poka-Yoke), Visual Factory (5S), and Inventory Management (Kanban/Just-In-Time).

A: Mistake Proofing (Poka-Yoke) is a fundamental Lean tool used to prevent human or mechanical errors from becoming defects.

B: Visual Factory is a Lean concept that uses visual indicators to communicate information and expose abnormalities instantly on the shop floor.

D: Inventory Management, specifically through Just-In-Time (JIT) and Kanban pull systems, is a primary pillar of Lean manufacturing.

George, M. L. (2002). Lean Six Sigma: Combining Six Sigma Quality with Lean Production Speed. McGraw-Hill. (Chapter 4: The Lean Enterprise, pp. 65-70).

The standard process Z score measures the distance between the specification limit and the process mean in terms of standard deviation units. Given an Upper Specification Limit ($\text{USL}$) of $2,800, a mean ($\mu$) of $2,240, and a standard deviation ($\sigma$) of $120, the Z-value is computed as:

$$Z = \frac{\text{USL} - \mu}{\sigma} = \frac{2,800 - 2,240}{120} = \frac{560}{120} = 4.67$$

A: 2.33 results from incorrectly doubling the standard deviation divisor or miscalculating the specification margin.

C: 6.48 is a mathematical error not matching the standard score ratio $(2800 - 2240) / 120$.

D: 8.28 results from incorrectly dividing by the standard error of the mean instead of the sample standard deviation.

- Breyfogle, F. W. (2003). Implementing Six Sigma: Smarter Solutions Using Statistical Methods (2nd ed.). Wiley. Chapter 12: Process Capability and Z-value, pp. 185–189. https://doi.org/10.1002/9781118320495

- Pyzdek, T., & Keller, P. (2014). The Six Sigma Handbook (4th ed.). McGraw-Hill Education. Chapter 9: Process Capability, pp. 335–340.

A foundational concept of Lean, famously articulated by Taiichi Ohno, is compressing the lead time across the end-to-end value stream. The Order Production Cycle (or Order-to-Cash cycle) measures the elapsed time from the exact moment a customer order is received to the point payment is collected. Removing non-value-added wastes along this pathway streamlines the process, shortens lead times, and improves cash flow.

A. Shift start represents an operational working boundary, not the customer-driven order trigger for the value stream.

B. Product development covers initial product design and engineering, which occurs prior to the execution of customer order fulfillment.

D. New fiscal year is an accounting timeline and does not reflect operational order-to-cash lead times.

1. Ohno, T. (1988). Toyota Production System: Beyond Large-Scale Production. Productivity Press, Chapter 1: "Starting from Need", p. 9.

2. Womack, J. P., & Jones, D. T. (2003). Lean Thinking: Banish Waste and Create Wealth in Your Corporation. Free Press, Chapter 1, pp. 15-26.

Key Performance Indicators (KPIs) and business metrics quantify process performance, efficiency, quality, and operational resource usage. Cycle Time measures throughput speed and efficiency, Defects measure process output quality and error rate, Number of Units Reworked measures waste and non-value-added activity rate, and Labor Hours measure resource effort and operational input. Because all listed items represent standard operational metrics and KPIs used in Lean Six Sigma to monitor and evaluate overall process health, option E is the correct answer.

A: Cycle Time is a key efficiency metric, but options B, C, and D are also valid business metrics/KPIs.

B: Defects measure process failure rate and quality performance, but options A, C, and D are also valid business metrics/KPIs.

C: Number of Units Reworked measures process waste, but options A, B, and D are also valid business metrics/KPIs.

D: Labor Hours measure resource input and cost, but options A, B, and C are also valid business metrics/KPIs.

1. ISO 13053-1:2011 Quantitative methods in process improvement — Six Sigma — Part 1: DMAIC methodology, Section 6.4 (Process performance metrics).

2. Pyzdek, T. & Keller, P. (2014). The Six Sigma Handbook, 4th ed., McGraw-Hill Education, Chapter 6: Project Selection and Performance Metrics, pp. 125-130.

3. MIT OpenCourseWare, "16.852J: Integration of Lean Enterprise System Design", Lecture 4: Lean Enterprise Performance Metrics.