CQE Certified Quality EngineerExam Questions and Answers

The process performance index (Ppk) measures the performance of a process relative to the specification limits, accounting for the mean and variability of the process. It is an indicator of how well the process can produce output within the specification limits.

References:

Montgomery, D.C. (2009). Introduction to Statistical Quality Control. Wiley.

ASQ. (n.d.). Process Performance (Pp, Ppk). Retrieved from https://asq.org/quality-resources/process-performance

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A system audit evaluates the overall quality management system (QMS) of an organization to ensure it conforms to established standards, such as ISO 9001.

This type of audit examines whether the processes and activities are effectively integrated and implemented to achieve quality objectives.

It focuses on the adequacy and compliance of the entire QMS rather than individual processes or products.

References: ISO 9001 and the ASQ "Quality Audits for Improved Performance" emphasize the role of system audits in assessing conformance to quality programs.

Concurrent engineering is an approach to product development where multiple phases of the design process are carried out simultaneously to reduce time-to-market and improve product quality.

Concurrent engineering is a systematic approach to integrated product development that emphasizes the parallelization of tasks (i.e., performing tasks concurrently), which contrasts with the traditional sequential engineering design method.

The situation described is an example of an unintended consequence. Each module functions as intended individually, but when combined, the overall system's performance is suboptimal. This situation often arises when interactions between modules are not fully considered, leading to unforeseen issues that degrade overall system performance.

When measurements are taken using a reference scale, such as a pair of calipers, the resulting data are referred to as continuous data. Continuous data can take any value within a given range and are measured on a scale that can be subdivided. This type of data is crucial for precise quality control and statistical analysis in manufacturing and engineering.

When establishing a system for the classification of defects, it is crucial to consider the relative seriousness of the defects. This involves evaluating the potential impact of each type of defect on the end-user and the product's performance. The classification typically divides defects into categories such as critical, major, and minor, based on their severity and potential consequences.

References:

"Quality Control Handbook" by J.M. Juran.

ISO 2859-1:1999, "Sampling procedures for inspection by attributes"

The Average Outgoing Quality Limit (AOQL) is a key concept in quality control and inspection plans. It is defined as the maximum average outgoing quality over all possible levels of incoming quality for a given acceptance sampling plan. The AOQL is particularly used in situations where 100% inspection or screening of rejected lots is performed, meaning nonconforming units are identified and replaced. This ensures that the outgoing quality is controlled even if the incoming quality fluctuates.

References:

"Introduction to Statistical Quality Control" by Douglas C. Montgomery.

ASQ (American Society for Quality) Glossary: AOQL

When a potential solution, such as adding reinforcements to packaging, is identified, the most appropriate action is to pilot the solution. Piloting allows the company to test the effectiveness of the solution on a smaller scale before full implementation, ensuring that it resolves the issue without unintended consequences.

Risk management in software quality engineering aims to identify, assess, and mitigate risks that could affect project outcomes. The primary characteristic of effective risk management is that it should be all-inclusive. This means it should encompass all potential risk areas, including technical, project management, resource allocation, and external factors. An all-inclusive approach ensures that no significant risk is overlooked and that comprehensive strategies are in place to manage identified risks effectively.References:

Software Quality Assurance: Principles and Practice by Nina S. Godbole.

ASQ Software Quality Engineer Handbook.

When an auditor finds a major discrepancy during a pre-award audit of a new supplier, the appropriate action is to include the discrepancy in the final report. This documentation is essential for transparency and for the organization to make informed decisions regarding the supplier. While other actions like verifying corrective actions and investigating the cause are important, they are typically follow-up steps after the discrepancy has been officially recorded.

A product that exhibits a constant failure rate typically follows an exponential distribution for the failure rate. The exponential distribution is often used to model the time between failures in systems with a constant hazard rate, meaning the failure rate does not change over time.References:

Reliability Engineering by Elsayed A. Elsayed.

ASQ Quality Press: The Certified Reliability Engineer Handbook.

The expected number of rejects per sample can be calculated using the reject rate and the sample size. Given a reject rate of 6% (or 0.06) and a sample size of 5:

Expected number of rejects per sample = 0.06 * 5 = 0.3

References:

Montgomery, D.C. (2009). Introduction to Statistical Quality Control. Wiley.

ASQ. (n.d.). Basic Quality Tools. Retrieved from https://asq.org/quality-resources/basic-quality-tools

To ensure traceability from design and production through to end-user receipt and use, a company must develop a robust product identification system. This system involves assigning unique identifiers to each product or batch, which can be tracked throughout the entire supply chain. This allows for effective tracking of production history, quality control, and accountability in the event of product issues or recalls.

References:

"Traceability in the Food and Feed Chain" by IFSQN.

ISO 9001:2015, Quality Management Systems – Requirements

Management commitment is the most crucial aspect of a successful quality improvement effort. Without the active involvement and support of management, quality initiatives are less likely to receive the necessary resources, attention, and prioritization. Management commitment includes setting clear quality goals, providing the required resources, and leading by example to foster a culture of continuous improvement. This ensures that quality improvement is integrated into the organizational strategy and receives ongoing support and reinforcement.

References:

Juran, J.M., & Gryna, F.M. (1993). Quality Planning and Analysis: From Product Development through Use. McGraw-Hill.

Crosby, P.B. (1979). Quality is Free. McGraw-Hill.

Bilateral tolerance means that the allowable deviation is specified in both directions from the nominal dimension.

In the provided drawing, the hole dimension is given with an equal tolerance range on both sides, indicating bilateral tolerance.

References: "Engineering Drawing and Design" by David A. Madsen and "Geometric Dimensioning and Tolerancing" by Alex Krulikowski discuss bilateral tolerances and theirrepresentation in technical drawings.

One of the primary advantages of a ship-to-stock program is that it reduces dock-to-line time. This program streamlines the process by allowing materials to be delivered directly to the production line without the need for incoming inspection, thus speeding up the supply chain and reducinginventory holding costs.References:

ASQ Quality Press: The Certified Quality Engineer Handbook.

Lean Supply Chain and Logistics Management by Paul Myerson.

In value stream analysis, inspection is typically classified as non-value added. This is because inspection does not directly transform the product or add value from the customer's perspective. Instead, it is an activity that checks for defects or issues, which ideally should be prevented by improving the processes.

References:

Rother, M., & Shook, J. (1999). Learning to See: Value Stream Mapping to Add Value and Eliminate MUDA. Lean Enterprise Institute.

Liker, J.K. (2004). The Toyota Way: 14 Management Principles from the World's Greatest Manufacturer. McGraw-Hill.

The fishbone diagram, also known as the Ishikawa or cause-and-effect diagram, is used to identify and evaluate all possible causes of a problem.

It visually organizes potential causes into categories, helping to isolate the most probable ones.

This tool is effective for brainstorming and systematically analyzing the root causes of a quality issue.

References: ASQ's "Quality Toolbox" and Ishikawa's original works on cause-and-effect diagrams.

When nonconforming items are found, the first action should be to identify and label them clearly. This prevents further processing or use and ensures proper handling of these items. Identification is critical before taking any further actions such as retesting, destruction, or returning to the supplier. Reference: ISO 9001:2015, Clause 8.7 - Control of Nonconforming Outputs, which specifies the need for clear identification and segregation of nonconforming products.

A material review board (MRB) gets its authority to act from executive management. The MRB is typically composed of representatives from various departments, including engineering, quality, and production, and is responsible for reviewing and making decisions on non-conforming materials. The authority given by executive management ensures that the MRB has the power to enforce quality standards and make necessary decisions.

Quality planning focuses on identifying and meeting the needs of the customers. It involves defining quality standards and determining how to achieve them to ensure customer satisfaction.

To convince management of the need for a quality improvement program, it is most effective to present the size of the problem in terms of potential savings and increased profit. Management is often driven by financial metrics, so quantifying the impact of quality issues and the benefits of improvements in monetary terms will be persuasive. Reference: "Juran's Quality Handbook" by Joseph M. Juran, which emphasizes presenting business cases in financial terms to gain management support for quality initiatives.

When several units from a random sample are found to be defective, the immediate next action should be to segregate the defective units. This step is crucial to prevent defective units from being mixed with non-defective units, ensuring that they do not reach customers or proceed further in the production process. Segregating defective units helps in identifying the extent of the issue and facilitates further investigation and corrective actions.

The appropriate number of class intervals for the construction of a histogram can be estimated using Sturges' rule, which is given by k=1+3.322log⁡10(n)k = 1 + 3.322 \log_{10}(n)k=1+3.322log10​(n), where nnn is the number of observations. For 36 observations:

k=1+3.322log⁡10(36)≈1+3.322×1.556≈6.17k = 1 + 3.322 \log_{10}(36) \approx 1 + 3.322 \times 1.556 \approx 6.17k=1+3.322log10​(36)≈1+3.322×1.556≈6.17

This suggests around 6 intervals, but in practice, the number of intervals often rounded up, hence the appropriate number of class intervals would be 8 for better representation of the data. References:

Introduction to Probability and Statistics for Engineers and Scientists by Sheldon M. Ross.

ASQ Quality Press: The Certified Quality Engineer Handbook.

The Malcolm Baldrige framework evaluates an organization's approach and results. It assesses how the organization approaches various aspects of quality and performance management and the results achieved through these approaches. This comprehensive evaluation helps organizations understand their strengths and areas for improvement. Reference: "The Malcolm Baldrige National Quality Award Criteria for Performance Excellence," which outlines the evaluation criteria focusing on approach and results.

Risk describes the combination of the severity and probability of occurrence of harm. In the context of quality management, risk assessment involves evaluating both how severe the potential harm could be and the likelihood of it occurring, to manage and mitigate potential failures effectively.References:

Failure Mode and Effect Analysis (FMEA) by ASQ Quality Press.

ISO 31000: Risk Management Guidelines.

Management philosophy is crucial in shaping the culture of an organization. It defines the values, beliefs, and principles that guide the behavior of its members. A strong, coherent management philosophy provides direction, motivates employees, and fosters a sense of identity and purpose within the organization. It influences decision-making, leadership styles, and the overall work environment.

The constant failure rate per hour is calculated as the inverse of the mean time between failures (MTBF). Given an MTBF of 200 hours: Failure rate (λ) = 1 / MTBF = 1 / 200 = 0.005

A critical design review (CDR) is an assessment of the product or system design's maturity, ensuring that it meets the specified requirements and is ready to proceed to the next development stage. It evaluates design performance, reliability, and readiness for production.

References:

INCOSE. (2015). Systems Engineering Handbook: A Guide for System Life Cycle Processes and Activities. Wiley.

NASA. (2016). Systems Engineering Handbook. NASA SP-2016-6105 Rev 2.

A scatter diagram is used to assess the relationship between two variables. In this case, it can be used to analyze the relationship between storage temperature and the overall length of the metalcomponent. A scatter diagram helps in visualizing any correlation between the two variables. Reference: "The Quality Toolbox" by Nancy R. Tague, which provides descriptions and uses for various quality tools including scatter diagrams.

Process capability analysis evaluates how well a process can produce output within specified limits.

It measures the inherent variability of a process relative to its specification limits.

This analysis is valuable for comparing the capabilities of different processes or equipment to ensure they meet required specifications.

It helps in selecting the most appropriate process or equipment by providing quantitative data on their performance.

References: ASQ's "Certified Quality Engineer Handbook" outlines the use of process capability analysis for comparing processes and equipment.

The effectiveness of corrective action can best be assessed by measuring the results of the corrective action. This involves evaluating whether the action taken has successfully addressed theroot cause of the problem and has led to a measurable improvement in the quality metrics or process performance.References:

ASQ Quality Press: The Certified Quality Engineer Handbook.

Total Quality Management by Dale H. Besterfield.

The primary purpose of the Material Review Board (MRB) is to review and determine the appropriate disposition of nonconforming products. The MRB evaluates the nonconformities, decides whether the products can be reworked, used as-is, or must be scrapped, and ensures that corrective actions are implemented to prevent recurrence.

References:

"The Certified Quality Engineer Handbook" by Connie M. Borror.

ASQ Glossary: Material Review Board (MRB)

A probability plot is used to evaluate whether a data set follows a specified distribution, such as the normal distribution. By plotting the data against the expected values of the distribution, one can visually assess normality.

References:

Montgomery, D.C., & Runger, G.C. (2010). Applied Statistics and Probability for Engineers.Wiley.

NIST/SEMATECH. (n.d.). e-Handbook of Statistical Methods. Retrieved fromhttps://www.itl.nist.gov/div898/handbook/

The Student's t statistic is calculated as follows:

t = (X̄ - μ) / (s / √n)

Given:

Sample mean (X̄) = 515

Population mean (μ) = 500

Sample standard deviation (s) = 9

Sample size (n) = 6

t = (515 - 500) / (9 / √6) = 15 / (9 / 2.45) ≈ 3.73

References:

Montgomery, D.C., & Runger, G.C. (2010). Applied Statistics and Probability for Engineers.Wiley.

NIST/SEMATECH. (n.d.). e-Handbook of Statistical Methods. Retrieved fromhttps://www.itl.nist.gov/div898/handbook/

The diagram shown is typical of an interaction plot used in the analysis of designed experiments.

Confounded:

Confounding occurs when the effects of two factors cannot be separated. The diagram does not indicate this.

Replicated:

Replication refers to repeating the experiment or conditions multiple times to ensure reliability, not depicted here.

Show Randomization:

Randomization refers to the random assignment of treatments to experimental units. The plot does not indicate this.

Show Interaction:

Interaction occurs when the effect of one factor depends on the level of another factor.

The crossing lines in the plot indicate that the response to Factor A changes depending on the level of Factor B, demonstrating an interaction between the two factors.

References: Design of experiments (DOE) and statistical analysis texts.

In the provided drawing, the symbol marked "A" is being used to indicate a datum. A datum is a reference point, line, or surface used as a basis for measurement and to establish the location or orientation of other features. It serves as a starting point for dimensional control and ensures consistency in the manufacturing process.

To find the probability of at least one car starting on a cold morning, we can use the complement rule.

Determine the probability of one car not starting:

Probability of a car starting: P(start)=0.6P(\text{start}) = 0.6P(start)=0.6

Probability of a car not starting: P(not start)=1−0.6=0.4P(\text{not start}) = 1 - 0.6 = 0.4P(not start)=1−0.6=0.4

Determine the probability of neither car starting:

Since the cars are independent, the probability of both cars not starting is: P(both not start)=0.4×0.4=0.16P(\text{both not start}) = 0.4 \times 0.4 = 0.16P(both not start)=0.4×0.4=0.16

Determine the probability of at least one car starting:

P(at least one starts)=1−P(both not start)=1−0.16=0.84P(\text{at least one starts}) = 1 - P(\text{both not start}) = 1 - 0.16 = 0.84P(at least one starts)=1−P(both not start)=1−0.16=0.84

References: Basic principles of probability and complement rule from standard probability texts.

In factorial design experiments, fractionating involves using a subset of the full set of experimental runs. A 242^424 full factorial experiment involves 16 runs, and fractionating this to 24−12^{4-1}24−1 results in 8 runs.

90% Fraction:

Incorrect, as this would imply a fractional design close to the full factorial, but it is not standard terminology.

75% Fraction:

The correct answer as 24−12^{4-1}24−1 implies a design that uses 816\frac{8}{16}168​ or 50% of the full factorial runs. However, in common terminology, a fractionated design resulting in fewer runs (half of the runs) is considered a 50% fraction. Therefore, this fractionation corresponds to a 50% fraction or half fraction.

Fraction:

Too vague, as it does not specify the fraction size.

Fraction:

Duplicates "fraction."

Therefore, the correct fractional reduction is to a 50% fraction, which is commonly used in design of experiments. The proper fraction designation in this case should be 50%, not 75%.

References: Design of experiments (DOE) principles.

In geometric dimensioning and tolerancing (GD&T), the symbol shown in the image is used to indicate a datum target point. This symbol is employed to designate specific locations on a part that are used as reference points for measurements. Datum targets are essential for ensuring accurate and repeatable measurements, particularly in complex assemblies where precision is crucial.

Datum Target Point: A specific point on a part that serves as a reference for measurement or manufacturing. Datum target points are critical for establishing a reference frame for the part's geometry.

References:

ASME Y14.5-2009 - Geometric Dimensioning and Tolerancing Standard.

Foster, L. W. (2010). Geometric Dimensioning and Tolerancing for Mechanical Design 2/E. McGraw-Hill Education.