ASQ CQE Certification Exam Syllabus

I. Management and Leadership (18 Questions)

1. Strategic planning
- Identify and define top management’s responsibility for the QMS, including establishing policies and objectives, setting organization-wide goals, and supporting quality initiatives. (Apply)

2. Deployment techniques
- Define, describe, and use various deployment tools in support of the QMS such as:
a. Benchmarking - Define the concept of benchmarking and why it may be used. (Remember)
b. Stakeholder - Define, describe, and use stakeholder identification and analysis. (Apply)
c. Performance - Define, describe, and use performance measurement tools. (Apply)
d. Project management - Define, describe, and use project management tools, including PERT charts, Gantt charts, critical path method (CPM), and resource allocation. (Apply)

3. Quality information system (QIS)
- Identify and describe the basic elements of a QIS, including who will contribute data, the kind of data to be managed, who will have access to the data, the level of flexibility for future information needs, and data analysis. (Understand)

1. Roles and responsibilities
- Describe the facilitator’s roles and responsibilities on a team. (Understand)

2. Facilitation tools
- Apply various tools used with teams, including brainstorming, nominal group technique, conflict resolution, and force-field analysis. (Apply)

1. Techniques
- Apply various supplier management techniques, including supplier qualification, certification, and evaluation. (Apply)

2. Improvement
- Analyze supplier ratings and performance improvement results. (Analyze)

3. Risk
- Understand business continuity, resiliency, and contingency planning. (Understand)

II. The Quality System (16 Questions)

1. Basic elements
- Interpret the basic elements of a quality system, including planning, control, and improvement, from product and process design through quality cost systems and audit programs. (Evaluate)

2. Design
- Analyze the design and alignment of interrelated processes to the strategic plan and core processes. (Analyze)

1. Document components
- Identify and describe quality system documentation components, including quality policies and procedures to support the system. (Understand)

2. Document control
- Evaluate configuration management, maintenance, and document control to manage work instructions and quality records. (Evaluate)

1. Types of audits
- Describe and distinguish between various types of quality audits such as product, process, management (system), registration (certification), compliance (regulatory), first, second, and third party. (Apply)

2. Roles and responsibilities in audits
- Identify and define roles and responsibilities for audit participants such as audit team (leader and members), client, and auditee. (Understand)

3. Audit planning and implementation
- Describe and apply the stages of a quality audit, from audit planning through conducting the audit. (Apply)

4. Audit reporting and follow-up
- Apply the steps of audit reporting and follow-up, including the need to verify corrective action. (Apply)

III. Product, Process, and Service Design (23 Questions)

1. Inputs
- Translate design inputs such as customer needs, regulatory requirements, and risk assessment into robust design using techniques such as failure mode and effects analysis (FMEA), quality function deployment (QFD), Design for X (DFX), and Design for Six Sigma (DFSS). (Analyze)

2. Review
- Identify and apply common elements of the design review process, including roles and responsibilities of participants. (Apply)

1. Predictive and preventive maintenance tools
- Describe and apply the tools and techniques used to maintain and improve process and product reliability. (Apply)

2. Reliability and maintainability indices
- Review and analyze indices such as MTTF, MTBF, MTTR, availability, and failure rate. (Analyze)

3. Reliability models
- Identify, define, and distinguish between the basic elements of reliability models such as exponential, Weibull, and bathtub curve. (Apply)

4. Reliability/Safety/Hazard Assessment Tools
- Define, construct, and interpret the results of failure mode and effects analysis (FMEA), failure mode, effects, and criticality analysis (FMECA), and fault tree analysis (FTA). (Evaluate)

IV. Product and Process Control (25 Questions)

1. Material identification, status, and traceability
- Define and distinguish between these concepts, and describe methods for applying them in various situations. (Analyze)

2. Material segregation
- Describe material segregation and its importance, and evaluate appropriate methods for applying it in various situations. (Evaluate)

3. Material classification
- Classify product and process defects and nonconformities. (Evaluate)

4. Material review board
- Describe the purpose and function of an MRB and evaluate nonconforming product or material to make a disposition decision in various situations. (Evaluate)

1. Sampling concepts
- Interpret the concepts of producer and consumer risk and related terms, including operating characteristic (OC) curves, acceptable quality limit (AQL), lot tolerance percent defective (LTPD), average outgoing quality (AOQ), and average outgoing quality limit (AOQL). (Analyze)

2. Sampling standards and plans
- Identify, interpret, and apply ANSI/ASQ Z1.4 and Z1.9 standards for attributes and variables sampling. Identify and distinguish between single, double, multiple, sequential, and continuous sampling methods. Identify the characteristics of Dodge-Romig sampling tables and when they should be used. (Analyze)

3. Sample integrity
- Identify and apply techniques for establishing and maintaining sample integrity. (Apply)

1. Measurement tools
- Select and describe appropriate uses of inspection tools such as gage blocks, calipers, micrometers, and optical comparators. (Analyze)

2. Destructive and nondestructive tests
- Identify when destructive and nondestructive measurement test methods should be used and apply the methods appropriately. (Apply)

V. Continuous Improvement (27 Questions)

VI. Quantitative Methods and Tools (36 Questions)

1. Types of data
- Define, classify, and compare discrete (attributes) and continuous (variables) data. (Apply)

2. Measurement scales
- Define and describe nominal, ordinal, interval, and ratio scales. (Understand)

3. Data collection methods
- Describe various methods for collecting data, including tally or check sheets, data coding, and automatic gaging and identify the strengths and weaknesses of the methods. (Apply)

4. Data accuracy and integrity
- Apply techniques that ensure data accuracy and integrity, and identify factors that can influence data accuracy such as source/resource issues, flexibility, versatility, inconsistency, inappropriate interpretation of data values, and redundancy. (Apply)

5. Descriptive statistics
- Describe, calculate, and interpret measures of central tendency and dispersion (central limit theorem), and construct and interpret frequency distributions, including simple, categorical, grouped, ungrouped, and cumulative. (Evaluate)

6. Graphical methods for depicting relationships
- Construct, apply, and interpret diagrams and charts such as stem-and-leaf plots, and box-and-whisker plots. (Note: Scatter diagrams are covered in V.A.) (Analyze)

7. Graphical methods for depicting distributions
- Construct, apply, and interpret diagrams such as normal and non-normal probability plots.(Note: Histograms are covered in V.A.) (Analyze)

1. Terminology
- Define and apply quantitative terms, including population, parameter, sample, statistic, random sampling, and expected value. (Analyze)

2. Drawing statistical conclusions
- Distinguish between numeric and analytical studies. Assess the validity of statistical conclusions by analyzing the assumptions used and the robustness of the technique used. (Evaluate)

3. Probability terms and concepts
- Describe concepts such as independence, mutually exclusive, multiplication rules, complementary probability, and joint occurrence of events. (Understand)

1. Continuous distributions
- Define and distinguish between these distributions such as normal, uniform, bivariate normal, exponential, lognormal, Weibull, chi square, Student’s t, and F. (Analyze)

2. Discrete distributions
- Define and distinguish between these distributions such as binomial, Poisson, hypergeometric, and multinomial. (Analyze)

1. Point estimates and confidence intervals
- Define, describe, and assess the efficiency and bias of estimators. Calculate and interpret standard error, tolerance intervals and confidence intervals. (Evaluate)

2. Hypothesis testing
- Define, interpret, and apply hypothesis tests for means, variances, and proportions. Apply and interpret the concepts of significance level, power, and type I and type II errors. Define and distinguish between statistical and practical significance. (Evaluate)

3. Paired-comparison tests
- Define and use paired-comparison (parametric) hypothesis tests and interpret the results. (Apply)

4. Goodness-of-fit tests
- Define chi square and other goodness-of-fit tests and understand the results. (Understand)

5. Analysis of variance (ANOVA)
- Define and use ANOVAs and interpret the results. (Analyze)

6. Contingency tables
- Define and use contingency tables to evaluate statistical significance. (Apply)

1. Linear regression
- Calculate the regression equation for simple regressions and least squares estimates. Construct and interpret hypothesis tests for regression statistics. Use linear regression models for estimation and prediction. (Analyze)

2. Simple linear correlation
- Calculate the correlation coefficient and its confidence interval, and construct and interpret a hypothesis test for correlation statistics. (Analyze)

3. Time-series analysis
- Define, describe, and use time- series analysis, including moving average to identify trends and seasonal or cyclical variation. (Apply)

1. Objectives and benefits
- Identify and explain the objectives and benefits of SPC. (Understand)

2. Common and special causes
- Describe, identify, and distinguish between these types of causes. (Analyze)

3. Selection of variable
- Identify and select characteristics for monitoring by control chart. (Analyze)

4. Rational subgrouping
- Define and apply the principles of rational subgrouping. (Apply)

5. Control charts
- Identify, select, construct, and use various control charts, including X-R, X-s, individuals and moving range (ImR or XmR), moving average and moving range (MamR), p, np, c, and u. (Analyze)

6. Control chart analysis
- Read and interpret control charts and use rules for determining statistical control. (Evaluate)

7. Pre-control charts
- Define and describe these charts and how they differ from other control charts. (Understand)

8. Short-run SPC
- Identify and define short-run SPC rules. (Understand)

1. Process capability studies
- Define, describe, calculate, and use process capability studies, including identifying characteristics, specifications and tolerances, developing sampling plans for such studies, and establishing statistical control. (Analyze)

2. Process performance vs. specifications
- Distinguish between natural process limits and specification limits, and calculate percent defective, defects per million opportunities (DPMO), and parts per million (PPM). (Analyze)

3. Process capability indices
- Define, select, and calculate Cp, Cpk, Cpm, and Cr, and evaluate process capability. (Evaluate)

4. Process performance indices
- Define, select, and calculate Pp and Ppk, and evaluate process performance. (Evaluate)

1. Terminology
- Define terms such as dependent and independent variables, factors, levels, response, treatment, error, and replication. (Understand)

2. Planning and organizing experiments
- Identify the basic elements of designed experiments, including determining the experiment objective, selecting factors, responses, and measurement methods, and choosing the appropriate design. (Analyze)

3. Design principles
- Define and apply the principles of power and sample size, balance, replication, order, efficiency, randomization, blocking, interaction, and confounding. (Apply)

4. One-factor experiments
- Construct one-factor experiments such as completely randomized, randomized block, and Latin square designs, and use computational and graphical methods to analyze the significance of results. (Analyze)

5. Full-factorial experiments
- Construct full-factorial designs and use computational and graphical methods to analyze the significance of results. (Analyze)

6. Two-level fractional factorial experiments
- Construct two-level fractional factorial designs and apply computational and graphical methods to analyze the significance of results. (Analyze)

VII. Risk Management (15 Questions)

1. Planning and oversight
- Understand identification, planning, prioritization, and oversight of risk. (Understand)

2. Metrics
- Identify and apply evaluation metrics. (Apply)

3. Mitigation planning
- Apply and interpret risk mitigation plan. (Evaluate)

1. Identification and documentation
- Identify and document risks, gaps, and controls. (Analyze)

2. Auditing and testing
- Apply auditing techniques and testing of controls. (Evaluate)