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ASQ CQE : Quality Engineer Exam

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Exam Number : CQE
Exam Name : Quality Engineer
Vendor Name : ASQ
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Topics in this body of knowledge (BoK) include subtext explanations and the cognitive level at which the questions will be written. This information will provide useful guidance for both the test Development Committee and the candidate preparing to take the exam. The subtext is not intended to limit the subject matter or be all-inclusive of that material that will be covered in the exam. It is meant to clarify the type of content that will be included on the exam. The descriptor in parentheses at the end of each entry refers to the maximum cognitive level at which the subject will be tested. A complete description of cognitive levels is provided at the end of this document

I. Management and Leadership (18 Questions) A. Quality Philosophies and FoundationsDescribe continuous improvement tools, including lean, Six Sigma, theory of constraints, statistical process control (SPC), and total quality management, and understand how modern quality has evolved from quality control through statistical process control (SPC) to total quality management and leadership principles (including Demings 14 points). (Understand)B. The Quality Management System (QMS)1. Strategic planningIdentify and define top managements 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)

C. ASQ Code of Ethics for Professional ConductDetermine appropriate behavior in situations requiring ethical decisions. (Evaluate)D. Leadership Principles and TechniquesAnalyze various principles and techniques for developing and organizing teams and leading quality initiatives. (Analyze)E. Facilitation Principles and Techniques1. Roles and responsibilitiesDescribe the facilitators roles and responsibilities on a team. (Understand)2. Facilitation toolsApply various tools used with teams, including brainstorming, nominal group technique, conflict resolution, and force-field analysis. (Apply)F. Communication SkillsIdentify specific communication methods that are used for delivering information and messages in a variety of situations across all levels of the organization. (Analyze)G. Customer RelationsDefine, apply, and analyze the results of customer relation tools such as quality function deployment (QFD) and customer satisfaction surveys. (Analyze)H. provider Management1. TechniquesApply various provider management techniques, including provider qualification, certification, and evaluation. (Apply)2. ImprovementAnalyze provider ratings and performance improvement results. (Analyze)3. RiskUnderstand business continuity, resiliency, and contingency planning. (Understand)

I. Barriers to Quality ImprovementIdentify barriers to quality improvement, analyze their causes and impact, and implement methods for improvement. (Analyze)II. The Quality System (16 Questions)A. Elements of the Quality System1. Basic elementsInterpret 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. DesignAnalyze the design and alignment of interrelated processes to the strategic plan and core processes. (Analyze)B. Documentation of the Quality System1. Document componentsIdentify and describe quality system documentation components, including quality policies and procedures to support the system. (Understand)2. Document controlEvaluate configuration management, maintenance, and document control to manage work instructions and quality records. (Evaluate)C. Quality Standards and Other GuidelinesApply national and international standards and other requirements and guidelines, including the Malcolm Baldrige National Quality Award (MBNQA), and describe key points of the ISO 9000 series of standards. (Note: Industry-specific standards will not be tested.) (Apply)

D. Quality Audits1. Types of auditsDescribe 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 auditsIdentify and define roles and responsibilities for audit participants such as audit team (leader and members), client, and auditee. (Understand)3. Audit planning and implementationDescribe and apply the stages of a quality audit, from audit planning through conducting the audit. (Apply)4. Audit reporting and follow-upApply the steps of audit reporting and follow-up, including the need to verify corrective action. (Apply)E. Cost of Quality (COQ)Identify and apply COQ concepts, including cost categorization, data collection, reporting, and interpreting results. (Analyze)F. Quality TrainingIdentify and apply key elements of a training program, including conducting a needs analysis, developing curricula and materials, and determining the programs effectiveness. (Apply)III. Product, Process, and Service Design (23 Questions)A. Classification of Quality CharacteristicsDefine, interpret, and classify quality characteristics for new and existing products, processes, and services. (Note: The classification of defects is covered in IV.B.3.) (Evaluate)

B. Design Inputs and Review1. InputsTranslate 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. ReviewIdentify and apply common elements of the design review process, including roles and responsibilities of participants. (Apply)C. Technical Drawings and SpecificationsInterpret specification requirements in relation to product and process characteristics and technical drawings, including characteristics such as views, title blocks, dimensioning and tolerancing, and GD&T symbols. (Evaluate)D. Verification and ValidationInterpret the results of evaluations and tests used to verify and validate the design of products, processes and services, such as installation qualification (IQ), operational qualification (OQ), and process qualification (PQ). (Evaluate)E. Reliability and Maintainability1. Predictive and preventive maintenance toolsDescribe and apply the tools and techniques used to maintain and Boost process and product reliability. (Apply)2. Reliability and maintainability indicesReview and analyze indices such as MTTF, MTBF, MTTR, availability, and failure rate. (Analyze)3. Reliability modelsIdentify, define, and distinguish between the basic elements of reliability models such as exponential, Weibull, and bathtub curve. (Apply)

4.Reliability/Safety/Hazard Assessment ToolsDefine, 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)A. MethodsImplement product and process control methods such as control plan development, critical control point identification, and work instruction development and validation. (Analyze)B. Material Control1. Material identification, status, and traceabilityDefine and distinguish between these concepts, and describe methods for applying them in various situations. (Analyze)2. Material segregationDescribe material segregation and its importance, and evaluate appropriate methods for applying it in various situations. (Evaluate)3. Material classificationClassify product and process defects and nonconformities. (Evaluate) 4. Material review boardDescribe the purpose and function of an MRB and evaluate nonconforming product or material to make a disposition decision in various situations. (Evaluate)C. Acceptance Sampling1. Sampling conceptsInterpret 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. trial integrityIdentify and apply techniques for establishing and maintaining trial integrity. (Apply)D. Measurement and Test1. Measurement toolsSelect and describe appropriate uses of inspection tools such as gage blocks, calipers, micrometers, and optical comparators. (Analyze)2. Destructive and nondestructive testsIdentify when destructive and nondestructive measurement test methods should be used and apply the methods appropriately. (Apply)E. MetrologyApply metrology techniques such as calibration, traceability to calibration standards, measurement error and its sources, and control and maintenance of measurement standards and devices. (Analyze)F. Measurement System Analysis (MSA)Calculate, analyze, and interpret repeatability and reproducibility (gage R&R) studies, measurement correlation, capability, bias, linearity, precision, stability and accuracy, as well as related MSA quantitative and graphical methods. (Evaluate)

V. Continuous Improvement (27 Questions)A. Quality Control ToolsSelect, construct, apply, and interpret the following quality control tools:1. Flowcharts2. Pareto charts3. Cause and effect diagrams4. Control charts5. Check sheets6. Scatter diagrams7. Histograms (Analyze)B. Quality Management and Planning ToolsSelect, construct, apply, and interpret the following quality management and planning tools:1. Affinity diagrams and force field analysis2. Tree diagrams3. Process decision program charts (PDPC)4. Matrix diagrams5. Interrelationship digraphs6. Prioritization matrices7. Activity network diagrams (Analyze)C. Continuous Improvement MethodologiesDefine, describe, and apply the following continuous improvement methodologies:1. Total quality management (TQM)2. Kaizen3. Plan-do-check-act (PDCA)4. Six Sigma5. Theory of constraints (ToC) (Evaluate)D. Lean toolsDefine, describe, and apply the following lean tools:1. 5S2. Value stream mapping3. Kanban4. Visual control5. Waste (Muda)6. Standardized work7. Takt time8. Single minute exchange of die (SMED) (Evaluate)E. Corrective ActionIdentify, describe, and apply elements of the corrective action process, including problem identification, failure analysis, root cause analysis, problem correction, recurrence control, and verification of effectiveness. (Evaluate)F. Preventive ActionIdentify, describe, and apply various preventive action tools such as error proofing/poka-yoke and robust design and analyze their effectiveness. (Evaluate)VI. Quantitative Methods and Tools (36 Questions)A. Collecting and Summarizing Data1. Types of dataDefine, classify, and compare discrete (attributes) and continuous (variables) data. (Apply)2. Measurement scalesDefine 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 statisticsDescribe, 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)B. Quantitative Concepts1. TerminologyDefine and apply quantitative terms, including population, parameter, sample, statistic, random sampling, and expected value. (Analyze)2. Drawing statistical conclusionsDistinguish 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)C. Probability Distributions1. Continuous distributions Define and distinguish between these distributions such as normal, uniform, bivariate normal, exponential, lognormal, Weibull, chi square, Students t, and F. (Analyze)

2. Discrete distributions Define and distinguish between these distributions such as binomial, Poisson, hypergeometric, and multinomial. (Analyze)D. Statistical Decision Making1. Point estimates and confidence intervalsDefine, describe, and assess the efficiency and bias of estimators. Calculate and interpret standard error, tolerance intervals, and confidence intervals. (Evaluate)2. Hypothesis testingDefine, 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 testsDefine 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 tablesDefine and use contingency tables to evaluate statistical significance. (Apply)E. Relationships Between Variables1. Linear regressionCalculate 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 analysisDefine, describe, and use time- series analysis, including moving average to identify trends and seasonal or cyclical variation. (Apply)F. Statistical Process Control (SPC)1. Objectives and benefitsIdentify 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 variableIdentify and select characteristics for monitoring by control chart. (Analyze)4. Rational subgroupingDefine and apply the principles of rational subgrouping. (Apply)5. Control chartsIdentify, 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 analysisRead and interpret control charts and use rules for determining statistical control. (Evaluate)7. Pre-control chartsDefine and describe these charts and how they differ from other control charts. (Understand)8. Short-run SPCIdentify and define short-run SPC rules. (Understand)

G. Process and Performance Capability1. 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. specificationsDistinguish 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)H. Design and Analysis of Experiments1. TerminologyDefine terms such as dependent and independent variables, factors, levels, response, treatment, error, and replication. (Understand)2. Planning and organizing experimentsIdentify 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 principlesDefine and apply the principles of power and trial 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 experimentsConstruct two-level fractional factorial designs and apply computational and graphical methods to analyze the significance of results. (Analyze)VII. Risk Management (15 Questions)A. Risk Oversight1. Planning and oversight Understand identification, planning, prioritization, and oversight of risk. (Understand)2. MetricsIdentify and apply evaluation metrics. (Apply)3. Mitigation planningApply and interpret risk mitigation plan. (Evaluate)B. Risk AssessmentApply categorization methods and evaluation tools to assess risk. (Analyze)C. Risk Control1. Identification and documentation Identify and document risks, gaps, and controls. (Analyze)2. Auditing and testingApply auditing techniques and testing of controls. (Evaluate)



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Dr. Mary McShane-Vaughn

Dr. Mary McShane-Vaughn has created and delivered Yellow, green and Black Belt training courses to a whole bunch of scholars, each in-person and on-line. over the past five years she has enthusiastically delivered more than 45 Yellow, eco-friendly and Black Belt lessons for her school and corporate purchasers.

She is at present important at school training companions, a corporation that develops and can provide Lean Six Sigma working towards for enterprises and universities. She additionally serves on the editorial review board for ASQ's Six Sigma forum and is co-creator of The licensed high-quality Inspector instruction manual, and creator of The likelihood guide, both published with the aid of ASQ fine Press.

Dr. McShane-Vaughn is a senior member of the American Society for satisfactory and a member of the American Statistical affiliation and holds ASQ certifications as a Six Sigma Black Belt, best Engineer, and Reliability Engineer.

She served as the Six Sigma Black Belt examination Chair for the American Society for excellent (ASQ) from 2010-2012, and became an examiner for the Georgia Oglethorpe Award, Georgia's equivalent of the national Malcolm Baldrige Award.

in the past, Dr. McShane-Vaughn become a tenured faculty member at Southern Polytechnic State institution in Marietta, Georgia, now Kennesaw State university. For eight years she directed and grew the grasp of Science in high-quality Assurance program and taught facts, statistical quality control, linear regression and design of experiments on-line in the graduate application. Her analysis pursuits include industrial records, powerful experimental design and distance learning course delivery strategies.

before her profession in lecturers, she worked for 15 years as a high quality engineer and statistician within the automotive, scientific equipment manufacturing, client products testing, and salary management industries.

Dr. McShane-Vaughn holds a Ph.D. in Industrial Engineering and an MS in information from the Georgia Institute of know-how, and a B.S. in Industrial Engineering from frequent Motors Institute (now Kettering tuition) in Flint, Michigan. 


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