The Certified Quality Process Analyst is a paraprofessional who, in support of and under the direction of quality engineers or supervisors, analyzes and solves quality problems and is involved in quality improvement projects. A Certified Quality Process Analyst may be a recent graduate or someone with work experience who wants to demonstrate his or her knowledge of quality tools and processes.

Is this the right certification for you?

Here are the requirements and exam specifics for a Quality Process Analyst. If you already know this is the certification you want to pursue, move on to exam preparation.

Education and/or Experience

You must have Two years of work experience, or an Associate’s Degree or Two years of equivalent higher education.

Minimum Expectations for a Certified Quality Process Analyst

I

• Must be willing to subscribe to and follow the ASQ code of ethics;
• Must understand the elements and purpose of quality planning, and who contributes to its development;
• Must be able to identify and distinguish the cost of quality categories;
• Must recognize the difference between standards, requirements, and specifications;
• Must understand the need for documentation control, its basic terms and hierarchy;
• Must understand the purpose, elements, and types of audits, and the roles of those involved;
• Must know the types of teams, team-building activities, common team roles, and typical group behaviors;
• Must be able to identify the basic types of training tools and methods used to verify its effectiveness.

II

• Must be able to select, apply and interpret basic quality tools;
• Must be able to define and interpret the plan-do-check-act (PDCA) cycle and continuous improvement models;
• Must understand the concepts of basic quality management tools ;
• Must be able to select and interpret basic project management tools;
• Must know the basic concepts of the Taguchi Loss function;
• Must understand the underlying principles and terminology associated with Lean processes;
• Must understand how benchmarking supports best practices.

III

• Must understand the concepts, terms and calculations of basic descriptive statistics;
• Must know the various classifications of data and collection methods;
• Must understand and distinguish between various sampling characteristics and methods;
• Must be able to distinguish between characteristics of a measurement system;
• Must understand the purpose and appropriate applications of various types of control charts, including their construction and interpretation;
• Must understand the principles of hypothesis testing, including the appropriate use of test statistics;
• Must be able to define basic design of experiment terminology.

IV

• Must understand the relationships and roles of internal/external customers and suppliers, including their impact on products and services;
• Must be able to identify and recognize customer satisfaction data gathering and analysis tools;
• Must be able to identify and understand various validation and qualification methods;
• Must be able to define basic reliability measures and concepts, including failure models;
• Must understand the types of metrics used to assess supplier performance;
• Must be able to understand and apply basic concepts of corrective and preventive action, including verification and validation of effectiveness;
• Must be able to identify and apply the various methods used for material identification, status, and traceability.

Examination

Each certification candidate is required to pass a written examination that consists of multiple choice questions that measure comprehension of the Body of Knowledge. The Certified Quality Process Analyst examination is a one–part, 100–question, four–hour exam and is offered in English.

Examinations are conducted twice a year, in June and December. Examination sites are hosted by local ASQ sections and by international organizations (contact the ASQ Certification Department for international locations). You will be notified approximately two weeks before the examination date of your assigned testing location. Please allow extra time for international mail.

Please Note: The Body of Knowledge for certification is constantly affected by new technologies, policies, and the changing dynamics of manufacturing and service industries. Changed versions of the examination based on the current Body of Knowledge are used at each offering.

Included in this body of knowledge are explanations (subtext) and cognitive levels for each topic or subtopic in the test. These details will be used by the Examination Development Committee as guidelines for writing test questions and are designed to help candidates prepare for the exam by identifying specific content within each topic that can be tested. Except where specified, the subtext is not intended to limit the subject or be all-inclusive of what might be covered in an exam but is intended to clarify how topics are related to the role of the Certified Quality Process Analyst (CQPA). The descriptor in parentheses at the end of each subtext entry refers to the highest cognitive level at which the topic will be tested. A more complete description of cognitive levels is provided at the end of this document.

1. Quality Basics (24 Questions)
   1. ASQ code of ethics
      Identify appropriate behaviors for situations requiring ethical decisions. (Apply)
   2. Quality planning
      Define a quality plan, understand its purpose for the organization as a whole and who in the organization contributes to its development. (Understand)
   3. Cost of quality (COQ)
      Describe and distinguish the classic COQ categories (prevention, appraisal, internal failure, external failure) and apply COQ concepts. (Apply)
   4. Quality standards, requirements, and specifications
      Define and distinguish between quality standards, requirements, and specifications. (Understand)
   5. Documentation systems
      Identify and describe common elements and different types of documentation systems such as configuration management, quality manual, document control, etc. (Understand)
   6. Audits
       
      1. Audit types
         Define and describe various audit types: internal, external, system, product, and process. (Understand)
      2. Audit process
         Describe various elements, including audit preparation, performance, record keeping, and closure. (Understand)
         [NOTE: Corrective action is covered in IV.F.]
      3. Roles and responsibilities
         Identify and define roles and responsibilities of audit participants (lead auditor, audit team member, client, and auditee). (Understand)
   7. Teams
       
      1. Types of teams
         Distinguish between various types of teams such as process improvement, work group, self-managed, temporary/ad hoc, cellular, etc. (Analyze)
      2. Team-building techniques
         Define basic steps in team-building such as introductory meeting for team members to share information about themselves, the use of ice-breaker activities to enhance team membership, the need for developing a common vision and agreement on team objectives, etc. (Apply)
      3. Roles and responsibilities
         Explain the various team roles and responsibilities, such as sponsor, champion, facilitator, team leader, and team member,and responsibilities with regard to various group dynamics, such as recognizing hidden agendas, handling distractions and disruptive behavior, keeping on task, etc. (Understand)
   8. Training components
      Define and describe methods that can be used to train individuals on new or improved procedures and processes, and use various tools to measure the effectiveness of that training, such as feedback from training sessions, end-of-course test results, on-the-job behavior or performance changes, department or area performance improvements, etc. (Understand)
2. Problem Solving and Improvement [23 questions]
   1. Basic quality tools
      Select, apply, and interpret these tools: flow charts, Pareto charts, cause and effect diagrams, check sheets, scatter diagrams, and histograms. (Analyze)
      [NOTE: The application of control charts is covered in section III.E.]
   2. Continuous improvement models
      Define and explain elements of Plan-Do-Check-Act (PDCA), kaizen, and incremental and breakthrough improvement. (Apply)
   3. Basic quality management tools
      Select and apply affinity diagrams, tree diagrams, process decision program charts, matrix diagrams, interrelationship digraphs, prioritization matrices, and activity network diagrams. (Apply)
   4. Project management tools
      Select and interpret scheduling and monitoring tools such as Gantt charts, program evaluation and review technique (PERT), critical path method (CPM), etc. (Analyze)
   5. Taguchi loss function
      Identify and describe Taguchi concepts and techniques such as signal-to-noise ratio, controllable and uncontrollable factors, and robustness. (Understand)
   6. Lean
      Identify and apply lean tools and processes, including set-up reduction (SUR), pull (including just-in-time (JIT) and kanban), 5S, continuous flow manufacturing (CFM), value stream, poka-yoke, and total preventive/predictive maintenance (TPM) to reduce waste in areas of cost, inventory, labor, and distance. (Apply)
   7. Benchmarking
      Define and describe this technique and how it can be used to support best practices. (Understand)
3. Data Analysis [35 questions]
   1. Terms and definitions
      1. Basic statistics
         Define, compute, and interpret mean, median, mode, standard deviation, range, and variance. (Apply)
      2. Basic distributions
         Define and explain frequency distributions (normal, binomial, Poisson, and Weibull) and the characteristics of skewed and bimodal distributions. (Understand)
      3. Probability
         Describe and apply basic terms and concepts (independence, mutual exclusivity, etc.) and perform basic probability calculations. (Apply)
      4. Measurement scales
         Define and apply nominal, ordinal, interval, and ratio measurement scales. (Apply)
   2. Data types and collection methods
      1. Types of data
         Identify, define, and classify continuous (variables) data and discrete (attributes) data, and identify when it is appropriate to convert attributes data to variables measures. (Apply)
      2. Methods for collecting data
         Define and apply methods for collecting data such as using data coding, automatic gaging, etc. (Apply)
   3. Sampling
      1. Characteristics
         Identify and define sampling characteristics such as lot size, sample size, acceptance number, operating characteristic (OC) curve, etc. (Understand)
      2. Sampling methods
         Define and distinguish between various sampling methods such as random, sequential, stratified, fixed sampling, attributes and variables sampling, etc. (Understand)
         [NOTE: Reading sampling tables is not required.]
   4. Measurement terms
      Define and distinguish between accuracy, precision, repeatability, reproducibility, bias, and linearity. (Understand)
   5. Statistical process control (SPC)
      1. Techniques and applications
         Select appropriate control charts for monitoring or analyzing various processes and explain their construction and use. (Apply)
      2. Control limits and specification limits
         Identify and describe different uses of control limits and specification limits. (Understand)
      3. Variables charts
         Identify, select, construct, and interpret - R and - s charts. (Analyze)
      4. Attributes charts
         Identify, select, construct, and interpret p, np, c, and u charts. (Analyze)
      5. Rational subgroups
         Define and describe the principles of rational subgroups. (Understand)
      6. Process capability measures
         Define the prerequisites for measuring capability, and calculate and interpret C_p, C_pk, P_p, and P_pk in various situations. (Analyze)
      7. PRE-control chart
         Define the concept and use of PRE-control charts. (Understand)
      8. Common and special cause variation
         Interpret various control chart patterns (runs, hugging, and trends) to determine process control, and use rules to distinguish between common cause and special cause variation. (Analyze)
      9. Data plotting
         Identify the advantages and limitations of analyzing data visually instead of numerically. (Understand)
   6. Regression and correlation
      Describe how regression and correlation models are used for estimation and prediction. (Apply)
   7. Hypothesis testing
      Determine and calculate confidence intervals using t tests and the z statistic, and determine whether the result is significant. (Analyze)
      [NOTE: The F test is covered in area III.I.]
   8. Design of experiments (DOE)
      Define basic terms such as blocking, randomization, etc. (Remember)
   9. Analysis of variance (ANOVA)
      Define and determine the applicability of ANOVAs. (Understand)
4. Customer-Supplier Relations [18 questions]
   1. Internal and external customers and suppliers
      Define and distinguish between internal and external customers and suppliers and their impact on products and services, and identify strategies for working with them to improve products, services, and processes. (Apply)
   2. Customer satisfaction analysis
      Describe the different types of tools used to gather and analyze customer feedback: surveys, complaint forms, warranty analysis, quality function deployment (QFD), etc. (Understand)
   3. Product/process approval systems
      Identify and describe how validation and qualification methods (alpha/beta testing, first-article, etc.) are used in new or revised products, processes, and services. (Understand)
   4. Reliability
      Define basic concepts such as mean time to failure (MTTF), mean time between failures (MTBF), mean time between maintenance actions (MTBMA), and mean time to repair (MTTR), and identify failure models such as bathtub curve, prediction, growth, etc. (Remember)
   5. Supplier management
      Define and describe key measures of supplier performance (quality, price, delivery, level of service, etc.) and commonly used metrics (defect rates, functional performance, timeliness, responsiveness, technical support, etc.). (Understand)
   6. Elements of corrective and preventive action
      Identify elements of the corrective action process including containment, problem identification, root cause analysis, correction, recurrence prevention, verification and validation of effectiveness, and concepts of preventive action. (Analyze)
   7. Material identification, status, and traceability
      Describe methodologies used for material identification and conformance status. Apply various methods of identifying and segregating nonconforming materials, and describe the requirements for preserving the identity of a product and its origin. (Apply)
      [NOTE: Product recall procedures will not be included.]

Levels of Cognition
based on Bloom's Taxonomy (Revised)

In addition to content specifics, the subtext detail also indicates the intended complexity level of the test questions for that topic. These levels are based on the Revised “Levels of Cognition” (from Bloom’s Taxonomy, 2001) and are presented below in rank order, from least complex to most complex.

Remember
(Also commonly referred to as recognition, recall, or rote knowledge.) Be able to remember or recognize terminology, definitions, facts, ideas, materials, patterns, sequences, methodologies, principles, etc.

Understand
Be able to read and understand descriptions, communications, reports, tables, diagrams, directions, regulations, etc.

Apply
Be able to apply ideas, procedures, methods, formulas, principles, theories, etc., in job-related situations.

Analyze
Be able to break down information into its constituent parts and recognize the parts’ relationship to one another and how they are organized; identify sublevel factors or salient data from a complex scenario.

Evaluate
Be able to make judgments regarding the value of proposed ideas, solutions, methodologies, etc., by using appropriate criteria or standards to estimate accuracy, effectiveness, economic benefits, etc.

Create
Be able to put parts or elements together in such a way as to show a pattern or structure not clearly there before; able to identify which data or information from a complex set is appropriate to examine further or from which supported conclusions can be drawn.