Certified Quality Engineer Training

Understand the right level of documented information under ISO 9001-2015, covering documents and records, distribution, access, storage, retention, and disposition, plus basic revision control and configuration management.

Explore ISO 9001 standards, ISO 9000 overview, and the Baldridge award, with emphasis on the three-layer certification system: certification body, accreditation body, and IAF.

Explore ISO 9001 revision history from 1987 to the 2015 version, noting the switch from twenty clauses to eight to ten main clauses and major upgrades in 2000 and 2008.

Explore why ISO 9001:2015 revised from 2008, focusing on reduced documentation and the creation of a common structure for multiple management systems through Annex SL, aligning standards.

Explore ISO 9001:2015 changes from 2008, including updated terms (product and services, documented information, external providers), no exclusions, process approach, and risk-based thinking.

Explore first party, second party, and third party audits, including internal vs external classifications and terms like registration and compliance audits for ISO 9001.

Expands audit roles by introducing technical experts, observers, and guides, detailing how they support the audit team with domain knowledge, non-interference observation, and facility navigation.

Identify how design inputs shape product and service design per ISO 9001:2015 clause 8.3. Focus on input and control (review, verification, validation); outputs and changes are not covered in CQE.

Explore robust design by identifying outer noise, inner noise, and between product noise to minimize their impact. Learn how temperature changes, shock, vibration, humidity, and deterioration affect the process.

Apply failure modes and effects analysis (FMEA) to identify and prioritize design and process risks, conducting conceptual, design, or process FMEA at system, subsystem, or component levels.

Use quality function deployment, or the house of quality, to translate customer needs into design inputs by ranking importance and linking what customers want to how you deliver it.

Learn to interpret drawings and specifications for the CQE exam, including dimensions, tolerances, and geometric dimensioning and tolerancing, plus first and third angle projections.

Demonstrate third angle projection by placing the object in the third quadrant and applying walls between viewer and object, yielding front, top, and side views and the symbol.

Explain the title block essentials of a manufacturing drawing, including drawing number, sheet number, revisions, approvals, units, scale, tolerances, bill of materials (bom), notes, and zones.

Learn to use eight common line types in technical drawings, including construction, boundary, hidden, centerline, dimension, break, cutting, and hatch lines, to convey boundaries, visibility, and cross-sections clearly.

Clarify datum versus datum feature in 3C GD&T. A datum is a perfect reference, while a datum feature is the tangible surface used to locate the part.

Explore how mean time to failure (MTTF) measures reliability for non repairable items by analyzing a lifecycle, failure timing, and the impact of sample size on average bulb life.

Explore mean time between failures (MTBF) as the reliability measure for repairable items, calculated as total operating hours divided by failed units, with the reciprocal giving the failure rate.

Explore mean time between failures (MTBF) and how exponential distribution governs reliability, including a 2-year MTBF example yielding about 36% no-failure probability and related failure-rate concepts.

Explore basic probability concepts and how reliability relates to probability, using dice, a 1000-bulbs example, and Venn diagrams to analyze union and intersection events for system performance.

Explore how series and parallel configurations affect system reliability; compute reliability by multiplying component reliabilities for series and noting that parallel uses an or condition.

Learn to calculate mixed series and parallel system reliability, solving parallel subsystems first, then multiplying series reliabilities, with notes on binomial, Poisson, Weibull, and exponential distributions for the CQE exam.

This lecture covers the 2022 ASQ CQE updates to the body of knowledge for reliability and maintainability, including use FMEA and hazard analysis, and explains dFMEA, pFMEA, and uFMEA.

Explore methods to control production and service delivery, covering control plan development, critical control point identification, work instruction development, and validation, plus acceptance sampling and measurement system analysis.

Understand material identification, status, and traceability, including PMI, mill test reports (MTRs), and lot numbers, to ensure materials are used and traceable under ISO 9001 guidance.

Differentiate defects from nonconformities and learn ISO 9001 requirements for nonconforming outputs. Apply containment, correction, corrective actions, and update the risk register and quality management system to prevent recurrence.

Learn how acceptance sampling uses samples with AQL and acceptable quality limits to decide lot acceptance, and understand producer's and consumer's risks, including type 1 and type 2 errors.

Explore acceptance sampling standards for attribute and variable sampling, compare ANSI/ASQ z1.4 and z1.9 with MIL-STD 105 and 414, and learn go/no-go decisions, acceptable quality limit concepts, and OC curve.

Explore acceptable quality limit, its role in acceptance sampling, and OC curves showing the probability of accepting a lot with defects, including producer's risk at 1.5 percent.

Explore how acceptable and rejectable quality limits shape sampling plans, define producer and buyer risks, and use alpha, beta, LTPD, and the OC curve to assess lot acceptance.

Illustrate OC curve for a sampling plan using Poisson distribution, linking AQL, RQL, alpha, and beta to acceptance probabilities. Show how increasing sample size steepens the curve and reduces RQL.

Explain how aoq and aoql relate to a sampling plan of 80 samples with an acceptance number of 3, and how ati varies with input defectives.

Explore attribute acceptance sampling with two examples (lot sizes 1000 and 50), using general inspection level 2 and AQLs of 1.5, 1.0, and 2.5, via code letters and arrows.

Compare the dodge romig sampling plans with MIL STD Z1.4, focusing on LQL and AOQL tables, single or double sampling, and process average to minimize ATI and protect the customer.

Explore how the coordinate measuring machine (CMM) was added in 2022 and how it measures complex geometry using multiple X, Y, Z points with touch or non-touch probes.

Explore how a histogram, a bar chart, visualizes the frequency and spread of measurements, using water bottle and arrival-time examples to reveal center, variation, and causes of deviation.

Apply a Pareto chart to prioritize quality improvements by the 80/20 rule, sorting issues from largest to smallest and targeting the vital few until 80 percent of problems are addressed.

Explore how a scatterplot shows the relationship between two variables, with the independent variable on the x-axis and the dependent variable on the y-axis, using temperature and ice cream sales.

Explore kaizen, the step-by-step improvement method, and kaizen blitz, a rapid, focused waste-removal approach. Document current state, identify wastes, implement changes, standardize, and celebrate gains.

Explore the PDCA cycle—plan, do, check, act—as an iterative, Deming‑inspired approach to planning, implementing, evaluating, and refining process improvements.

Identify the current constraint, exploit existing resources, subordinate all activities to the constraint, elevate the constraint with additional action, and anticipate new constraints as they move.

Learn how 5s drives workplace organisation by sorting, setting in order, shining, standardising, and sustaining to reduce waste and boost space utilisation, productivity, morale, and safety.

Learn how lean and Six Sigma reduce waste by identifying Muda, Mura, and Muri, including Type 1 and Type 2 Muda, to balance flow and boost profits.

Explore the 2022 updates to ASQ CQE section 5E, which adds 5 Whys as a corrective-action tool, with examples, best practices, and how to address root causes and policy issues.

Apply robust design as preventive action to minimize variation. In welding, use controllable factors like electrode, position, and heating to reduce outer noise, inner noise, and between product noise.

Explore qualitative and quantitative data, and differentiate continuous versus discrete data with real-world examples and measurement tools like go/no-go gauges.

Develop a data collection plan by defining goals, setting an operational definition, selecting data types and sampling, and using reliable time-based measurements like assembly time with a stopwatch.

Learn how to apply data coding to simplify recording, using addition, subtraction, multiplication, or truncation, and understand how these methods affect the mean and standard deviation.

Analyze data accuracy and integrity, identifying bias, knowledge gaps, boredom, rounding, and falsification. Implement safeguards like automation and audits, and preview descriptive statistics, inferential statistics, and hypothesis testing.

Explore descriptive statistics by summarizing data through central tendency and variability, using mean, median, mode, percentile, quartile, range, and standard deviation (sigma) for six sigma.

Master stem-and-leaf plots, box-and-whisker plots, and scatterplots to visualize data relationships; learn how stems and leaves organize data and interpret summaries from mpg examples.

determine the required sample size from the desired margin of error and confidence interval using z-values, sigma, and appropriate formulas for continuous data or proportions.

Explore how Venn diagrams illustrate union and intersection of events using dice examples, and define mutually exclusive, independent, and complementary events.

Explore factorials, permutations, and combinations, define 0! = 1, and distinguish between when order matters or not, with formulas for nPr and nCr and practical examples.

Explore the Bernoulli distribution as a single-trial variant of the binomial and contrast it with the hypergeometric distribution for sampling without replacement from a finite population.

Explore Poisson distribution for discrete data, compare it with binomial, and compute probabilities using mu and the formula e^{-mu} mu^x / x!, noting the mean equals variance for rare events.

Compute a 95% confidence interval using the z table when the population standard deviation is known or the sample size is large, illustrated with a 100-sample salary example.

Explore one-sample and two-sample hypothesis tests for mean, variance, and proportions, including z, t, paired t, p tests, chi-square, and ANOVA, to assess population changes.

Explore tests for variance and standard deviation, including the f test for equality of two variances, the chi-square test for population variance, and anova-related applications.

Understand the analysis of variance (anova) for testing equality of several means with the F test. See why anova controls error rates when comparing more than two means.

Perform manual ANOVA calculations by computing the sum of squares between and within, degrees of freedom, and the F value, then verify results with a Microsoft Excel ANOVA demonstration.

Learn how correlation measures how two variables fluctuate together, using hours studied as the independent variable and exam marks as the dependent variable, plus scatter diagrams and the correlation coefficient.

Compute the Pearson correlation coefficient quickly in Excel with the data analysis pack. Observe how you select input ranges and output results to a new worksheet.

Explore the correlation coefficient r as a measure of the strength and direction of the linear relationship between x and y, shown by hours studied and marks obtained.

Derive the regression equation y = a + b x to predict marks from hours studied, using the best-fit line with intercept and slope that minimizes squared distances.

Statistical process control uses monitoring and control charts to detect deviations and trigger quick action, reducing defects and ensuring conforming products while distinguishing common and special causes.

Learn to compute x bar and r charts, using constant subgroup sizes, with x bar mean, r bar range, and control limits via a2, d3, and d4.

Contrast p charts with np charts to show how changing subgroup size affects p bar and the upper and lower control limits, illustrated by a hospital unplanned-return example.

Learn how to construct a u chart for defects per unit when subgroup sizes vary, compute u bar, and set variable upper and lower control limits for each subgroup.

Learn short run SPC by focusing on the process, using a difference chart with I-MR charts and nominal sizes (300, 400, 500 mm) to set control limits.

Define the objective, select factors and the response, design and conduct experiments (full, partial, or Plackett-Burman), and analyze results with anova to guide screening, optimization, and robustness decisions.

Explore how sugar and milk interact to affect coffee ratings using design of experiment, larger samples, and three visuals: interaction charts, contour plots, and an interaction-inclusive equation.

Explore design and analysis of experiments with three factors at two levels, using sugar, milk, and bean, coded minus/plus, with results shown on a rating cube.

Explore half factorial design, reducing eight full-factor experiments to four using diamond or circle corners in a three-factor, two-level coffee study and c = a·b, plus resolution and blocking.

Identify nuisance factors and apply blocking, randomisation, and ANCOVA to manage their impact. Understand balanced and unbalanced designs.

Block randomized design controls known nuisance factors, such as sex, by blocking first (16 male, 14 female) and then randomizing within each block to treatment and placebo, ensuring balanced groups.

Apply qualitative risk analysis with a probability and impact matrix to identify high-priority risks and plan responses, avoid, mitigate, transfer, or accept negatives and exploit, enhance, share, or accept positives.

Apply these four options to positive risk: exploit, enhance, share, and accept, and monitor these actions as part of risk management. Put your best team members and resources to work.

Learn how risk based thinking emerged from ISO 9001:2015, identify risk in planning, and apply proportionate actions while evaluating effectiveness to continuously update risk.

Demonstrate mitigation planning as part of risk management by reducing the probability or impact, simplifying processes, prototyping for validation, and using inspections and lessons learned to reach full production.