
Production Quality Course
Master the tools, methods, and frameworks that drive consistent product quality on the production floor. This course covers everything from statistical process control and capability analysis to root cause investigation and continuous improvement. Whether you work in manufacturing, quality assurance, or operations management, you will gain the practical skills to reduce defects, cut costs, and build a quality system that holds up under scrutiny.
What you'll learn:
You will learn how to apply core quality management principles across every stage of production, from incoming inspection to final product release. The course covers statistical tools including control charts, capability indices, and sampling plans, giving you the ability to make data-driven decisions with confidence. You will work through structured problem-solving methods, lean improvement frameworks, and DMAIC project execution. Advanced topics include FMEA, APQP, supplier quality management, and regulatory compliance. By the end, you will know how to design, implement, and sustain a quality system that meets both customer requirements and business objectives.
How you study in practice Production Quality Course
How you practise Production Quality Course
For businesses looking to train their team
With Dedika for businesses, the course includes exercises and examples tailored to your own business and the way your company needs.
Course content
8 Chapters • 40 LessonsDuration between 4 and 360 hours (you decide)
Chapter 1HideHide detailsSee detailsFoundations of Production Quality
Foundations of Production Quality
Lesson 1 • Quality Management Systems Overview
Introduces structured QMS frameworks, their components, and certification pathways. Sets the stage for applying systematic quality practices throughout the course.
Lesson 2 • History and Evolution of Quality
Traces quality management from craft inspection to modern systems thinking. Provides historical context that explains why current practices exist.
Lesson 3 • Roles and Responsibilities in Quality
Maps quality ownership across organisational levels from operators to executives. Clarifies accountability structures students will operate within.
Lesson 4 • Defining Quality in Production
Covers the multiple dimensions of quality—conformance, fitness for use, and customer perception. Anchors all subsequent chapters in a shared definitional framework.
Lesson 5 • Cost of Quality Framework
Breaks down prevention, appraisal, internal failure, and external failure costs. Demonstrates how quality investment reduces total operational cost.
Chapter 2HideHide detailsSee detailsStatistical Foundations for Quality Control
Statistical Foundations for Quality Control
Lesson 1 • Measurement System Analysis
Evaluates gauge repeatability, reproducibility, and bias to validate measurement tools. Ensures data collected in later chapters is trustworthy.
Lesson 2 • Descriptive Statistics for Production
Applies measures of central tendency and dispersion to production datasets. Provides the numerical summaries used in all subsequent analysis chapters.
Lesson 3 • Sampling Theory and Plans
Covers random sampling, sample size determination, and acceptance sampling logic. Ensures students can design statistically valid inspection schemes.
Lesson 4 • Probability and Distributions
Introduces normal, binomial, and Poisson distributions relevant to defect modelling. Enables students to predict process behaviour and set realistic quality targets.
Lesson 5 • Data Types and Measurement Scales
Distinguishes attribute from variable data and nominal from ratio scales. Correct data classification drives appropriate tool selection throughout the course.
Chapter 3HideHide detailsSee detailsProcess Control Charts and Monitoring
Process Control Charts and Monitoring
Lesson 1 • Variable Control Charts
Constructs X-bar, R, and S charts for continuous measurement data. Covers control limit calculation, plotting, and interpretation rules.
Lesson 2 • Control Chart Interpretation Patterns
Identifies runs, trends, cycles, and stratification patterns on control charts. Pattern recognition enables faster diagnosis of process problems.
Lesson 3 • Attribute Control Charts
Builds p, np, c, and u charts for count and proportion defect data. Extends monitoring capability to processes where variable measurement is impractical.
Lesson 4 • Implementing SPC in Production
Guides the practical rollout of statistical process control on the shop floor. Addresses operator training, data collection frequency, and chart maintenance.
Lesson 5 • Variation and Process Stability
Differentiates common cause from special cause variation and defines statistical control. This distinction is the conceptual core of all control chart interpretation.
Chapter 4HideHide detailsSee detailsProcess Capability and Performance
Process Capability and Performance
Lesson 1 • Specification Limits and Tolerances
Defines upper and lower specification limits, bilateral and unilateral tolerances. Establishes the target boundaries against which capability is measured.
Lesson 2 • Performance Indices Pp and Ppk
Distinguishes short-term capability from long-term performance using Pp and Ppk. Helps students communicate process stability over extended production runs.
Lesson 3 • Capability Indices Cp and Cpk
Calculates and interprets Cp for spread and Cpk for centering relative to specifications. These indices are the primary language of capability reporting.
Lesson 4 • Non-Normal Process Capability
Addresses capability analysis when data does not follow a normal distribution. Equips students to handle real-world processes that violate normality assumptions.
Lesson 5 • Capability Improvement Strategies
Links low capability indices to actionable improvement levers such as centering and variance reduction. Connects capability analysis to the improvement chapters that follow.
Chapter 5HideHide detailsSee detailsRoot Cause Analysis and Problem Solving
Root Cause Analysis and Problem Solving
Lesson 1 • Problem Definition and Scoping
Applies problem statements, IS/IS-NOT analysis, and scope boundaries to frame quality issues. Precise problem definition prevents wasted investigation effort.
Lesson 2 • Corrective and Preventive Actions
Structures CAPA plans with owners, timelines, and effectiveness verification criteria. Closes the loop between root cause identification and sustained process improvement.
Lesson 3 • Five Whys and Fault Tree Analysis
Drills from symptom to root cause using iterative why questioning and logic trees. Combines inductive and deductive reasoning for thorough cause verification.
Lesson 4 • Cause-and-Effect Analysis Tools
Constructs fishbone diagrams and applies the 5M+E framework to map potential causes. Provides a visual structure for team-based cause brainstorming.
Lesson 5 • Data-Driven Cause Verification
Uses Pareto analysis, scatter plots, and hypothesis testing to confirm suspected causes. Prevents corrective actions based on opinion rather than evidence.
Chapter 6HideHide detailsSee detailsInspection, Testing, and Acceptance
Inspection, Testing, and Acceptance
Lesson 1 • Inspection Methods and Techniques
Covers visual, dimensional, functional, and destructive testing methods. Matches inspection technique to product characteristic and defect type.
Lesson 2 • Nonconforming Material Control
Establishes segregation, identification, and disposition processes for rejected material. Prevents nonconforming product from reaching customers or downstream operations.
Lesson 3 • Acceptance Sampling Execution
Applies single, double, and sequential sampling plans to lot disposition decisions. Balances producer and consumer risk in acceptance decisions.
Lesson 4 • Calibration and Gauge Management
Manages calibration schedules, traceability, and out-of-tolerance response for measurement tools. Ensures inspection results are legally and technically defensible.
Lesson 5 • Inspection Strategy and Planning
Defines incoming, in-process, and final inspection stages and their strategic purpose. Aligns inspection intensity with risk level and product criticality.
Chapter 7HideHide detailsSee detailsContinuous Improvement Methodologies
Continuous Improvement Methodologies
Lesson 1 • Sustaining Improvement and Control Plans
Creates control plans, standard work, and monitoring systems to lock in improvement gains. Addresses the common failure mode of reverting to pre-improvement conditions.
Lesson 2 • Design of Experiments for Improvement
Uses factorial and response surface designs to identify optimal process settings. DOE provides statistically rigorous evidence for improvement decisions.
Lesson 3 • DMAIC Framework Application
Executes the Define, Measure, Analyse, Improve, and Control phases of a quality improvement project. Provides a repeatable project structure applicable to any production problem.
Lesson 4 • Lean Principles and Waste Elimination
Identifies the eight wastes and applies value stream mapping to expose non-value-added activities. Lean thinking complements statistical tools by targeting flow and efficiency.
Lesson 5 • Kaizen Event Planning and Execution
Structures focused rapid-improvement events with defined scope, team roles, and follow-up actions. Kaizen events deliver quick wins that build organisational improvement culture.
Chapter 8HideHide detailsSee detailsQuality Strategy and Organisational Integration
Quality Strategy and Organisational Integration
Lesson 1 • Quality Auditing and Compliance
Plans and conducts internal audits to verify QMS conformance and identify improvement opportunities. Prepares students for both auditor and auditee roles.
Lesson 2 • Customer Satisfaction and Feedback Systems
Captures, analyses, and acts on customer complaints, returns, and satisfaction surveys. Closes the feedback loop between customer experience and production quality decisions.
Lesson 3 • Supplier Quality Management
Designs supplier qualification, monitoring, and development programmes to control incoming quality. Extends quality management beyond the factory to the supply chain.
Lesson 4 • Building a Quality Culture
Identifies cultural enablers and barriers to quality and applies change management techniques. Sustains quality performance through people engagement, not just systems.
Lesson 5 • Aligning Quality with Business Strategy
Links quality objectives to organisational goals using policy deployment and balanced scorecards. Ensures quality investments are prioritised by strategic impact.
Your valid completion certificate
This course is for you:
Production operators: ready to move into quality roles with formal knowledge.
Quality technicians: seeking structured frameworks to back up hands-on experience.
Manufacturing supervisors: responsible for output quality but lacking analytical tools.
Operations managers: needing to understand quality systems to lead their teams effectively.
Career changers: entering manufacturing from unrelated fields and building core competencies.
Industrial engineering students: bridging academic theory with real production quality practice.
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