About the Course
Organizations use quality engineering to prove that processes can stay within specification, not just to describe defects after they happen. In this field, you need to demonstrate control-chart interpretation, capability analysis, measurement discipline, root-cause analysis, and corrective-action design, all while aligning with ISO 9001:2015 quality management requirements and internal customer expectations. This course is built around those realities, so you can convert data from production, inspection, and test systems into decisions that leadership can defend.
The course turns scattered statistical knowledge into a working system for day-to-day quality control. You will practice selecting the right control chart, calculating Cp/Cpk and Pp/Ppk, interpreting measurement system analysis outputs, and linking Pareto and Ishikawa analysis to a realistic response plan. You will also be introduced to advanced quality analytics concepts such as AI-assisted defect pattern detection and automated SPC dashboards, while the hands-on work focuses on core tools you can apply immediately. What you will learn: how to use SPC charts, capability indices, and measurement system analysis to monitor variation, identify unstable processes, and design corrective actions that hold up in review. You will practice building control plans and quality reports, and you will be introduced to predictive quality workflows at a conceptual level.
Quality engineering and SPC training is especially useful where throughput pressure, supplier variation, and audit expectations compete for attention. The course is designed for professionals who must maintain process stability in real operating conditions, where data may be incomplete, shifts may be fragmented, and improvement work must happen without stopping production.
Target Audience
This advanced quality engineering and SPC training is for professionals who already work with process data and now need stronger statistical control, capability analysis, and corrective-action discipline.
- Quality Engineer responsible for control charts, capability studies, and reaction plans.
- SPC Analyst monitoring process stability and special-cause variation across production lines.
- Manufacturing Quality Manager approving control plans and escalation triggers.
- Process Improvement Engineer linking Pareto analysis to root-cause countermeasures.
- Quality Assurance Supervisor reviewing inspection trends and nonconformance containment.
- Operations Excellence Lead translating variation data into operational control actions.
- Metrology Specialist supporting measurement system analysis and gauge calibration decisions.
- Production Supervisor acting on SPC alerts during shift-based operations.
- Supplier Quality Engineer managing incoming variation and supplier capability reviews.
- Continuous Improvement Manager reporting process capability and defect reduction progress.
Course Objectives
This course equips you to plan, execute, and measure quality engineering and SPC initiatives that reduce variation, strengthen process capability, and support audit-ready reporting.
- Assess current process stability using X-bar and R charts, Individuals charts, and Pareto analysis.
- Apply SPC rules to identify special-cause variation and prioritize containment actions.
- Design a control plan that links critical-to-quality characteristics to reaction triggers.
- Build capability reports using Cp, Cpk, Pp, and Ppk calculations from process data.
- Evaluate measurement reliability through MSA, gauge R&R, and bias checks.
- Navigate ISO 9001:2015 quality documentation and supplier quality escalation requirements.
- Implement data-driven quality targets using defect rate, DPMO, and process capability dashboards.
- Synthesize SPC findings into management reports, corrective-action summaries, and improvement recommendations.
Requirements & Prerequisites
Prerequisites required: working knowledge of basic statistics, familiarity with process data, and experience in a production, testing, or quality environment. You should be comfortable with mean, standard deviation, histograms, and simple spreadsheet-based analysis. A laptop with Microsoft Excel or equivalent spreadsheet software is required for hands-on exercises. No programming is required for completion, although prior exposure to Minitab or another statistical quality tool will help. Advanced concepts are taught at the operational application level, with some conceptual exposure to AI-assisted quality analytics.
Local Application and Business Return in your market
How participants can apply the training in local operating conditions, and the return their organisation can plan for.
How participants apply this
Expected ROI
Training Methodology
This is a practical, outcome-driven course designed to turn quality engineering and SPC training aspiration into measurable action and credible reporting.
Methodology includes:
- Hands-on calculation exercise using real process data to compute Cp/Cpk, Pp/Ppk, and defect rates.
- Scenario simulation based on an out-of-control control chart and line-stop escalation decision.
- Assessment exercise using ISO 9001:2015 control-document checks and an SPC audit checklist.
- Stakeholder mapping of quality alerts, production response owners, and escalation paths.
- Case study analysis from automotive, pharmaceuticals, electronics, and food manufacturing quality environments.
- Group workshop producing a control plan and reaction matrix under time constraints.
- Reflection exercise challenging current SPC habits against capability benchmarks and measurement system results.
Upcoming Sessions
Next available dates worldwide
Certification
Recognized credentials that advance your career
Participants who complete the Quality Engineering and SPC Training Program earn a Trainingcred Certificate of Achievement, demonstrating professional competence and alignment with global standards in learning and development.
NITA Accredited
Accredited by the National Industrial Training Authority, ensuring programs meet nationally recognized standards of quality and relevance.
CPD Certified
Recognized by the CPD Certification Service, ensuring every program meets internationally benchmarked standards of professional excellence.
Why this course earns its place on your CV
Accredited training, practitioner trainers, and peers on the same career track — the three things real expertise is built on.
Effective Learning & Skill Development
- Build expertise with structured, outcome-driven learning.
- Equip individuals and teams with skills that grow with industry needs.
- Reinforce learning through real-world scenarios, case studies and practical exercises.
Career Growth & Professional Advancement
- Apply what you learn with a proven methodology that ensures lasting impact.
- Develop immediately usable skills that translate directly into workplace success.
- Gain the expertise needed for career advancement and leadership roles.
Training Optimization & Learning Excellence
- Tailor training to industry-specific challenges and organizational goals.
- Use data-driven insights and automation to enhance training effectiveness.
- Evaluate progress and ensure long-term learning success.
Tools and platforms relevant to this field
Examples local teams may encounter, and that may be featured in training where they support the confirmed course scope.
These are field-relevant examples, not a promise that every tool will be covered. Exact coverage depends on the confirmed course scope, participant needs, and delivery format.
-
Power BI MicrosoftUsed to build interactive SPC dashboards that visualize control charts and capability indices for real-time process monitoring and executive reporting.
-
JMP Statistical Software SAS InstituteProvides advanced statistical analysis capabilities for process capability studies, control chart generation, and measurement system analysis in US manufacturing.
-
Minitab Minitab, LLCIndustry-standard tool for SPC, process capability analysis, and design of experiments, widely adopted in US quality engineering for its robust statistical features.
