Diploma in Statistical Process Control and DOE
Online postgraduate diploma of 800 hours in statistical process control and DOE. 8 modules covering ISO 7870-2:2023, ISO 22514-2 and AIAG MSA 4th edition, with Minitab, JMP, R and Design-Expert, with an assigned technical tutor.
Diploma in Statistical Process Control and DOE — studying from Canada
Canada has a notable robotics and automation sector, with research leadership at institutions such as McGill University, the University of Toronto and the University of Waterloo. Industrial automation firms and integrators serve manufacturing, automotive and resource industries across Ontario, Québec and Alberta. The Canadian Space Agency's robotic systems contribute to space robotics expertise. Engineers work on control systems, industrial robots, mechatronics and automation integration.
Fees for Canada: C$1,700 (Canadian dollar), with instalments and employer sponsorship available.
Relevant bodies in Canada
Typical roles
Questions from Canada
Is this programme recognised by professional bodies in Canada for robotics and control engineering?
SEIUM's qualifications are private, not official state degrees, and are not accredited by any national body in Canada. Professional engineering titles are regulated provincially, for example by Professional Engineers Ontario, and engineering graduates in Canada typically pursue licensure through these bodies. Recognition of a private qualification is decided by employers or the relevant body.
Where could this qualification help in Canada's robotics and automation job market?
Canadian employers in manufacturing, logistics, aerospace, mining and automation integration may hire for robotics and control skills. Whether they value a private qualification is their decision, and many also weigh portfolios, experience and recognised credentials. The final project can demonstrate applied ability, though it does not guarantee any job.
How can I study this while working full time in Canada?
The programme is entirely online and taught in English, so you can study from home across Canadian time zones, and no student visa is needed. Choose from 300-hour specialist courses, 800-hour postgraduate diplomas or 1,900-hour master's programmes. Fees are payable in instalments, employer sponsorship is possible, and you receive an assigned technical tutor.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Distinguish between common-cause and special-cause variation.
Design and interpret univariate and multivariate control charts.
Assess process capability and measurement system capability.
Plan and analyse full and fractional factorial designs.
Optimise processes using response surface methodology.
Apply robust design against noise factors.
Integrate SPC and DOE into the company's quality system.
Who it's for
- Quality engineers responsible for process capability and control plans.
- Six Sigma Black Belts who want deeper DOE and SPC skills.
- Process engineers running experiments to optimise production.
- Metrology technicians handling measurement system analysis.
- Industrial statistical analysts.
- Process development engineers scaling processes from lab to production.
- Engineering or science graduates aiming to enter the automotive sector.
What you'll work with
- ISO 7870-2:2023 (Shewhart control charts)
- ISO 22514-2 (process capability and performance)
- AIAG MSA 4th edition (measurement systems analysis)
- AIAG SPC 2nd edition (statistical process control)
- ISO 3534-3 (vocabulary: design of experiments)
- JCGM 100:2008 (GUM: uncertainty of measurement)
- ISO 13053-1 (Six Sigma: DMAIC methodology)
- Minitab
- JMP
- R with the qcc and DoE.base packages
- Design-Expert
- Python with statsmodels
8 modules
1.1Common causes and special causes1.2Normal, binomial and Poisson distributions1.3Descriptive statistics and exploratory plots1.4Sampling and rational subgroups1.5Confidence intervals1.6Hypothesis tests and power1.7Normality tests and transformations1.8Simple and multiple linear regression1.9Deming's statistical thinking1.10Workshop: exploratory analysis of process data
2.1X-bar R and X-bar S charts2.2Individuals and moving range charts2.3p, np, c and u charts2.4Western Electric and Nelson rules2.5Phase I and phase II2.6CUSUM and EWMA charts2.7Hotelling T² multivariate charts2.8Control with autocorrelated data2.9Out-of-control reaction plan2.10Practical: implementing an EWMA chart on a line
3.1Cp, Cpk, Pp and Ppk indices3.2Capability with non-normal data3.3Machine capability Cmk3.4R&R analysis of measurement systems3.5Bias, linearity and stability3.6Attribute studies and kappa3.7Measurement uncertainty according to the GUM3.8Tolerances and specifications3.9Process control plan3.10Lab: crossed R&R study in Minitab
4.1Principles: randomisation, replication and blocking4.22^k full factorial designs4.3Main effects and interactions4.4ANOVA and residual analysis4.5Fractional factorial designs4.6Resolution and confounding of effects4.7Centre points and curvature4.8Plackett-Burman screening designs4.9Definitive screening designs4.10Case study: screening of welding parameters
5.1Method of steepest ascent5.2Central composite designs5.3Box-Behnken designs5.4Second-order models5.5Optimisation with the desirability function5.6Mixture designs5.7D-optimal and I-optimal designs5.8Experimental validation of the optimum5.9Scale-up from laboratory to production5.10Practical: optimisation of a curing process
6.1Taguchi philosophy and the loss function6.2Control factors and noise factors6.3Taguchi orthogonal arrays6.4Calculating the signal-to-noise ratio6.5Split-plot designs6.6Modelling the mean and the variance6.7Statistical tolerance allocation6.8Robust design in industrial processes6.9Criticisms of and alternatives to Taguchi6.10Case study: robustness against ambient humidity
7.1SPC in APQP and PPAP7.2Control plan and PFMEA7.3Deploying SPC on the shop floor7.4Automated SPC with MES data7.5Training operators in control charts7.6Auditing the SPC system7.7DOE within DMAIC projects7.8Documenting experiments7.9A culture of data-driven decisions7.10Workshop: control plan for a critical characteristic
8.1Defining the quality problem8.2Validating the measurement system8.3Initial capability study8.4Planning the experiment8.5Running and analysing the DOE8.6Optimisation and confirmation8.7Control plan with SPC8.8Results and benefits8.9Report and presentation8.10Final project: final review with the tutor
How you'll learn
Training is 100% online on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. There are no fixed timetables: you progress at your own pace within each intake, so the programme fits around your job.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is Minitab, JMP, R with the qcc and DoE.base packages, Design-Expert and Python with statsmodels, in free, academic or evaluation versions. Testing is studied through real procedures: measurement system R&R studies, factorial experiments on a pilot line, and control charts for autocorrelated processes. Assessment is continuous by module, plus the final project.
Standards covered: ISO 7870-2:2023, ISO 22514-2, AIAG MSA 4th edition, AIAG SPC 2nd edition, ISO 3534-3, JCGM 100:2008 (GUM) and ISO 13053-1.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Where this takes you
Requirements
- Prior technical training or professional experience in the sector. No university degree is required.
- Internet connection and a computer capable of running the programme's software.
- English sufficient to read technical standards.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme totals 800 hours over 6–8 months. You set your own pace within each intake, and your tutor helps you plan the workload around your job.
You work with Minitab, JMP, R with the qcc and DoE.base packages, Design-Expert and Python with statsmodels, using free, academic or evaluation versions. Your tutor indicates the free alternative wherever one exists.
A SEIUM Institute diploma, awarded on passing the continuous assessment and the final project. It is SEIUM's own qualification, not an official state degree; its recognition depends on the programme completed and the regulations of each country.
Yes. Modules passed are recognised in a higher programme in the same area (postgraduate diploma or master's). Ask about the recognition policy when you enrol.
Prior technical training or professional experience in the sector (no university degree required), a computer able to run the software, and English sufficient to read technical standards.
Start dates are set by SEIUM's faculty for each intake. Our admissions team will confirm the next available date when you apply.
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