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Postgraduate Diploma in Advanced Control and Process Optimisation

Online 800 h Postgraduate Diploma in Advanced Control and Process Optimisation. 8 modules covering IEC 61511, IEC 61131-3 and AspenTech DMC3. Dedicated tutor and open enrolment.

Duration800 h
ModeOnline
AwardSEIUM Institute diploma
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Virtual lab · try it before you enrol

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.

SIM · LIVE ●
Learning outcomes

What you will be able to do

01

Apply advanced regulatory control strategies.

02

Model industrial processes using mass and energy balances and identification.

03

Design multivariable predictive controllers.

04

Formulate and solve process optimisation problems.

05

Develop virtual sensors and quality inferences.

06

Monitor the performance and benefits of advanced control.

07

Manage APC implementation projects.

Profile

Who it's for

  • Advanced control engineer who wants to specialise in Advanced Control and Process Optimisation.
  • Process engineer who wants to specialise in Advanced Control and Process Optimisation.
  • Optimisation engineer who wants to specialise in Advanced Control and Process Optimisation.
  • APC consultant who wants to specialise in Advanced Control and Process Optimisation.
  • Distributed control systems engineer who wants to specialise in Advanced Control and Process Optimisation.
  • Plant performance analyst who wants to specialise in Advanced Control and Process Optimisation.
  • Engineering or science graduates seeking to enter refining and petrochemicals.
Standards & tools

What you'll work with

  • IEC 61511
  • IEC 61131-3
  • ISA-5.1
  • ISA-95
  • IEC 62264-1
  • ISA-18.2
Syllabus

8 modules · 800 h

  1. 1.1Limitations of simple PID control
  2. 1.2Cascade control
  3. 1.3Ratio control
  4. 1.4Feedforward disturbance control
  5. 1.5Selective and override control
  6. 1.6Split-range control
  7. 1.7Dead-time compensation
  8. 1.8Loop decoupling
  9. 1.9Inventory and level control
  10. 1.10Practical: ratio control in a blend
  1. 2.1Mass and energy balances
  2. 2.2Dynamic reactor models
  3. 2.3Distillation column models
  4. 2.4Process identification
  5. 2.5Finite response models
  6. 2.6Empirical and grey-box models
  7. 2.7Dynamic process simulation
  8. 2.8Model validation
  9. 2.9Linearity and process operating points
  10. 2.10Laboratory: identification of a heat exchanger
  1. 3.1Structure of an MPC controller
  2. 3.2DMC and dynamic matrix control
  3. 3.3Manipulated, controlled and disturbance variables
  4. 3.4Process constraints
  5. 3.5Steady-state optimisation layer
  6. 3.6Tuning MPC controllers
  7. 3.7Model maintenance
  8. 3.8Commercial APC packages
  9. 3.9Constraint variables and their prioritisation
  10. 3.10Workshop: multivariable MPC of a distillation column
  1. 4.1Formulation of optimisation problems
  2. 4.2Linear and non-linear programming
  3. 4.3Real-time optimisation
  4. 4.4Constrained optimisation
  5. 4.5Economic objective functions
  6. 4.6Sensitivity analysis
  7. 4.7Multi-objective process optimisation
  8. 4.8Optimisation tools
  9. 4.9Optimisation of plant utilities
  10. 4.10Practical: economic optimisation of a reactor
  1. 5.1Virtual process sensors
  2. 5.2Quality inferences
  3. 5.3PLS regression for inferences
  4. 5.4Neural networks for properties
  5. 5.5Validation of inferences
  6. 5.6Correction with analysers
  7. 5.7Management of online analysers
  8. 5.8Bias and model updating
  9. 5.9Delays of laboratory analysers
  10. 5.10Laboratory: virtual composition sensor
  1. 6.1Advanced control metrics
  2. 6.2APC service factor
  3. 6.3Detection of degradation
  4. 6.4Benefits analysis
  5. 6.5Economic indicators of control
  6. 6.6Performance reports
  7. 6.7Diagnosis of regulatory loops
  8. 6.8Maintenance of APC applications
  9. 6.9Analysis of APC disconnection causes
  10. 6.10Case study: APC audit in a refinery
  1. 7.1Feasibility study
  2. 7.2Plant tests (step tests)
  3. 7.3Controller design
  4. 7.4Commissioning
  5. 7.5Operator training
  6. 7.6Change management
  7. 7.7Return on investment
  8. 7.8Lessons learned from APC projects
  9. 7.9APC model maintenance plan
  10. 7.10Case study: APC project in a chemical plant
  1. 8.1Process analysis
  2. 8.2Regulatory control design
  3. 8.3Modelling and identification
  4. 8.4MPC design
  5. 8.5Economic process optimisation
  6. 8.6Virtual process sensors
  7. 8.7Benefits assessment
  8. 8.8Analysis of results
  9. 8.9Report and presentation
  10. 8.10Final review with the tutor
Methodology, software & labs

How you'll learn

Delivered 100 % online through the SEIUM campus, with downloadable material, recorded classes and a dedicated technical tutor. There are no fixed timetables: students progress at their own pace within the intake, which makes it possible to combine study with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is AspenTech DMC3, Aspen HYSYS, MATLAB/Simulink, Honeywell Profit Suite, Python with Pyomo, in free, academic or evaluation versions. Tests are studied using real predictive control procedures for distillation columns, real-time optimisation of reactors and virtual sensors for product quality. Assessment is continuous by module plus the final integrating project.

Accredited laboratories(EN ISO/IEC 17025) with rotor rig, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-focused Master's Thesis (TFM):safety case, test plan, compliance dossier and operating limits.
Industry-mentored:faculty with track records in the training, , eVTOL/UAM and flight test.
Flexible format(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:safety-by-design approach, cyber-OT, DIH and compliance as core pillars.
Capstone project

Build it end to end

Your final project follows the real engineering workflow, step by step, reviewed by your tutor.

Process analysis

Apply advanced regulatory control strategies.

Regulatory control design

Model industrial processes using mass and energy balances and identification.

Modelling and identification

Design multivariable predictive controllers.

MPC design

Formulate and solve process optimisation problems.

Economic process optimisation

Develop virtual sensors and quality inferences.

Career opportunities

Where this takes you

Advanced control engineerProcess engineerOptimisation engineerAPC consultantDistributed control systems engineerPlant performance analyst
Admissions & scholarships

Requirements

  • Prior technical training or professional experience in the sector. A university degree is not required.
  • Internet connection and a computer capable of running the programme's software.
  • Sufficient level of Spanish to follow technical regulatory reading.

Ready to start?

Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.

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FAQ

Frequently asked questions

The programme consists of 800 hours in total, spread over 6 to 8 months. This is an average of 10 to 15 hours per week, compatible with a full-time job.

The programme uses AspenTech DMC3, Aspen HYSYS, MATLAB/Simulink, Honeywell Profit Suite and Python with Pyomo. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.

A SEIUM proprietary diploma upon passing the continuous assessment and the final integrating project. This is in-house training, not an official Ministry qualification.

Yes. Modules passed in a course or postgraduate diploma in the same area can be credited towards the advanced programme. Check the credit transfer policy when you enrol.

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