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Postgraduate Diploma in MES, Traceability and Data-Ops in Production

Online 800-hour Postgraduate Diploma in MES, Traceability and Data-Ops in Production. 8 modules covering IEC 62264 / ISA-95 (enterprise-control integration), IEC 62541 (OPC UA) and Siemens Opcenter. Assigned tutor and open enrolment.

Duration800 h
ModeOnline
LanguageEnglish
Start datesSet by the faculty
AwardSEIUM Institute diploma
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Learning outcomes

What you will be able to do

01

Define the functions of a manufacturing execution system.

02

Integrate plant, machine and corporate system data.

03

Design material and process traceability systems.

04

Establish DataOps practices and data governance.

05

Apply analytics to improve productivity and quality.

06

Deploy and maintain models in production using MLOps practices.

07

Incorporate cybersecurity and change management into MES projects.

Profile

Who it's for

  • MES engineer seeking to specialise in MES, Traceability and Data-Ops in Production.
  • Industrial data engineer seeking to specialise in MES, Traceability and Data-Ops in Production.
  • MLOps specialist seeking to specialise in MES, Traceability and Data-Ops in Production.
  • Traceability manager seeking to specialise in MES, Traceability and Data-Ops in Production.
  • Industry 4.0 solutions architect seeking to specialise in MES, Traceability and Data-Ops in Production.
  • OT cybersecurity manager seeking to specialise in MES, Traceability and Data-Ops in Production.
  • Engineering or science graduates looking to enter shipbuilding.
Standards & tools

What you'll work with

  • IEC 62264 / ISA-95 (enterprise-control integration)
  • IEC 62541 (OPC UA)
  • IEC 62443 (industrial cybersecurity)
  • ISA-88 (batch control)
  • ISO 8000 (data quality)
  • ISO 22400 (manufacturing key performance indicators)
  • ISO/IEC 27001 (information security)
Syllabus

8 modules · 800 h

  1. 1.1ISA-95 pyramid and automation levels
  2. 1.2MES functions according to MESA International
  3. 1.3Differences between ERP, MES and SCADA
  4. 1.4Work orders in shipyards
  5. 1.5Plant data capture
  6. 1.6Resource and workshop personnel management
  7. 1.7Quality management integrated into MES
  8. 1.8MES solutions for the naval industry
  9. 1.9Implementation case studies in shipyards
  10. 1.10Practical: ISA-95 model of a panel workshop
  1. 2.1ISA-95 and B2MML interfaces
  2. 2.2OPC UA and information models
  3. 2.3MQTT and publish-subscribe architecture
  4. 2.4Integration of CNC machines and welding robots
  5. 2.5Integration with CAD/CAM and nesting
  6. 2.6Integration with ERP and planning
  7. 2.7Service buses and APIs
  8. 2.8Master data quality
  9. 2.9Edge and cloud architectures
  10. 2.10Workshop: OPC UA connection of a plasma cutting machine
  1. 3.1Product genealogy
  2. 3.2Plate traceability from cutting
  3. 3.3Recording welding parameters
  4. 3.4Welder traceability and certifications
  5. 3.5Paint traceability and environmental conditions
  6. 3.6Recording inspections and non-conformities
  7. 3.7Digital construction logbook
  8. 3.8Class and shipowner requirements
  9. 3.9Traceability audit
  10. 3.10Practical: genealogy data model of a block
  1. 4.1DataOps principles and lifecycle
  2. 4.2Data pipelines and ingestion
  3. 4.3Data lakes and analytical warehouses
  4. 4.4Data and schema versioning
  5. 4.5Automated data quality
  6. 4.6Data catalogue and lineage
  7. 4.7Data governance and ownership
  8. 4.8Orchestration with Apache Airflow
  9. 4.9Pipeline monitoring
  10. 4.10Laboratory: production data pipeline with Airflow
  1. 5.1OEE indicators and productivity
  2. 5.2Descriptive progress analytics
  3. 5.3Time and deviation analysis
  4. 5.4Process anomaly detection
  5. 5.5Lead time prediction with machine learning
  6. 5.6Quality and defect analysis
  7. 5.7Visualisation with Power BI and Grafana
  8. 5.8Real-time analytics with streaming
  9. 5.9Communicating results to the plant floor
  10. 5.10Practical: OEE dashboard for a workshop
  1. 6.1From prototype to production
  2. 6.2Containerisation with Docker
  3. 6.3Deployment at the edge and in the cloud
  4. 6.4Model drift monitoring
  5. 6.5Retraining and version management
  6. 6.6Testing models in production
  7. 6.7Infrastructure as code
  8. 6.8Deployment security
  9. 6.9Operating costs
  10. 6.10Case study: deployment of a delay prediction model
  1. 7.1IEC 62443 standard in OT environments
  2. 7.2Plant network segmentation
  3. 7.3Identity and access management
  4. 7.4Incident response in production
  5. 7.5Data protection and intellectual property
  6. 7.6Organisational change management
  7. 7.7Training for plant users
  8. 7.8Digital adoption indicators
  9. 7.9Digital transformation roadmap
  10. 7.10Case study: IEC 62443 assessment of a workshop network
  1. 8.1Plant diagnosis
  2. 8.2Proposed MES architecture
  3. 8.3Data integration model
  4. 8.4Traceability system
  5. 8.5DataOps pipeline design
  6. 8.6Analytical dashboard
  7. 8.7Cybersecurity plan
  8. 8.8Implementation plan
  9. 8.9Report and presentation
  10. 8.10Final review with the tutor
Methodology, software & labs

How you'll learn

Fully 100% online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: students progress at their own pace within the intake, making it possible to combine with work.

Each module combines theory, guided reading of the original standard and applied exercises. The working software is Siemens Opcenter, Apache Kafka, MLflow, Python, Power BI, in free, academic or evaluation versions. Exercises are based on real procedures for plant data integration via OPC UA, deployment of an analytics model in production, and design of a traceability system. Assessment is continuous, module by module, plus the final integrative project.

Accreditable laboratories(EN ISO/IEC 17025) with a rotor test rig, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-oriented final project:safety case, test plan, compliance dossier and operating limits.
Industry mentoring:lecturers with experience in training, , eVTOL/UAM and flight test.
Flexible format(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:a safety-by-design approach, with OT cybersecurity, 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.

Plant diagnosis

Define the functions of a manufacturing execution system.

Proposed MES architecture

Integrate plant, machine and corporate system data.

Data integration model

Design material and process traceability systems.

Traceability system

Establish DataOps practices and data governance.

DataOps pipeline design

Apply analytics to improve productivity and quality.

Career opportunities

Where this takes you

MES engineerIndustrial data engineerMLOps specialistTraceability managerIndustry 4.0 solutions architectOT cybersecurity manager
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 command of Spanish to follow technical standards documentation.

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.

You will work with Siemens Opcenter, Apache Kafka, MLflow, Python, Power BI. Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.

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

Yes. Modules passed in a Course or Postgraduate Diploma in the same area are recognised towards the higher-level programme. Check the recognition policy when enrolling.

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