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Postgraduate DiplomaRobotics, Automation & Control Applications open

Postgraduate Diploma in Telemetry, KPIs and AMR Operations Control

Online 800-hour Postgraduate Diploma in Telemetry, KPIs and AMR Operations Control. 8 modules covering ISO 22400-2:2014, VDA 5050 v2.1 and Grafana. Assigned tutor and enrolment open.

Duration800 h
ModeOnline
AwardSEIUM Institute diploma
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Postgraduate Diploma in Telemetry, KPIs and AMR Operations Control — studying from the United Kingdom

Robotics and automation are growing across the United Kingdom, from manufacturing and logistics to healthcare and research. Universities including Bristol, Oxford, Imperial College London and Edinburgh host robotics research, while the Robotics and Autonomous Systems hub and the Advanced Robotics Hub support collaboration with industry. Manufacturers, logistics operators and automation integrators employ engineers in control systems, sensing, programming and systems integration. Safety standards for collaborative robots shape deployment across industries.

Fees for the United Kingdom: £910 (Pound sterling), with instalments and employer sponsorship available.

Relevant bodies in the United Kingdom

  • Institution of Engineering and Technology (IET)
  • British Standards Institution (BSI)
  • UK Robotics and Artificial Intelligence Hub (RAI Hub)
  • Make UK

Typical roles

  • Robotics Engineer
  • Automation Engineer
  • Control Systems Engineer
  • Systems Integration Engineer

Questions from the United Kingdom

Which UK bodies recognise robotics and control engineering, and how does SEIUM's training fit?

The Institution of Engineering and Technology and the Institution of Mechanical Engineers are the main UK professional bodies for control and automation engineers. Chartered status is awarded through the Engineering Council via accredited routes. SEIUM's private qualifications are not accredited by any national body, so any recognition by these institutions is their own decision.

Will UK robotics and automation employers value a private online qualification?

UK robotics and automation employers usually weigh practical projects, programming skills and relevant experience heavily. A private qualification can support your CV where it reflects applied control or robotics work, particularly a strong final project. Employers decide how much value to attach to it, so tailor your application to their stated requirements.

Can I balance this with a UK job, and is there support in English?

Yes. The programmes are 100% online, taught in English, and you are assigned a technical tutor for support. Study ranges from 300 to 1,900 hours, so plan your schedule accordingly. Fees are payable in instalments, and employer sponsorship is possible. No student visa is required because you study from within the UK.

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Learning outcomes

What you will be able to do

01

Identify the relevant operational data of an AMR fleet.

02

Design scalable telemetry architectures.

03

Define availability, utilisation and performance KPIs.

04

Build dashboards for different profiles.

05

Organise an operations control centre.

06

Apply analytics to predictive maintenance.

07

Drive continuous improvement based on data.

Profile

Who it's for

  • Robotics operations analyst looking to specialise in Telemetry, KPIs and AMR Operations Control.
  • Control centre supervisor looking to specialise in Telemetry, KPIs and AMR Operations Control.
  • Industrial data engineer looking to specialise in Telemetry, KPIs and AMR Operations Control.
  • AMR fleet manager looking to specialise in Telemetry, KPIs and AMR Operations Control.
  • Predictive maintenance engineer looking to specialise in Telemetry, KPIs and AMR Operations Control.
  • Continuous improvement engineer looking to specialise in Telemetry, KPIs and AMR Operations Control.
  • Engineering or science graduates seeking to enter logistics.
Standards & tools

What you'll work with

  • ISO 22400-2:2014
  • VDA 5050 v2.1
  • ISO 3691-4:2023
  • EN 13306:2017
  • IEC 62443-3-3:2013
  • Regulation (EU) 2016/679 (GDPR)
Syllabus

8 modules · 800 h

  1. 1.1Data sources on a mobile robot
  2. 1.2Status, position and battery
  3. 1.3Events, alarms and faults
  4. 1.4Mission data and timings
  5. 1.5Sensor and motor diagnostics
  6. 1.6Sampling frequencies and volume
  7. 1.7Message formats and schemas
  8. 1.8Data quality and completeness
  9. 1.9Privacy and personal data
  10. 1.10Workshop: data inventory of an AMR fleet
  1. 2.1Data collection on the robot with agents
  2. 2.2Transport with MQTT and DDS
  3. 2.3Telemetry in ROS 2
  4. 2.4OpenTelemetry for metrics and traces
  5. 2.5Time-series databases
  6. 2.6InfluxDB and TimescaleDB
  7. 2.7Edge buffering during disconnections
  8. 2.8Data retention and aggregation
  9. 2.9Scalability for large fleets
  10. 2.10Practical: telemetry pipeline with MQTT and InfluxDB
  1. 3.1Technical and operational availability
  2. 3.2Utilisation and productive time
  3. 3.3Missions per hour and throughput
  4. 3.4Mean mission time
  5. 3.5MTBF and MTTR of robots
  6. 3.6Manual interventions per mission
  7. 3.7Distance travelled and efficiency
  8. 3.8Fleet energy KPIs
  9. 3.9KPI trees and targets
  10. 3.10Case study: KPI dashboard for a logistics centre
  1. 4.1Dashboard design principles
  2. 4.2Grafana for operations
  3. 4.3Real-time fleet maps
  4. 4.4Traffic and blockage heat maps
  5. 4.5Alerts and thresholds
  6. 4.6Dashboards for operator, supervisor and management
  7. 4.7Automatic shift reports
  8. 4.8Accessibility and visual clarity
  9. 4.9Query performance
  10. 4.10Laboratory: fleet dashboard in Grafana
  1. 5.1Functions of a control centre
  2. 5.2Remote robot supervision
  3. 5.3Intervention and teleoperation
  4. 5.4Incident and ticket management
  5. 5.5Standard operating procedures
  6. 5.6Shifts and incident escalation
  7. 5.7Communication with the plant
  8. 5.8Mission exception management
  9. 5.9Logging and traceability
  10. 5.10Practical: procedure for managing a blockage
  1. 6.1Root cause analysis of stoppages
  2. 6.2Pareto analysis of fleet errors
  3. 6.3Anomaly detection
  4. 6.4Predicting component failures
  5. 6.5Battery health
  6. 6.6Condition-based maintenance of robots
  7. 6.7Trend analysis
  8. 6.8Models with Python and scikit-learn
  9. 6.9Validation of predictive models
  10. 6.10Case study: predicting drive wheel failures
  1. 7.1PDCA cycle applied to fleets
  2. 7.2Periodic KPI review
  3. 7.3Route and zone adjustments
  4. 7.4Battery charging optimisation
  5. 7.5Comparison between shifts and centres
  6. 7.6Benchmarking between fleets
  7. 7.7SLA management with suppliers
  8. 7.8Reporting to management
  9. 7.9Data-driven culture
  10. 7.10Laboratory: analysis of improvement after a layout change
  1. 8.1Operations analysis
  2. 8.2Data architecture design
  3. 8.3KPI definition
  4. 8.4Telemetry pipeline
  5. 8.5Dashboards
  6. 8.6Control centre procedures
  7. 8.7Predictive maintenance model
  8. 8.8Continuous improvement plan
  9. 8.9Report and presentation
  10. 8.10Final review with the tutor
Methodology, software & labs

How you'll learn

100 % online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetable: 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 Grafana, InfluxDB, OpenTelemetry, Eclipse Mosquitto, Python with pandas, in free, academic or evaluation versions. The trials are based on real procedures for analysing fleet availability and utilisation, detecting anomalies in robot data and managing incidents in a control centre. Assessment is continuous per module, plus the final integrating project.

Accredited laboratories(EN ISO/IEC 17025) with a rotor test rig, EMC/Lightning pre-compliance, HIL/SIL, vibration/acoustics.
Evidence-driven Master's Thesis:safety case, test plan, compliance dossier and operational limits.
Industry mentoring:lecturers with experience in training, , eVTOL/UAM and flight test.
Flexible delivery(hybrid/online), international cohorts and support from SEIUM Career Services.
Ethics and safety:a safety-by-design approach, with cyber-OT, DIH and compliance as its pillars.
Capstone project

Build it end to end

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

Analysis of Operations

Identify the relevant operational data of an AMR fleet.

Data Architecture Design

Design scalable telemetry architectures.

KPI Definition

Define availability, utilisation and performance KPIs.

Telemetry Pipeline

Build dashboards for different profiles.

Dashboards

Organise an operations control centre.

Career opportunities

Where this takes you

Robotics operations analystControl centre supervisorIndustrial data engineerAMR fleet managerPredictive maintenance engineerContinuous improvement engineer
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 texts.

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 totals 800 hours, spread over 6 to 8 months. That is between 10 and 15 hours a week on average, compatible with a full-time job.

You work with Grafana, InfluxDB, OpenTelemetry, Eclipse Mosquitto, Python with pandas. Free, academic or evaluation versions are used, and the tutor indicates the open-source alternative where one exists.

A SEIUM own diploma on passing the continuous assessment and the final integrating project. It 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 programme. Check the credit recognition policy when you enrol.

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