Rickard Sörlin

Talking SCADA — Academic Product Case

University of Skövde → Blekinge Institute of Technology · Aug 2025 – May 2026

Explored how AI could let a building explain hidden energy waste, likely causes and useful next investigation steps in plain language while keeping operational decisions with people.

• • Framed the user problem, intended users and Jobs to Be Done for building operators, facility managers and energy teams.
• • Developed the concept from discovery through product definition, a bounded read-only MVP, PRD and SRD, requirements traceability and Cost-Value-Risk prioritisation.
• • Connected customer and business value through Software Value Map, Business Model Canvas, packaging, sourcing and staged commercialisation planning.
• • Defined the next validation step with representative users and real building data; intended energy, cost and emissions gains remain unmeasured.

Technical context: Conceptual multi-agent decision support using operational time-series data, building-system relationships and domain context; a design direction to compare with simpler support.

AI-Powered Troubleshooting Assistant

Mälardalens Industrial Technology Center (MITC)

Explored how an AI-enabled assistant could reduce downtime in industrial environments by translating machine signals, alarms, and documentation into actionable insights.

• • Conducted discovery interviews with operators and testbed teams to understand workflows and identify key pain points.
• • Defined and validated the core problem: dependency on specialist knowledge during incidents.
• • Designed and prototyped an AI assistant providing root-cause insights and step-by-step guidance.
• • Evaluated usability and user value through real-world testing with industrial partners.
• • Demonstrated how AI-supported decision guidance enabled faster incident resolution and reduced reliance on specialists.

Technical context: RAG-based architecture, OPC UA integration, industrial control systems.

Uncertainty-Aware 48-hour Wind Power Forecasting

Thesis — Mälardalen University & Electrification Hub

Explored how AI-driven forecasting supports decision-making under uncertainty in energy systems.

• • Identified decision-making under uncertainty as a key challenge for energy planning and operations.
• • Developed a data-driven forecasting solution using real-world wind and weather data.
• • Delivered probabilistic forecasts supporting planning, optimisation, and flexibility scenarios.
• • Demonstrated how uncertainty-aware forecasts enable improved planning, load balancing, and energy optimisation.

Technical context: Temporal Fusion Transformer with probabilistic forecasting.

Schneider Electric

Nordic responsibility for strategic customers and prioritisation of defects and improvements with R&D for EcoStruxure Building Operation and its edge-controller ecosystem, in an international, English-speaking environment.

• • Own the largest and most strategic VIP customers across the Nordic region.
• • Turn recurring Nordic field cases into structured product feedback and enhancement proposals for EcoStruxure Building Operation and its edge IoT ecosystem, prioritised with R&D by customer impact, technical risk and business relevance.
• • Support and mentor Level 2 advanced support engineers across the Nordic region through escalation, technical guidance and knowledge sharing.

Schneider Electric

Led customer and technical discovery for complex digital platform solutions across healthcare, pharmaceutical, data-centre and other mission-critical environments.

• • Developed and presented technical solution proposals to internal management, sales and customer stakeholders, weighing customer value, feasibility, lifecycle risk and cost.
• • Held end-to-end technical ownership from problem definition and requirements through integration, validation and delivery.
• • Aligned engineering, sales and customers around a shared solution direction; represented Schneider Electric at KTH Live-In Lab and mentored technical teams.

Schneider Electric

Sweden's national technical expert for a digital building platform and its ecosystem of edge controllers, working with Product Owners, Global Product Support and R&D.

• • Turned recurring field issues into structured product feedback and enhancement proposals, prioritised critical defects and validated releases with R&D.
• • Owned a reusable HVAC deviation-management capability that turned operational data into actionable insight for troubleshooting and energy optimisation.
• • Supported product lifecycle through release validation, deployment readiness and rollout risk assessment.

Schneider Electric

Delivered digital solutions for building operation and energy optimisation in close collaboration with customers and operational teams.

• • Worked with customers on discovery and requirements, translating operational needs into solution design.
• • Held technical ownership from solution design through delivery and operational handover.
• • Collaborated with R&D as a quality tester and mentored teams on platform capabilities.

Blekinge Institute of Technology

Courses: Product Management & Portfolio Strategy, Strategy & Business Models, Leadership, Product Requirement Management, Agile Process & Project Management (Scrum).

University of Skövde

Courses: Innovation in Practice.

Umeå University, Linköping University, Mälardalen University

Courses: Predictive Data Analytics, Natural Language Processing, Deep Learning for Industrial Imaging, Autonomous Systems.

Mälardalen University (MDU), Sweden

Courses: Interaction Design, Deep Learning, Machine Learning (Advanced), Ethics, Artificial Intelligence 1 & 2, Statistics, Software Engineering for AI (agile development, user stories, backlog structuring, UML, requirements prioritisation).

Sjödals Gymnasium, Sweden