START-UP & SME ELEVATOR PITCHES
Moderator: Ulf Borbos, Project Manager, Swedish Incubators & Science Parks
Enabling smart maintenance with high-quality labeled sensor data
- Stefan Lagerkvist, CEO, VikingAnalytics
- Synopsis: One of the most critical enablers for smart manufacturing (i.e. predictive maintenance and optimization) is high quality sensor data that has been processed and labelled by a subject matter expert. You are "data ready" for smart manufacturing when you realize this enabler. Viking Analytics’ unique platform Multiviz can be used by subject matter experts to convert raw, real-time and historical sensor data to useful information. We also provide professional services to help you design your value adding, data driven solutions.
EmbeDL: Deep Learning Optimization - from R&D to High-Performance, Cost and Energy Efficient AI-Powered Embedded Systems
- Peter Lake, CCO, EmbeDLAB
- Synopsis: EmbeDLis a Deep Learning Optimization technology that helps companies bring Deep Learning from R&D to embedded systems by advanced optimizations, resulting in high-performance, cost and energy efficient products and solutions. EmbeDLOptimization technology is HW aware and has proven algorithm improvements for various industry sectors e.g. Automotive, Robotics/Production, Health Care, AI Data Centers, Video analytic Industries.
AI and Visual Inspection for optimized manufacturing processes
- Lijo George, Partner & MD, Amazing Innovation Sweden AB
- Synopsis: In metal casting foundry, a key challenge exist concerning casting quality. Around 20% of the castings are rejected at various stages of manufacturing depending on the complexity of the design. Reasons range from sand quality, metal composition, pouring related defects, dimensional defects. Computer-vision based inspection using deep learning and video analytics, Models for optimization of processes can get around 10% increase in process yield which can reduce CO2 emission by 0.8 MtCO2/Annum and reduce GHG emissions. Large saving in electrical energy consumption and cost as well. Many such use cases exist across smart manufacturing landscape to take advantage of.
Data driven gamification for improved training and lifelong learning
- Magnus Gerdin, Researcher Industry 4.0, Insert Coin
- Synopsis: Gwen is a science based SaaS for gamification in existing platforms and applications. It is currently used in several different contexts with at focus on learning in higher education and the production industry. A few of the current research projects focus on training of the industrial workforce and student behavior patterns related to expected outcome.
Quantification of business weather impact and decision-aid using machine learning
- Sebastian Haglund El Gaidi, Co-founder, Greenlytics
- Synopsis: Many businesses depend on weather in some way, either as a direct impact on the core business or from indirect reasons such as sales or supply chains. The Greenlytics Platform is an AI-as-a-Service tool that allows to quantify business impact from weather and thereby improve that decision-making process. The platform includes a unique weather database as well as state-of-the-art machine learning tools to process data and put models into production to deliver operational business value.