Staying ahead of the technology curve means strengthening your competitive advantage. That is why we give you data-driven innovation insights into the manufacturing industry. This time, you get to discover 5 hand-picked artificial intelligence startups impacting manufacturing.
Global Startup Heat Map highlights 5 Top Artificial Intelligence Startups out of 832 impacting Manufacturing
The insights of this data-driven analysis are derived from the Big Data & Artificial Intelligence-powered StartUs Insights Discovery Platform, covering 1.379.000+ startups & scaleups globally. The platform gives you an exhaustive overview of emerging technologies & relevant startups within a specific field in just a few clicks.
The Global Startup Heat Map below reveals the distribution of the 832 exemplary startups & scaleups we analyzed for this research. Further, it highlights 5 manufacturing startups that we hand-picked based on criteria such as founding year, location, funding raised, and more. You get to explore the solutions of these 5 startups & scaleups in this report. For insights on the other 827 artificial intelligence solutions for manufacturing, get in touch.
Invisible AI tracks Manual Assembly Processes
Despite the increasing shift towards digitization and automation, many manufacturing plants globally still employ manual assembly lines. In addition to being prone to errors, human workers also tend to reduce factory productivity by lowering the “base pace” of production. Startups solve this challenge by combining AI with cameras to efficiently track worker performance and identify the bottlenecks to remove.
Invisible AI is a US-based startup offering an end-to-end hardware and software solution to track manual assembly processes. Invisible AI’s proprietary algorithms automate assembly line monitoring using cameras and a no-code platform. The AI platform keeps an eye on assembly operations and delivers actionable insights to factory managers, engineers, operators, and executives. Invisible AI also generates a high return-on-investment (ROI) by improving quality, performance, and operational efficiency.
FactoryPal offers a Machine Learning Software-as-a-Service (SaaS)
Factories deploy various industrial internet of things (IIoT) devices and sensors to monitor their machines. As a next step, manufacturing companies implement enterprise resource productivity (ERP) systems and integrate factory data collection. By building AI algorithms using this data, startups streamline factory operations in a comprehensive manner. For example, with accurate data collection, manufacturing companies improve their overall equipment efficiency (OEE), in turn, reducing maintenance costs.
German startup FactoryPal develops a suite of smart solutions architecture to support business, information, and technical excellence in manufacturing companies. The startup’s FactoryPal Live enables manufacturing companies to digitize their shop floor and obtain a digital real-time view of daily operations. The FactoryPal Boost solution, on the other hand, focuses on centerline efficiency and utilizes machine learning (ML) to constantly optimize for the highest OEE. Finally, FactoryPal Insights is an analytics engine to derive valuable information about the shop floor.
Gimic automates Quality Inspections in Factories
Post-production processes, such as inspection and quality assurance, are prime targets for factory automation. Startups convert simple images and videos into cognitive machines with the help of AI. With this enhancement, cameras prove to be more adept at detecting defects in the final products than humans. Moreover, automating such quality checks significantly reduces the time taken to push products from the factory to the end consumers.
Gimic is a Swedish startup improving the accuracy of quality inspection in factories and production lines. Using cameras and AI algorithms, the startup enables manufacturing companies to reduce errors and spot production defects early in the product value chain. Gimic’s cognitive camera technology is available for different kinds of machines in a factory. For example, the startup’s Helix and Motus solutions streamline rotating machine and in-line inspections, respectively. Octopus is a flexible inspection solution to carry out multiple scans of a single object. Finally, Cotton is a quality system that collects and processes real-time production data from the inspections to extract value and help manufacturing companies make strategic decisions.
Neurisium enables Production Automation
Production and factory managers are looking for ways to derive valuable insights from the large volume of factory data. This data spans production planning, asset health monitoring, reporting, supply chain, and warehousing, as well as sales and revenue information. Moreover, even in seemingly productive manufacturing plants, AI is able to offer numerous opportunities for improvement. AI algorithms achieve this by enabling manufacturing companies to optimize their production and improve decision-making across their factories.
Based out of Estonia, Neurisium is an AI startup improving production line output using data from machines across a line. The startup utilizes ML to help engineers optimize production line processes. Neurisium optimizes production parameters, implements predictive maintenance, and suggests real-time production line improvements. Moreover, the ML solution also offers ways for factories to reduce their scrap rate.
PowerArena reduces Manufacturing Errors through Computer Vision
AI is a powerful tool for manufacturers to understand why their processes fall short of their targets. While some issues are easily handled by humans, AI is able to analyze information at a granular level. Even the slightest anomalies in machine performance are a potential loss of time and money in the future. Hence, integrating predictive analytics with root cause analysis offers valuable insights for factory managers to plan production processes with greater accuracy and avoid downtime or productivity loss.
Chinese startup PowerArena utilizes computer vision to improve worker performance by revealing factory floor inefficiencies. The startup’s AI-based solutions reduce waste for manufacturing companies. The startup’s AI Line Balancer and AI (standard operating procedure) SOP Assistant allows factories to identify bottlenecks and raise productivity. PowerArena also offers an AI Quality Inspector to automate production line quality inspections. This smart manufacturing solution combines computer vision, time study, motion analysis, and machine learning to reveal precisely the areas that need improvement.
Discover more Manufacturing Startups
Manufacturing startups, such as the 5 examples highlighted in this report, focus on assembly line tracking and optimization, predictive maintenance, as well as computer vision-based AI solutions. While all of these technologies play a major role in advancing smart manufacturing, they only represent the tip of the iceberg. To explore more manufacturing technologies, simply get in touch to let us look into your areas of interest. For a more general overview, you can download our free Manufacturing Innovation Report to save your time and improve strategic decision-making.