5 Top Predictive Maintenance Startups Out Of 135 In Industry 4.0

5 Top Predictive Maintenance Startups Out Of 135 In Industry 4.0

We analyzed 135 predictive maintenance startups. Predictive-Sigma, Semiotic Labs, Presenso, Seebo, and Industrial Analytics are our 5 picks to watch out for. To learn more about the global distribution of these 5 and 130 more startups, check out our Heat Map!

Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups in Industry 4.0. As there is a large number of startups working on a wide variety of solutions, we decided to share our insights with you. So, let’s take a look at promising predictive maintenance solutions.

Heat Map: 5 Top Predictive Maintenance Startups

For our 5 picks, we used a data-driven startup scouting approach to identify the most relevant solutions globally. The Global Startup Heat Map below highlights 5 interesting examples out of 135 relevant solutions. Depending on your specific needs, your top picks might look entirely different.

 

PredictiveMaintenance_in_Industry4.0_Heatmap_StartUsInsights-noresize

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Who are the other 130 Predictive Maintenance Startups?

 

Predictive-Sigma – Smart Predictive Maintenance

Predictive maintenance is the analysis of a network of assets that enables prediction and notification of potential outages. It promises maximum protection of machinery and minimum productivity impact, also at the same time without necessarily increasing the overall system complexity. Spanish startup Predictive-sigma offers a technological platform for predictive maintenance that allows accessing information to increase asset availability and improve the performance of industrial machinery. It ensures to detect the failures of machines in advance and notifies companies to take necessary actions.

Semiotic Labs – Smart Condition Monitoring

Smart condition monitoring is the application of condition-based monitoring technologies, statistical process control or equipment performance. It is used in the early detection and elimination of equipment defects, that could lead to unplanned downtime or unnecessary expenditures. Condition monitoring technology takes into account sensor data, previous inspections, location and condition of the plant, and historical data. Semiotic Labs, a startup from the Netherlands, offers smart machine-monitoring technologies to the manufacturing industry. The solution offered by Semiotic Labs enhances the elimination of unplanned downtime and reduces maintenance tasks and costs.

Presenso – Predictive Analytics

Predictive analytics is a subcategory of advanced analytics and big data that allows the prediction of future events and occurrences based on sets of data from the past. It describes the collection, analysis, and usage of data generated in industrial operations and throughout the entire product lifecycle in the manufacturing industry. It also enables detecting abnormal behaviors of machines without the need for human input. Moreover, it learns and adapts to the desired scenarios by itself. The Israeli startup Presenso provides an Artificial Intelligence-driven industrial intelligence solution for failure prediction using machine learning and deep learning algorithms. Their solution analyzes assets sensor behavior and automatically learns how machines behave with algorithms that are predicting machine failures before they occur.

Seebo – Root Cause Analysis

Root Cause Analysis (RCA) is the process of identifying factors that cause defects or quality deviations in the manufactured product. RCA can be performed using machine learning and big data analytics, and these methods are unbiased and based purely upon historical and real-time data straight from the production floor. Seebo, a startup the USA, focuses on solutions such as predictive maintenance, predictive analytics and offers root cause analysis, using machine learning and probabilistic graphical models.

Industrial Analytics – Digital Twin

Digital twins are continuously learning systems, powered by machine learning algorithms, which makes them adaptive to the changes in the state and configuration of a physical twin. Predictive maintenance solutions powered by digital twins help to precisely monitor equipment health and timely recognize potential anomalies. German startup Industrial Analytics enhances predictive maintenance by feeding the measured data into digital twins of the machines to improve pattern recognition and anomaly detection. This enables artificial intelligence to give only true alarms also to calculate unknown system parameters.

What About The Other 130 Solutions?

While we believe data is key to creating insights it can be easy to be overwhelmed by it. Our ambition is to create a comprehensive overview and provide actionable innovation intelligence for your Proof of Concept (PoC), partnership, or investment targets. The 5 predictive maintenance startups showcased above are promising examples out of 135 we analyzed for this article. To identify the most relevant solutions based on your specific criteria and collaboration strategy, get in touch.

 

Ready to discover your top predictive maintenance solutions?
Ready to discover your top predictive maintenance solutions?




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