StartUs Insights_Global Startup HUB Analysis_Predictive-Maintenance-noresize

Predictive Maintenance: A Global Startup Hub Activity Analysis

We conducted an exhaustive analysis of the global geographic distribution of 1.654 predictive maintenance startups to identify the hubs with the most activity. Explore the global predictive maintenance landscape & meet some of the most promising startups in the field!

In Industry 4.0, maintenance is expected to do more than just reduce downtime. Predictive maintenance and condition-based monitoring, a prerequisite for building such predictive models, use advanced analytics to significantly increase equipment or machine runtime by identifying early signs of trouble and promptly alerting the operations manager.

Top 5 Global Predictive Maintenance Startup Hubs

Using our Startup Search Engine covering 1.000.000+ startups & emerging companies, we analyzed the geographic distribution of global activity in predictive maintenance. We identified 25 regional hubs (hub = the regional geographic center of activity for a specific topic; it covers the center point with a radius of 100km) that see high activity in developing predictive maintenance solutions. According to our data, the Greater Silicon Valley area, London, The Hague, New York City, and Houston account for 17% of global activity in this field.

StartUs Insights_Global Startup HUB Analysis_Map_Predictive-Maintenance-noresize

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The US accounts for 38% of global activity while European hubs in the UK, Netherlands, Germany, France, Spain, and Belgium account for more than 20% of activity in predictive maintenance solutions. Innovations are mainly driven by technologically advanced industries like automotive, manufacturing, and oil & gas that are already present in these countries. India, China, Singapore, and Sydney are expected to see the highest growth over the next few years due to the presence of various manufacturing units and growing demand from the automobile, transportation, and consumer electronics industries. Asian countries also see a rise in industrial safety regulations, which is set to drive growth for predictive maintenance. While Africa and South America have no hubs of activity yet, they continue to see a rise in the number of startups working on predictive maintenance solutions.

Let us have a look at some of the predictive maintenance startups from the top 5 hubs globally:

#1 Greater Silicon Valley Area | 87 Startups & Emerging Companies

Home to some of technology’s biggest names, Silicon Valley is also a global innovation hub, having produced several disruptive ideas over many years. It can seem fragmented and inaccessible to newcomers but several people have provided detailed guides on how to access the numerous innovations that are taking place here.

Based in Mountain View, SenseGrow develops ioEYE Predict, a suite of Internet of Things (IoT) based packages that include high-precision vibration sensors, a web application, and machine learning models to help smart manufacturing units sense and predict machine faults. They intend to help factories shift from costly reactive maintenance to predictive maintenance.

#2 London | 73 Startups & Emerging Companies

Globally active, London houses innovations from a diverse set of industries, including Industry 4.0. Modernization of their industrial sectors results in a high activity of predictive maintenance solutions.

London-based startup Prognostic develops end-to-end Platform-as-a-Service (PaaS) solutions to enable the implementation of the Industrial Internet of Things (IIoT). Their eponymous platform uses artificial intelligence (AI) to increase asset lifetime by implementing condition monitoring using historical, real-time, and other external data such as vibration, noise, and temperature while building failure patterns.

#3 The Hague | 42 Startups & Emerging Companies

The Netherlands is home to a vibrant, and collaborative startup ecosystem. Innovation friendly policies and access to high-quality incubation centers and research and development facilities make it an attractive place for startups.

Based out of Rotterdam, Clockworks Data Innovation develops customizable applications using machine learning, computer vision, and predictive analytics. They create predictive maintenance solutions to calculate the remaining lifetime of an asset and to identify faults before they occur for a range of capital intensive industries. They also provide remote sensing and process optimization services for clients.

#3 New York City | 42 Startups & Emerging Companies

Strengths in advanced manufacturing and robotics, cybersecurity, and health and life sciences subsectors make New York City one of the largest innovation hubs in the world.

Operating from New York City, Prediccio develops its eponymous asset monitoring platform that helps lower maintenance costs and increases asset performance. They use hardware sensors on the most critical assets for condition monitoring, performance monitoring, and overall equipment effectiveness. The company gathers and analyzes asset data in the cloud that can be accessed from any web browser.

#5 Houston | 37 Startups & Emerging Companies

Texas is going through a period of rapid growth in the number of startups aided by strong community engagement and corporate interest in innovations. Houston is the major hub for information technology but hosts a diverse range of innovations from other industries, including in Industry 4.0.

The US-based startup Sensoleak develops software solutions for the energy and utility sectors, consisting of a real-time monitoring system that combines artificial intelligence (AI), machine learning (ML), engineering logic, physics, and the internet of things (IoT) to detect, predict, and prevent failures of any kind. They are able to achieve a low rate of false alarms by using explanatory variables.

What’s next?

To build truly smart factories, the industrial sector must build the capabilities necessary to implement Industry 4.0 solutions like condition monitoring and predictive maintenance. As machines start making decisions on their own, the workforce will look to develop virtualization of the factory to ensure smooth operations. These developments will allow predictive maintenance to become the standard method for maintaining facilities, equipment, and machinery.

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