Viking Analytics offers a machine health monitoring platform that employs real-time data analytics and predictive maintenance algorithms to evaluate the operational status of industrial machinery. This technology helps companies minimize downtime and maintenance expenses by detecting potential equipment failures before they happen.
Funding
$3.7M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional threshold-based alarm systems for machine health monitoring often generate numerous false alarms, leading to wasted time and resources for maintenance teams. Manual tuning of these thresholds is also required to accommodate different machine operating modes, adding complexity and inefficiency.
Solution
Viking Analytics offers an AI-powered machine health monitoring platform that leverages unsupervised machine learning algorithms to analyze vibration data and detect anomalous machine behavior without relying on manually set thresholds. The platform automatically identifies potentially problematic machines and predicts failures in advance by recognizing machine operation modes and detecting early signs of suspicious behavior. Its MultiViz software streamlines the diagnostic process by recommending the most relevant measurements for further analysis, reducing the need to manage large volumes of vibration data. The system is compatible with various machines, processes, and sensor hardware, and is accessible as an API for OEMs and as software for vibration analysts and maintenance companies.
Target Audience
The primary target audience includes maintenance companies, vibration analysts, and OEMs seeking to remotely monitor machines, efficiently analyze data, and integrate predictive maintenance capabilities into their equipment offerings.
Features
- Unsupervised machine learning for asset analysis, enabling early discovery and prevention of machine failures
- Automatic detection of suspicious machines without threshold-based alarms
- Identification of potential pre-failure modes for any machines and processes
- AI-driven recommendations for detailed diagnostics and root cause analysis
- Compatibility with all machines, processes, and sensor hardware
- Accessible as an API for OEMs and as software for vibration analysts and maintenance companies
- MultiViz application for vibration condition monitoring and valve condition monitoring