Manufacturers spend a large portion of their budget on maintenance and plant automation systems, and yet are still plagued by equipment failure, wasteful energy usage and reduced product quality. mVision applies a combination of supervised and unsupervised learning techniques to determine predictors of equipment failure and then continuously monitors for them.
“Machine learning hasn’t hit mainstream in manufacturing, in part due to the effort required to build an accurate model and get the data needed to train the system,” said Alex Bates, Mtelligence chief technology officer. “Meanwhile, plant engineers and maintenance managers have been struggling to make sense of the mountains of data coming from various software packages. mVision enables customers to convert this data into profit.”
The platform includes pre-built adapters for maintenance, automation and condition monitoring systems, converting all data into the MIMOSA open standard data model. MIMOSA (Machinery Information Management Open Systems Alliance) is a mature open standard for modeling asset, maintenance and condition monitoring data.
Alan Johnston, President of the MIMOSA Foundation, commented: “I am genuinely excited to see the Mtelligence team continuing to add more capabilities to their offerings and to make those capabilities available via a SaaS model leveraging the MIMOSA standards. Innovative startups like Mtelligence will be an important part of helping lead the way to gaining more value from new generations of technology and new paradigms such as machine learning. As long-term members of MIMOSA, Mtelligence has realized the value proposition of leveraging MIMOSA standards to enable them to focus more of their resources on adding value to their clients.”
The use of an open standard data model and messaging protocol enables mVision to integrate with a wide variety of data sources, and also enables extensibility. For example, production line health indicators from mVision can be integrated to MES (manufacturing execution system) and ERP packages for optimal scheduling decisions based on capability forecast.
“In continuous manufacturing environments, one of the toughest decisions is when to stop production for preventive maintenance,” Bates said. “Preventive maintenance is often deferred, leading to increased component failures and reactive maintenance. With mVision, maintenance is prioritized based on the actual condition of the equipment.”
mVision was designed to handle very noisy data and variable manufacturing environments. The platform includes a library of intelligent processing filters for sensor data, including statistical process control (SPC) and signal processing algorithms, to improve the signal-to-noise ratio prior to training the mVision agent. The agent learns to differentiate normal operating context from abnormal conditions, and can recognize complex patterns that represent symptoms of impending failure.
Another unique mVision capability is its ability to correlate sensor data with equipment assembly and transactional data coming from EAM/CMMS systems, and the product includes pre-built adapters for SAP, IBM Maximo, Infor EAM, Infor Hansen, Ventyx EMPAC, JD Edwards and others. On the operations side, drivers are provided for plant historians including OSIsoft PI System, Wonderware Historian, GE Proficy, Honeywell PHD and numerous other automation packages. mVision integrates with the full suite of Mtelligence products including Mtelligence CBM, RCM and APM.
By offering a pay-as-you-go SaaS (software as a service) approach, Mtelligence enables manufacturers to take advantage of recent advances in the field of machine learning and neural networks without a large up-front capital investment. The solution supports both on-premise deployment and off-site hosting in Microsoft’s Azure cloud platform.
Mtelligence delivers greater visibility and greater returns on asset performance through our Reliability IntelligenceTM platform. Mtelligence solutions enable customers to maintain the right equipment at the right time, leveraging real-time plant data to prioritize and optimize maintenance resources. The company is a recognized thought leader in Open O&M and MIMOSA open standards, breaking down barriers to reliability by connecting plant and business, enabling increased availability, improved coordination between operations and maintenance, and reduced maintenance costs. We invite you to discover how our predictive analytics and integration software can improve efficiency, reduce operating costs and increase revenues. Mtelligence is headquartered in San Diego, CA, and is privately held.
For more information, visit: http://www.mtelligence.net