Improved Product Decisions with Machine Learning

Written By: Michelle Duke Hopkins
  • 8/3/2016

Data is one of the biggest challenges and biggest opportunities in the Internet of Things. It is also creating the most compelling business case for investing in IoT solutions.

A report by ABI research says “across the enterprise sector, the business case for Internet of Things (IoT) deployments is increasingly based on big data and analytics. Mere connectivity already allows valuable enhancements to products and processes, such as remote monitoring and service, but the stage where IoT truly becomes transformative to businesses is when it crosses over with analytic tools and modeling.”

At this week’s NIWeek 2016, the transformative business value of IoT data and analytics in an industrial environment was highlighted with a demo by Flowserve, one of the world’s largest manufacturers of pumps, valves, seals and components to the process industries. Many benefits and opportunities are realized with IoT data and analytics. FlowServe’s demo showcased one of the most compelling use cases— predictive maintenance to reduce unplanned downtime in critical assets.

Reducing downtime of critical assets and keeping manufacturing plants up and running is FlowServe’s mission. In manufacturing, unplanned downtime leads to billions of dollars lost each year. But with data coming from connected industrial assets, downtime can be minimized. With the combination of IoT analytics and machine learning these critical assets can unveil a comprehensive data story about a specific piece of equipment that provides more visibility into the combination of factors that lead to failures such as the operating environment. With this visibility and real time analytics plus machine learning, manufacturers can know when an asset is going to fail and how it is going to fail and can take preventative measures to avoid downtime.

Arc Advisory Group says “using IIoT and analytics for condition monitoring and predictive maintenance can help ensure high uptime for critical assets – particularly among those 82 percent of assets having a random failure pattern.” For FlowServe, IoT data provides predictive analytics that keep critical assets, like pumps, up and running ensuring that their customers experience a decrease in unplanned downtime.

  • CAD
  • Retail and Consumer Products
  • Connected Devices

About the Author

Michelle Duke Hopkins

Michelle Hopkins is Managing Editor of Product Lifecycle Report. She has spent her career in marketing and communications in the technology industry focused primarily on enterprise software. Michelle enjoys researching and writing about how new technology trends and innovations can transform business processes and impact customer relationships, competitive advantage and overall revenue and profitability. Frequent topics include the Internet of Things, manufacturing, service lifecycle management and STEM.