Optimizing Asset Management with IIOT

Asset Optimization is a structured approach to improving the effectiveness of overall asset management by classifying, defining, scheduling and implementing initiatives for better performance and decision making.Asset-intensive organizations are looking for ways to amplify productivity, enhance efficiency, reduce operational costs and improve system uptime through the Industrial Internet of Things (IIoT).

IIoT has already established a presence in asset-intensive industries. A survey conducted by Forrester Research has found that among industries such as manufacturing, construction, energy, aerospace and transportation/logistics, 66 percent of respondents stated that they have already implemented or plan to set upIoT technologies for asset management purposes.

Asset optimization through IIoT-generated data provides benefits across the supply chain. by facilitating mass data compilation from assets.Using embedded monitoring tools allow the assets to consistently communicate the state of their thermal properties, lubrication levels, vibrations and other key indicators of asset health. This data helps asset management teams to spot deficiencies before they lead to impromptu downtime. 

IIOT Based Solutions for Asset Optimization:

  • IoT and Predictive Maintenance (PM)to reduce maintenance costs:

IIoT solutions can benefit any asset-intensive organizations especially those that stand to benefit from predictive maintenance approach. Implementing a predictive maintenance strategy presents the solutions to catch problems before they occur. By detecting issues before they become apparent, monitoring tools which provide early warning notifications before failure have become a need. To avoid problems that can slow or halt production, equipment must be monitored as frequently as possible. This analytical maintenance strategy decreases unplanned downtime, reduces costs and improves asset performance.

  • Condition Monitoring (CM) for greater uptime and asset longevity:

Asset-intensive industries should consider condition monitoring (CM) for critical assets to improve the effectiveness of their maintenance resources. Condition based monitoring involves regular checks like examining temperature, pressure, vibration, voltage imbalances. If any of these conditions are outside acceptable parameters, then it calls for maintenance investigation. This kind of condition-based maintenance is predictive in nature and can help increase asset uptime, longevity and reduce asset lifecycle costs.Rather than executing maintenance based on a set interval, listening to the assets can provide valuable insight.

  • Industrial Platform as a Service minimizes unplanned downtime:

Billions of dollars are spent on the maintenance of industrial equipment every year and massive data is collected about the performance of assets. It has previously been very tricky to accumulate, evaluate and perform operations on this valuable information to save maintenance costs and improve performance. A (cloud) platform-as-a-service is needed to collect sensor data from industrial equipment that aggregates, analyzes and performs considerable actions on the collected data. This will help industrial customers to use the results to optimize asset performance and minimize downtime.

Having deployed various recent IIoT projects for clients including Fibro and Advanced Energy, we are seeing predictive analytics deliver tremendous value to operations. It’s exciting to see optimization models for building operational efficiencies are now being delivered leveraging data captured from machinery and goods, and an enormous transformation towards becoming a truly data-driven organization.

 

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