Improving Asset Management with IoT and Predictive Analytics

Asset tracking and predictive asset maintenance takes the guesswork out of equipment upkeep and improves the lifespan of the machinery. The use of IoT shifts maintenance from preventative to predictive and gives companies more control over their assets.

 

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Image credit: Capgemini

Due to the high-risk nature of the oil and gas industry, asset management is critically important for energy companies. Faced with health and safety regulations, increasing competition, and decreasing margins, energy companies are seeking ways to improve operational efficiencies. These large-scale operations have equipment in multiple locations with rotating workers. Simply knowing the exact location of the equipment, let alone knowing what might go wrong with it, can be a challenge.

Today’s IoT-based asset tracking solutions enable companies to track all assets at any given time from a centralized location, even across multiple geographic areas. Asset tracking improves resource management and can save money. Further fueling the need for asset management software are regulatory restrictions designed to curb greenhouse gas emissions and the increasing pressure on energy companies to reduce their environmental impact. Asset management solutions can help ensure federal compliance.

The Crystal Ball of Industry 4.0

When tied to predictive asset management solutions, companies can budget for and schedule maintenance more effectively. Predictive analytics uses data mining techniques to analyze current and historic data sets, then creates rules and models to predict future events. 

Unlike preventative maintenance, which relies on manufacturer guidelines and human assessment, predictive asset management software uses machine learning algorithms to forecast maintenance schedules. The need for predictive solutions is growing rapidly. Gartner predicts that by 2022, spending on IoT-enabled predictive maintenance will increase to $12.9 billion, up from $3.4 billion in 2018.

Global technology consultancy Capgemini, a partner in the Intel® IoT Solutions Marketplace, has built an end-to-end solution for predictive maintenance of assets. It is designed for use in various segments, including aviation, shipping/logistics, factories, and energy/utilities, such as power plants. Capgemini’s Predictive Asset Maintenance with Edge Compute integrates predictive and cognitive capabilities, which allows companies to better plan for the operation, maintenance, and decommissioning of assets.

Capgemini’s software monitors and analyzes each asset’s age, location, performance, and other operational attributes. It then analyzes the machine data to predict potential failures before they become catastrophic.

Gaining an Edge on Maintenance

The edge compute capabilities in the Capgemini solution enable each machine to be continually monitored. The collected data is recorded and fed into an artificial intelligence engine, which can identify trends, measure operational efficiency, compare that with historical data related to machine failures, and suggest new services or tweak processes to boost productivity. Additional capabilities can be integrated to detect which repairs are required and when, giving companies more control over operational costs, improving performance and uptime, and extending the life of the machinery.

Powered by Intel® technology, the Capgemini solution integrates connectivity, data flow, data platform, and visualization modules. It tracks assets in near real-time by collecting machine data via programmable logic controllers (PLCs) or sensors on the equipment. The sensors connect to an Intel gateway, which connects directly to the cloud.

Illustration with Intel technology at center of aviation, logistics, manufacturing and utilities

Image credit: Capgemini

The Capgemini software runs on the edge device and collects data from each machine’s internal computer. Processing analytics at the edge reduces transmissions to the cloud, and data is stored locally in case of a network outage.

Users access a customizable, cloud-based dashboard to visualize and track metrics. Operators can also receive notifications via text or email when thresholds are met or maintenance services are required.

Responding to a maintenance failure after the fact is disruptive and costly. Predictive asset maintenance gives companies the intelligence to identify triggers, pinpoint potential failures, and plan for outages, which keeps operations running smoothly.

Intel, the Intel logo, and other Intel marks are trademarks of Intel Corporation or its subsidiaries.

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