Decision automation through predictive maintenance. The future of infrastructure monitoring and smart city management calls for cooperation between various parties - equipment manufacturers, network operators, technology service providers and data analytics businesses among others.
By leveraging IoT to evaluate equipment performance, businesses can predict and plan for parts repair or equipment failure before it occurs. According to Gartner, it is projected that decision automation in the form of predictive maintenance will generate the highest business value for organisations with heavy assets, According to a report by PwC, benefits of predictive maintenance includes:
Reducing maintenance costs by 12%
From unexpected failure costs, to unplanned downtime and unnecessary maintenance costs, each asset has multiple associated costs which can be saved through improved maintenance planning. Using IoT, historical data and sensors can be used to make accurate predictions about the asset’s health, utilisation and possibility of failure to allow a business to plan ahead. Furthermore, predictive maintenance allows the systematic scheduling of the optimal maintenance and inspection routine.
Extending the lifetime of an asset by 20%
Through predictive maintenance,monitoring and optimisation of assets for improved performance would allow a business to gain better visibility into their assets via real-time monitoring. With schedule maintenance and repairs, the lifetime of an asset can be extended
Increase asset utilization by 9%
Unplanned downtime as a result of equipment failure can incur high costs by disrupting the production process. IoT-based predictive maintainers increase efficiency by identifying the root cause and setting up processes to address these causes. Predictions on machine failure can also be made to allow timely maintenance to improve asset availability, reliability and performance.
Reduce safety risk by 14%
Predictive asset maintenance enables businesses to address safety risks and potential equipment malfunctions before it impacts employees. Efficient actions to mitigate safety risks can be taken to identify potential hazardous working conditions and improve the working environment. Predictive maintenance can also be integrated with human capital management (HCM) solutions, keeping exposure levels below the threshold, complying with regulatory requirements.
Looking to the future, sensor-based predictive maintenance would be a key component of smart city infrastructure and management. If your company possesses a technology which you think has potential in the Chinese market, feel free to contact us at info@summeratlantic.com for a free evaluation of your company’s potential in the Chinese market.
Thank you for reading and we look forward to working with you.
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