From Reactive to Predictive: Smart Asset Management with GeoPal

Asset performance management is considered an important operational metric across the Utility industry - optimizing reliability, availability and safety (Gartner). Organisations within the Utility Industry are transitioning from reactive to preventive to predictive maintenance strategies, resulting in significantly reduced asset downtime and notable increases in productivity, efficiency, and profitability.

Deloitte notes that whilst traditionally the Utility industry has employed numerous maintenance techniques to identify failures models and limit asset downtime, the emergence and availability of new connected technologies enables machinery to automatically do this. Implementing smart technologies maximizes the lifespan of machine components whilst simultaneously avoiding asset failure and unnecessary operational downtime. Poor maintenance strategies have been reported to reduce productive capacity from between 5% to 20% yearly (McKinsey). Field driven studies also demonstrate that unplanned maintenance downtime bears a heavy financial burden - costing an estimated £40 billion yearly. Data driven, analytical solutions such as IoT and mobile sensors are enabling a new approach to asset management strategy across the utility sector, allowing organisations in the Utility Industry to circumnavigate the operational and financial burdens associated with traditional break-fix models.

Asset management strategies often fall into one of the following four categories, each with varying challenges and benefits; Reactive maintenance, Planned maintenance, Proactive maintenance, Predictive maintenance.

Reactive Maintenance

Reactive maintenance is the most traditional and least-advanced asset maintenance strategy. It involves repairing or replacing machinery at the point of failure. As reactive maintenance requires machine failure to occur before action is taken it results in significant unplanned downtime which disrupts operational continuity. In reactive maintenance, machine failure is often catastrophic, requiring total remediation at significant cost to the organisation.

Planned Maintenance

Planned maintenance involves pre-planned repairs and maintenance activity, replacing components regularly and before the point of failure. Whilst downtime is scheduled, planned maintenance still results in operational disruptions as machines are ‘offline’ for maintenance periods. Planned maintenance is not considered a cost-effective maintenance strategy, as it requires a ‘spare parts’ inventory and involves replacing components prematurely, before their lifespan has ended.

Proactive Maintenance

Proactive maintenance involves identifying the ‘root problem’ rather than the ‘symptom management’ approach. Identifying and preventing key machine failures before they occur, reduces wear and tear, thus increasing the lifespan of the machinery. Reduced machine breakdowns result in a decreased need for significant repairs, downtime, and inventory.

Predictive Maintenance

Smart connected technologies, such as IoT and remote sensors have allowed for a new and more efficient model of asset management - predictive maintenance. While traditionally, investing in the technology required to implement a predictive strategy has been associated with a significant financial burden, the increasing availability of cost effective and customizable solutions have facilitated the implementation of predictive maintenance across the utilitity industry.

Predictive maintenance involves a data driven, analytical ‘smart’ approach. Data is collected from connected smart machinery, through devices such as IoT and remote sensors, transmitting data to the end user on when and where a potential failure may occur. Accordingly, components efficiency and lifespan are maximized whilst simultaneously limiting downtime, unnecessary expenditure and worker risk. McKinsey notes that predictive maintenance not only extends equipment lifespan but can eliminate up to 30% of the standard maintenance routine and up to 50% of equipment downtime, garnering significant results for organisations profitability, productivity and continuity.

The consistent data flow and end-to-end transparency afforded by ‘connected’ and ‘smart’ machinery allows for maintenance agility. Emergency situations, unforeseen outages and related critical system failures can be predicted and addressed before damage ensues. This degree of visibility significantly improves safety, strategic decision making and operational efficiency.

Implementing Predictive models with GeoPal

By developing industry-specific solutions powered by IoT and GeoPal’s Mobile Workforce App, we have managed not only to transform our clients’ workforce productivity and asset availability but have also contributed to help them achieve consistent levels of service excellence. GeoPal is an IoT enabled Cloud Service and Mobile App that transforms Asset Management and Field Service Organisations from a reactive, break-fix service model to a predictive model.

GeoPal's IoT-enabled mobility platform and intelligent job dispatch allows organisations with assets in the field to eliminate costly, reactive maintenance, leading a shift towards a predictive model of maintenance. With IoT sensors on assets, alarms are raised when failures occur - before it’s too late. These alarms can automatically trigger work orders that are sent to field technicians' mobile devices, maximizing asset uptime.

With GeoPal, once an IoT device is connected, the potential to not only send and/or receive information, but to implement responsive processes, quickly delivers results – driving real business value. Transitioning from a reactive to a predictive model significantly improves key metrics such productivity, efficiency, and ultimately – profitability.

Learn how GeoPal can help you implement a predictive maintenance strategy, request a free demo today.

 

References

https://www.mckinsey.com/business-functions/operations/our-insights/digitally-enabled-reliability-beyond-predictive-maintenance

https://www.gartner.com/en/documents/3706742/mapping-a-route-to-asset-management-and-reliability

https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/how-predictive-analytics-can-boost-product-development\

https://www.capgemini.com/se-en/wp-content/uploads/sites/29/2017/07/predictive_maintenance_a_starting_point_to_the_digital_manufacturing_journey.pdf

https://www2.deloitte.com/content/dam/Deloitte/us/Documents/about-deloitte/us-a-turnkey-iot-solution-for-manufacturing.pdf

https://www2.deloitte.com/us/en/insights/focus/industry-4-0/using-predictive-technologies-for-asset-maintenance.html

 

 

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