Q . WHAT ARE THE KEY WAYS COMPANIES CAN MAXIMISE THEIR GREEN TECH CAPABILITIES ?
» Field Service & Asset Management scheduling and route optimization engines can be driven by AI and ML . These new apps will schedule both field crews and equipment in a way that minimizes resource use and promotes efficiency .
Delivery of AI and ML-based service , asset management and optimization will be led by innovative , mobile and cloudfirst-based applications . Rather than having Field Service Management and Enterprise Asset Management run through separate programs , companies can run both through a single cloud-native , AI-empowered system .
A modern in-memory , high-capacity scheduling engine that utilizes ML algorithms can also deliver an unfailingly accurate work route optimization schedule . This scheduling engine allows operations to reduce truck rolls , react faster and optimize dispatch call centers , helping businesses lower their carbon footprint .
For example , Hawaiian Telcom is leveraging KloudGin to deploy a fiber footprint throughout the islands , which will allow for more Hawai ' i residents and businesses to have access to broadband . This , in turn , allows more people to work remotely , which reduces commute traffic and reduces the overall environmental impact .
Q . HOW WILL PREDICTIVE ASSET MAINTENANCE CHANGE OPERATIONS AND PROCESSES ?
» Predictive maintenance ’ s goal is to maintain equipment before it breaks down . Maintenance can be scheduled before the point of failure by combining collected data and predictive analytics to estimate when a piece of equipment might fail . Ideally , maintenance should be scheduled at the most convenient and most cost-efficient time , to ensure the optimal lifespan for the equipment .
Imagine if a signal comes from your transformer or hydraulic pump that automatically directs the closest utility field crew - with the right parts and skillset - to conduct maintenance and prevent an asset failure before it happens . Preventing incidents such as water leaks or equipment breakdown will play an increasingly large role towards achieving enterprise ESG goals and increasing community safety .
Predictive asset maintenance ( PdM ) can be bolstered by using ML algorithms to automatically identify defects and predict failures without interrupting operations .
Q . WHAT ROLE WILL CLOUD COMPUTING PLAY IN REALISING NET ZERO TARGETS ?
» Route optimization algorithms based on ML will not only contribute to operational efficiency , but also allow greater fuel efficiency . This helps operations reduce their " truck rolls " and make sure that the technicians arrive safely and on time , with the right expertise and tools .
For example , integrated environmental services company Drain-All deployed a modern digital field force transformation system through KloudGin . In a matter of months , Drain-All ‘ s process automation reduced field report human errors , and created automated work order assignments with more efficient scheduling and dispatch - which led to a consolidation of roles , lowered carbon footprint , and incremental cost savings .
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