AESOP - Advanced Engineer Scheduling Optimisation & Prediction

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Efficient scheduling of field service engineers is very difficult to achieve. Current methods are human-intensive and it is challenging and disruptive to make last minute or real-time changes.This means that providing a responsive service is expensive, requires a substantial number of ‘on-demand’ engineers and can still fail to deliver as required due to the occurrence of unexpected problems.The ‘Advanced Engineer Scheduling Optimisation & Prediction’ (AESOP) project will prototype a unique customer service application to enable real-time responsive scheduling of field service engineers’ work programmes. The advanced predictive scheduling will combine:1) the use of real-time data feeds concerning traffic flows, the weather, calendar events, etc.;2) data from deployed machinery and equipment through an Internet of Things (IoT) infrastructure; 3) customer preferences for appointment times, and 4) all correlated with information about engineer workload, availability, location and skill set. The scheduling will include optimised sequencing of the various field service activities and the best routes between them.The benefits of this new approach are:a) Organisations will be able to reduce their overall service maintenance, planning and administration costs by at least 50% and be able save time for every service activity, making a significant annual cost saving across the service workforce;b) The predictive-based preventative maintenance scheduling through the use of information reported by IoT devices will significantly reduce overall maintenance costs, achieved through proactive scheduling thereby requiring fewer unexpected/planned maintenance journeys;c) Customers will receive more accurate information about when their service visits will take place. Customers will also have greater control over when their service visits are scheduled thereby reducing wasted time waiting for an engineer to arrive.