AESOP - Advanced Engineer Scheduling Optimisation & Prediction

AESOP - 高级调度优化工程师

• 批准号: 720784
• 金额: $ 28.81万
• 依托单位: MPL SYSTEMS LIMITED
• 依托单位国家: 英国
• 项目类别: GRD Development of Prototype
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=720784
• 关键词: AESOP; Advanced; Engineer; Scheduling; Optimisation

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.

现场服务工程师的有效调度是很难实现的。目前的方法是人力密集型的，在最后一分钟或实时更改是具有挑战性和破坏性的。这意味着提供响应服务是昂贵的，需要大量的“随需应变”工程师，但由于出现意外问题，仍可能无法按要求交付。“高级工程师调度优化与预测”（AESOP）该项目将建立一个独特的客户服务应用程序原型，以便能够实时响应现场服务工程师的工作计划。先进的预测调度将结合联合收割机：1）使用有关交通流量、天气、日历事件等的实时数据馈送; 2)通过物联网（IoT）基础设施从部署的机器和设备中获取数据; 3）客户对预约时间的偏好;以及4）所有这些都与工程师工作量、可用性、位置和技能集相关的信息。新方法的好处包括：a）机构可将整体服务维修、策划及行政成本减少最少50%，并可节省每项服务的时间，每年可大幅节省服务人员的成本; B）预测-通过使用物联网设备报告的信息进行基于预防性维护调度将显著降低整体维护成本，通过主动调度实现，从而需要更少的意外/计划维护行程;c）客户将获得关于何时进行服务访问的更准确信息。客户还可以更好地控制何时安排他们的服务访问，从而减少等待工程师到达的时间。