大数据能快速跟踪维护解决方案吗?

Leveraging big data can significantly enhance facilities maintenance and engineering, 减少对时间和劳动力的需求. 它是如何工作的??

Buildings can produce a continuous stream of data from the components or equipment under supervision. On average a building can generate 1 million data points per day. 数据几乎是实时传输的, 使用物联网(IoT)协议, 通常包括:

• 到目前为止的总使用时间
• 目前的使用水平
• 部件的尺寸和运动

This data is then compared with standard operational parameters to detect any faults that might be developing. 如果发现任何问题, 警报将被生成, allowing the maintenance team to get ahead of the game and fix any problems before they become more serious. 

Analysis of this data will enable the detection of any anomalies in the operation of mechanical devices: for example, 震动:不寻常的运动或震动模式. These sometimes-subtle signals may indicate misalignment or accelerating wear and tear that could trigger failure or breakdown. Another example is the detection of deviations in heating and cooling performance of HVAC assets which can support businesses with cost savings initiatives.

How Mitie’s 工程师 use data to ensure the success of your maintenance projects

Mitie is one of the UK’s largest strategic outsourcing and facilities management firms. 我们的 工程师 are dedicated to the elimination of disruptive downtime and asset damage. 我们的 ecosystem is designed from the ground up to handle predictive and reactive maintenance. We incorporate multiple factors into our data analysis, including:

• 表演
• 正常运行时间
• 能源消耗
• 运营成本

我们的 maintenance teams work in close coordination with our carbon reduction, 能源, 资产管理专家, to truly optimise equipment usage and maximise the operating life of our clients’ assets.

The data required for such fine calibration is captured in real time and then analysed within our Technical Service Operations Centre. 

这是一个24/7的过程, in which the current operation of a piece of equipment is automatically compared with a comprehensive database of optimal parameters to detect any potential problems that may be developing. 我们的工程团队可以立即关机, 或绕过, 任何此类部件或设备, 支持快速修复或更换.

Mitie helpdesk colleagues and specialist 工程师 work together closely to provide clients with assistance and 科技nical information. Clients can proactively contact our team at any time – via telephone, web表单或Aria, 我们的职场应用.

This data-driven approach to maintenance forms part of the 澳博官方网站科学®, a broad package of transformational solutions available to help our clients achieve lasting change within their businesses. 

Why data-informed maintenance leads to better results

Traditional predictive maintenance schedules require both precise management and sufficient manpower to conduct each check when required. The system stands or falls on accurate, comprehensive record keeping. These logistical challenges can escalate over time, increasing costs and creating staffing and time-management challenges for the business.

基于数据的维护则相反. 使用专业软件, 工程师 can potentially quickly zero in on problems, 甚至是特定的组件, significantly reducing the time required to detect and fix a developing fault. 潜在的商业利益是显而易见的:

• Reduced long-term maintenance costs (because wear and tear is reduced)
• Reduced repair costs (because there are fewer serious faults to fix)
• 更便宜的设备停机时间
• Increased生产力

工程维修: where data meets hardware

Future commentators will undoubtedly look back on our era as the Data Age. 多亏了现代信息技术, data has taken a central place in the fast-paced, 21世纪超级互联的商业世界. Many businesses generate new data points 24 hours a day, seven days a week – and all that data requires sophisticated analysis.

The future of engineering maintenance is one sector where data can intersect with physical hardware to unlock a range of tangible business benefits – and AI maintenance software will provide the key. To fully explore our suite of data-informed management services, 保持联系 今天和米蒂的专家团队一起.