Asset performance management is considered an important operational metric across the housing sector – optimising reliability, availability and safety. Organisations within the housing sector are transitioning from reactive to preventive to predictive maintenance strategies, resulting in significantly reduced asset downtime and notable increases in productivity, efficiency, and profitability.
Maintenance repairs can be expensive and time consuming, therefore it’s important to put processes in place in order to minimise and prevent them. Predictive maintenance software uses condition monitoring tools to monitor the performance and condition of equipment and determine when maintenance should be performed. The software predicts possible defects and estimates when they require fixing before a likely failure. As part of an organisation’s maintenance strategy, predictive maintenance differs from preventative maintenance whereby routine repairs and maintenance are scheduled to take place.
Combined with the Internet of Things (IoT), predictive maintenance software evaluates the performance of an asset providing information in real time. This information is provided through capturing data from IoT enabled sensors. This data is then analysed and actioned to prevent failures occurring. Predictive maintenance sensors include monitoring equipment which can detect a variety of things such as vibrations, temperature or humidity.
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 sector, allowing organisations 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 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 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 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.
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 housing sector.
Often organisations spend more time reacting to issues rather than preventing them from occurring. With predictive maintenance software in place, businesses can benefit from improved efficiencies and reduced costs.
Predictive maintenance software provides organsations with the ability to:
- Reduce costs associated with ordering spare parts and technicians’ costs related to labor time
- Optimise maintenance resources and increase workforce productivity with more time to spend on other jobs
- Maintain and improve product quality of equipment while preventing failures, breakdowns and downtime
- Improves overall availability of equipment in organisations
- Increase compliance and improve safety for staff fixing equipment as the software pre-empts when failures are about to occur rather than when in operation
How Totalmobile enables great Connected Field Service IoT
Totalmobile provide a suite of core products that provides organisations with a leading Connected Field Service IoT solution, leading to an increase in workforce capacity, cost efficiencies, compliance with standards and the overall customer experience.
IoT Enabled Predictive Job Creation: Sense from Totalmobile provides IoT technologies, included connected sensors and rules engines that allow the creation of work to be automated and assigned without the need for human intervention. Read more about Sense
Cloud Based Job Management: Connect from Totalmobile is a cloud based, intuitive job management solution that provides visibility and control of complex tasks, enabling the streamlined delivery of work. Read more about Connect
Dynamic Workforce Scheduling: Optimise from Totalmobile offers a dynamic scheduling solution that ensures the efficient allocation of resources to achieve complex scheduling goals based on time, location, availability and service levels. Read more about Optimise
Mobile Workforce Management: Mobilise from Totalmobile is a mobile working solution that empowers the mobile workforce with the ability to capture intelligent data and access the information they need to deliver services effectively, first time. Read more about Mobilise
Service Data and Analytics: Insight is a data and analytics solution that provides organisations with access to rich data, offering deep insights into the delivery of field services. Read more about Insight.