In the best case, sensors in machines or buildings continuously transmit data to digital applications – in the majority of cases a centralized maintenance-management system (CMMS). Smart maintenance software uses this data for different purposes. How Smart Maintenance Software Digitises Manual Processes.
For instance, a maintenance technician may receive an alert that the temperature of machinery is getting too high. The software can then automatically create a work order and dispatch a vendor without manual intervention. How Smart Maintenance Software Digitises Manual Processes.
Automated Work Orders
Using a work order system helps to streamline communication, providing all team members with crucial information about their assignments in one place. This includes important details like the equipment and tools needed, deadlines, and attachments. It also provides an overview of the project to identify any potential bottlenecks, allowing management to intervene quickly.
Having a work order process also eliminates the need to send paper work orders back to the office, which saves valuable technician time and improves your mean time to repair (MTTR) metric. And it allows managers to keep track of all completed work, including the time spent on a task and resources used to complete it. This data auto-populates any reports you set up in your Redlist dashboard, making it easier to monitor and measure success.
Adaptive Scheduling
As metal manufacturing continues to evolve, plant managers are embracing adaptive scheduling to improve the efficiency and effectiveness of maintenance tasks. Whether a production interruption occurs due to a natural disaster or a short-lived anomaly, smart technology can help mitigate disruptions and maintain productivity by adjusting work orders.
A good example of this is adaptive scheduling, a process that analyzes the current status of a schedule and changes it to minimize the impact of the disruption (Mourtzis et al., 2021c).
EQ2 LLC, Charlotte, NC, offers the HEMS CMMS software that provides adaptive scheduling features, such as call escalation and call assignment modules. It also has a rescale module that allows the software to resize jobs even when they have large state and enables maintenance teams to continue to execute their job without a network connection.
Predictive Maintenance
In the manufacturing world, technology continues to advance at a breakneck pace. The current industrial revolution dubbed Industry 4.0 relies on advanced technologies like AI, machine learning, the Internet of Things (IoT), and predictive maintenance to redefine existing manufacturing standards.
Predictive maintenance uses sensors and data analytics to detect warning signs that a machine is prone to failure. This enables you to service equipment and machinery before it fails, saving you money on costly repairs.
It also saves you from unexpected downtime and lost revenue. For example, the oil and gas industry proactively monitors oil temperature, speed, and vibration to prevent equipment breakdowns.
To utilize predictive maintenance, your CMMS must be able to record data from sensors and critical equipment. Then, it can use the data to create advanced prediction models and analytical tools. These tools can include sound monitoring, which converts high-frequency sounds from worn bearings, mechanical stress, and electrical problems into audible or visual alerts.
Artificial Intelligence
Maintenance tasks can be complex and tedious, especially for teams who have to deal with a large number of work orders. For example, a small team of facilities management experts handling maintenance requests for a city water-treatment facility in Canada found it challenging to keep up with the work demands, even when tracking everything manually on a whiteboard.
Using smart maintenance software, the team can easily manage work orders and track progress while focusing on their core responsibilities. This helps them to avoid expensive production delays caused by unplanned maintenance.
Smart maintenance solutions digitise manual processes by collecting, transporting and aggregating data from machines and infrastructure into a single CMMS application platform. They then perform predictive analysis, turning early warning signals into a clear action plan. This means that a company that produces COVID-19 vaccine vials can predict when their equipment might fail, giving them time to alert employees and take corrective action without any production losses needs read more hear.
