Lower costs associated with overzealous maintenance by using predictive maintenance tools, and schedule maintenance only when needed.
Boost the productivity of technicians and other maintenance staff by automatic assignment of preventive care work orders and tasks to the relevant open technicians.
Be proactive about the maintenance and replacement of assets before they breakdown. This can be done by keeping track of work orders and trends to stay on top of production levels and thereby minimize costly downtime.
Analyze historical and current data using machine learning-based algorithms to predict and schedule future maintenance and repair tasks.
Detect irregularities and anomalies, and instantly evaluate correlations while making out patterns and trends in the data using machine learning algorithms.
Input complete asset data from the model number and details to its maintenance history. This is in order to facilitate machine learning algorithms to forecast future asset maintenance protocols and recommend predictive maintenance schedules.
Predictive Maintenance is a condition-based proactive maintenance technique that keeps track of and monitors the working condition of assets using smart sensor devices. These IoT integrated sensor devices provide real-time information and help predict when assets need maintenance in order to avoid breakdowns or failure.
Predictive Maintenance is performed using Predictive Maintenance tools. These smart tools help you gauge the working condition of assets and whether they are about to breakdown based on certain IoT sensors installed in these tools. There are different Predictive Maintenance tools such as oil analysis, ultrasonic analysis, vibration analysis, and infrared analysis, which check and analyze different features of assets.
Predictive Maintenance is the maintenance of assets based on predictions. The goal is to schedule maintenance work orders and fix the situation before any mishap occurs and the asset is actually damaged.
IoT devices are smart devices with sensors that observe certain features of assets and study trends and patterns in order to determine when the need for maintenance may occur. When certain conditions have been met and the need has been determined, the IoT device triggers automatic work orders which call for maintenance tasks to be performed on that particular asset.
There are two types of strategies a company can employ when it makes maintenance plans. It can either choose a reactive strategy or a proactive one. A Predictive Maintenance strategy is a form of proactive maintenance strategy which makes use of IoT devices to make predictions about when assets are about to malfunction. This saves more costs than other proactive strategies that schedule inspection and maintenance at regular intervals.
Predictive Maintenance software benefits companies in a lot of ways. This includes a reduction in the stock of emergency spare parts, unnecessary maintenance checks, maintenance costs, machine breakdowns, and downtime for machines when they malfunction and are being repaired.
It also improves worker safety, increases productivity and profit, and also increases the lifespan of assets and their parts. The work orders generated by the software also track the whole maintenance process and provide verification at each step.
A Computerized Maintenance Management System is a system that lets you track, monitor, and analyze data pertaining to maintenance tasks and activities in an organization. This includes preventive maintenance, Predictive Maintenance, and all the reactive maintenance activities.
Predictive Maintenance is important because it is an essential maintenance strategy that facilitates safety and compliance, precautionary corrective actions, and elongated asset life. It saves the company a lot of resources because it helps schedule maintenance checks and repairs before the assets actually breakdown.