How SCM uses CMMS Software for IoT Predictive Maintenance

What are Predictive Maintenance Technologies?

Predictive maintenance technologies allow manufacturers to remain aware of the status of their equipment at all times. These technologies are installed on or near pieces of manufacturing equipment, and they provide real-time data on the efficiency of equipment and the necessity of maintenance intervention.

Various internet-connected sensor devices monitor the status of production equipment. Some examples of these preventive maintenance technologies include thermal sensors, which monitor the heat that a piece of equipment emits, and sonic sensors, which test for changes in the sounds emitted by equipment.

Other IoT preventive maintenance tools monitor the vibration that production equipment emits for anomalies. All of these different types of preventive maintenance technologies feed the data they collect to central software systems that use algorithmic functions to predict when maintenance will be necessary.

What is a Computerized Maintenance Management System (CMMS)?

CMMS software helps manufacturers keep track of the maintenance schedules for their production equipment. This type of software varies in complexity, and older CMMS solutions may require more manual input.

In recent years, however, CMMS software has evolved to handle input from IoT devices. Advanced CMMS software can now monitor the status of dozens of different pieces of equipment and use complicated algorithms to deliver clear, actionable insights regarding ideal preventive maintenance procedures. Some of the key functionalities of CMMS software include:

Data Communication

CMMS software facilitates the communication between IoT devices and central servers that is necessary to provide real-time data on the current status of production equipment. Data storage mines collected data from IoT devices in centralized, secure locations for easy reference and categorization. Most importantly, CMMS software provides actionable Data analytics that manufacturers can use to develop effective preventive maintenance procedures.

Condition-based Algorithms

CMMS software is the central hub that connects all the information provided by IoT preventive maintenance tools and makes this data easy for manufacturers to access and use. To accomplish this task, CMMS software uses highly complex condition-based algorithms to assess the condition of production equipment and develop plans for preventive maintenance. Predictive maintenance software uses these algorithms to leverage both real-time and stored data to predict when equipment will fail or require maintenance. Then, before any equipment failure actually happens, CMMS software delivers analytics that allows preventive maintenance to take place. CMMS software can provide these algorithmic insights for dozens of pieces of equipment simultaneously.

Benefits of Predictive Maintenance

In the past, equipment failures required the complete or partial shutdown of production while maintenance occurred. This inevitable inefficiency naturally slowed down production and reduced profits, but manufacturers were forced to accept unexpected equipment failure as a cost of business.

With predictive maintenance, however, it's possible to address equipment that is expected to become faulty at ideal times that do not conflict with production schedules. This revolution in supply chain software efficiently allows manufacturers to anticipate production delays well in advance. This keeps the supply chain operating effectively without loss in either production volume or revenue.

IoT devices that predict when equipment will fail or need maintenance, however, are only as good as the software that collects, stores, and analyzes the data they provide. Custom CMMS is the best software solution for manufacturers since it provides the flexibility necessary to adapt to your unique circumstances. Invest in custom predictive maintenance software to improve productivity and avoid setbacks.