Predictive maintenance with IoT enables strategic allocation of resources to optimize equipment performance throughout the organization. It allows to avoid unwanted pitfalls that causes wastage of time and resources while delivering productive results from the start.
Across the world, manufacturing equipment faces failures and downtime, while in different environments, due to the nature of repetitive tasks being performed by them. However, with a higher demand for efficiency and quality in production & manufacturing, these unplanned downtime causes delays and customer-loss, thereby hitting the bottom-line of the organization. Therefore, it is essential to limit the possibility of unplanned downtime as much as possible, to improve the bottom-line and gain competitive advantage.
Industrial Internet of Things (IoT), also known as IIoT, is the use of the Internet of Things (IoT) in the manufacturing/industrial sector. It constitutes the use of Wireless Industrial IoT sensors & applications, to connect machines and equipment sets, in order to facilitate machine-to-machine communication that improves the efficiency of overall manufacturing processes.
Predictive maintenance with IoT refers to the use of a data-driven approach, that analyses the equipment condition to predict when that equipment requires maintenance. It is a technique that can significantly improve the performance and lifetime of assets.
Predictive maintenance is a multi-step process that helps maintenance & reliability professionals monitor the equipment health to prevent failures and unplanned downtime. It uses data from sensors and predictive algorithms to estimate the correct time of equipment failure and schedule maintenance activities accordingly. It identifies the root cause of issues in complex machinery and the parts that need replacement. Predictive maintenance process generally involves:
At a macro level, Predictive Maintenance with IoT uses advanced technologies such as Smart Sensors, Internet of Things, Big Data, Machine Learning, Cloud Computing, Edge Computing and Wireless Communication Networks. Engineers and Professionals bring these technologies together to build a robust Predictive Maintenance Solution. Predictive maintenance technology is based on a simple architecture as mentioned below:
Predictive Maintenance has the potential to reduce unplanned downtime and prevent asset failures. It facilitates remote condition monitoring of critical industrial assets and ensures proactive asset maintenance. The goal of predictive maintenance with IoT is to improve the health & performance of machines, leading to reduced downtime, increased production and improved workplace safety.
Predictive Maintenance with IoT offers myriad benefits to the manufacturing operators, that help them gain significant competitive advantage. These benefits include:
Predictive Maintenance system analyses historical as well as real-time performance data of the machines using predictive algorithms to detect faults before it occurs and prevent subsequent failures. It also allows to maximize asset uptime and optimize maintenance costs & resources.
These practices should assist maintenance & reliability professionals to deal with issues and extract value from full scale implementation of predictive maintenance.
Nanoprecise is an Industrial IoT Predictive Maintenance solution provider that offers real-time predictive information about the genuine health and performance of industrial assets. Nanoprecise offers IoT Solutions for Industrial Manufacturing with our unique 6-in-1 Wireless Industrial IoT Sensor and patented AI-based analytics platform. The Industrial IoT Predictive Maintenance Solutions from Nanoprecise uses a combination of AI + IoT + LTE-driven seamless monitoring, to offer prescriptive diagnostics. Nanoprecise specializes in scaling Industrial IoT across various sectors to empower maintenance and reliability professionals with the right data at the right time.
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