IIoT-based predictive maintenance – A mission critical need for manufacturing

Industry 4.0 continues to gain momentum across every industrial and manufacturing segment. This revolution is built upon three primary technologies: Big Data, Edge Computing and the Internet of Things (IoT). As the adoption of IoT devices continues to grow, many organizations are switching to edge technology because of its advantages over legacy cloud solutions. One of the key advantages of edge computing is real-time predictive maintenance. In a predictive analytics solution, Artificial Intelligence (AI) is combined with Business Intelligence (BI) to monitor the operating condition and predict when to perform maintenance on that asset.
What is Predictive Analytics?
Predictive analytics uses statistical algorithms and advanced analytics combined with AI techniques to predict future outcomes based on historical and current data patterns. Organizations use this method to benefit possible future events by using predictive modelling to take maintenance decisions before a disruptive event. This technique imports data from the targeted asset synthesizes it and combines it with different data sources. Once a large amount of data is cleaned, the data analysis is initiated to recognize patterns and trends. In simple words, using Artificial Intelligence and Machine Learning technique, a machine can predict future events.
What is Predictive Maintenance?
A subset of predictive analytics, predictive maintenance is the process of utilizing data analysis to predict future outcomes. This technique is used to recognize potential faults in machines and processes. Manufacturing and service industries need to improve the performance of their assets. As per the report by a leading publication, spending on IoT-enabled predictive maintenance will reach 12.9 billion by 2022 compared to $3.4 billion in 2018.
Benefits of Predictive Maintenance:
The Future of Predictive Maintenance
About Infinite Uptime
Infinite Uptime is transforming the industrial health diagnostics space with a Digital First approach. We provide comprehensive solutions around Machine Diagnostics, Predictive Maintenance and Condition Monitoring to the top engineering and process industries globally. We promise to deliver maximum Machine Uptime, minimize Factory Disruption and elevate Equipment Reliability for a stellar factory performance.
Infinite Uptime leverages IoT, machine learning, artificial intelligence, smart communications, cloud computing, analytics and data science techniques to accelerate digital adoption and turn Industry 4.0 into a business reality. To know more about us and our customer success stories, please visit www.infinite-uptime.com or write to contact@infinite-uptime.com.
FAQs
Predictive analytics involves using statistical algorithms, AI techniques, and advanced analytics to forecast future outcomes based on historical and current data patterns. It helps organizations anticipate future events and make proactive decisions, such as scheduling maintenance before issues arise.
Predictive maintenance offers several advantages, including improved machine lifespan, increased production by avoiding unscheduled downtimes, minimized maintenance costs, reduced downtime, and enhanced overall equipment effectiveness. It helps optimize resource scheduling and reduce operational setbacks.
Edge computing is preferred for predictive maintenance because it allows for real-time data analysis on-premise, reducing latency and data storage costs. Unlike cloud computing, which involves transmitting large amounts of data over the network, edge computing minimizes data sharing and associated costs, making it more efficient for handling extensive IoT data.
Infinite Uptime enhances predictive maintenance with a Digital First approach, offering solutions in machine diagnostics, condition monitoring, and predictive maintenance. By leveraging IoT, AI, and machine learning, Infinite Uptime helps industries achieve maximum machine uptime, reduced factory disruptions, and improved equipment reliability.