Artificial Intelligence in Maintenance

Across the world, manufacturing equipment face failures and downtime, due to the nature of repetitive tasks being performed by them. However, with a higher demand for efficiency and quality in production & manufacturing has put an ever-increasing strain on maintenance teams to prevent unplanned downtime that 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. This can be achieved with the help of a Predictive Maintenance Solution.

Predictive maintenance refers to the use of a data-driven approach, that analyses the equipment condition to predict when that equipment requires maintenance. Manufacturing organizations can significantly improve the performance and lifespan of assets using appropriate predictive maintenance measures.

The aim of Predictive maintenance is to predict the failures before it occurs, and determine the appropriate time for performing maintenance activities on industrial assets, so as to maximize its reliability without incurring additional costs.

An automated AI-based Predictive Maintenance solution can prevent asset failures and unplanned downtime. It consists of IIoT hardware that connects physical assets to each other, and an advanced analytics platform that analyzes the complex machine data to predict failures and prevent unplanned downtime. AI-based Predictive Maintenance solutions ensure remote condition monitoring and facilitate proactive asset maintenance.

The goal of an automated AI-based Predictive Maintenance system is to maintain & improve the performance of critical industrial assets, resulting in fewer failures, reduced downtime, increased production and improved workplace safety. The AI-based system uses machine output data, including historical performance as well as real-time contextual data, and analyses it using machine learning algorithms to notify maintenance and reliability professionals of the maintenance needs of different equipment sets.

Automated AI-based Predictive Maintenance System is a powerful tool that can help the maintenance & reliability professionals to streamline the extraction of actionable information from the machine health and performance data, to improve the overall manufacturing operations.

Automated AI-based Predictive Maintenance offers myriad benefits to the manufacturing industry.

  • The first big benefit of Artificial Intelligence in predictive maintenance is the ability to detect faults before they happen. This means that organizations can prevent costly equipment failures before they occur. This helps companies to save costs that are associated with frequent maintenance activities.
  • AI-based predictive maintenance systems also help companies prevent production losses from faulty equipment, and with fewer repairs needed, companies will spend less on hiring outside contractors and service technicians.
  • Furthermore, it helps companies save time as it eliminates the need for manual inspection checks or trips to the shop floor for diagnostics.
  • It also improves the workplace safety for engineers and technicians by collecting automatically data from the machines in complex and hard-to-reach places.

All these factors make AI a much more cost-effective option than traditional maintenance methods and other forms of redundancy like backups or replacements.

Condition Monitoring Services

Artificial Intelligence in Maintenance has brought about a paradigm shift in the manufacturing and production sectors across the world, with its ability to offer real-time information on the machine health & performance and tailoring maintenance routines to each equipment set, rather than conforming to a predefined schedule. The ability to view latest operating condition of machines, ensure that maintenance professionals encounter fewer surprises and can avoid problems altogether.

Reducing Downtime in Metal Industry

Our IoT driven Predictive maintenance solution helps to reduce downtime, monitor, collect exchange and analyze data from machines to enhance manufacturing processes of the metal industry.

Machine failure in the mines? No worries.

Our solutions can add immense value to your entire mining supply chain by harnessing the power of Industry 4.0. The asset performance will be optimized, costs and machine downtime can be reduced leading to a boost in ROI.

No more unplanned downtime in Cement Industry

Our Industry 4.0 digital solutions can help you tackle the challenges in cement production such as large energy consumption, high costs and complex processes.

Our advanced analytics can simplify complexities and help in real-time decisionmaking. Equipment lifespan and reliability will amplify due to our condition monitoring system.

Protect your assets with Zone Approved Solution

Our digitization solutions in industrial equipment maintenance can help oil and gas companies streamline maintenance. Our predictive analytics and conditional data monitoring help anticipate failures, reducing unplanned maintenance and unscheduled downtime.

No more Downtime, Keep your Machines Running in Chemical Plants

Our AI driven analytics can propel your chemical business to new heights of reliability by optimizing asset longevity and impacting top-line growth through proactive identification of upcoming machine failures. IoT driven asset maintenance solutions can provide immense flexibility and agility to production.

Request a Call Back

Frequently Asked Questions

Predictive maintenance is a data-driven approach, that analyses the complex data from industrial assets to predict when it requires maintenance. Artificial Intelligence systems offer the ability to analyze enormous volumes of this data and provides a better understanding of the overall health & performance of industrial assets.

Artificial Intelligence and Machine Learning analyzes the complex machine data and translates it into meaningful insights, thereby helping maintenance and reliability professionals to take corrective actions and prevent unplanned downtime.

AI-based Predictive Maintenance System detects anomalies, identifies fault modes and predicts equipment failures before it happens. This helps to prevent asset failures, reduce unplanned downtime, increase production efficiency and improve the workplace safety.

According to Deloitte, predictive maintenance on average, increases productivity by 25%, reduces breakdowns by 70% and lowers maintenance costs by 25%.

Artificial Intelligence has the potential to empower maintenance & reliability professionals with the right data at the right time. The ultimate goal is to obtain meaningful insights from the complex machine data for faster and more accurate decisions. This will help to reduce the maintenance costs and optimize the resources.