Digitization is a steady companion in every facet of any business. It transforms business processes to drive profitability and efficiency. Industry 4.0 technologies are helping in improving the safety, accessibility, productivity, and sustainability of energy systems around the world. It ensures higher efficiency, lower operating costs, and better control of business operations, both for the individual company and the network of connected companies.

Asset Management

Assets build the foundation for any business. Professional asset management has become key for productivity and sustainability in the industrial competition and even beyond as today’s industrial markets are exceedingly fast-paced. We can understand the performance, faults, causes, and effects of the equipment on a much wider and more detailed aspect by the data from connected equipment in machinery which means

Benefits of Asset Management

• Increase the value of the asset by improving performance and enhancing life
• Optimizing cost and reducing risk to unplanned downtime
• More efficient business processes and great overall agility
• the first step for predictive maintenance

Reactive to Predictive Maintenance

Reactive Maintenance Repairs are performed only after the failures of machines. Preventive maintenance Machinery failure is unpredictable and hence has to be concerned about maintenance. Is the machine behaving abnormally? Is there a fault in the system, or what’s the root cause? When will the machine fail? All these questions can be answered with the help of digitization and predictive analytics.

Predictive maintenance is highly growing and gaining popularity as an approach that enables companies to

• Improve uptime by 9%
• Reduce cost by 12%
• Reduce safety, health, environmental quality risks by 14%
• Extend the life of aging assets by 20 %
(data as per PWC.)

Data from assets enables us to detect the variance and symptoms of machine failure before critical damage by automated machine monitoring. It eliminates excessive times of machine maintenance hence reduces maintenance costs leading to profit. Analytics improvises the important parameters that affect the quality of the product and helps in ensuring the best possible operation, ensuring maximum productivity. Human-dependent errors on the health check of machines are reduced, lowering the chances of machine malfunctions. Features like accident avoidance systems can alert or even stop the equipment in case of hazardous danger.

Predictive maintenance matches the needs of the industry and the requirement of smart manufacturing and buildings. It is the recent lever in driving efficiency. It enables efficient planning for maintenance operations, making it easier to define operational maintenance goals and allocate maintenance resources, leads to the best resource utilization, and reduced downtime. The goal is to turn data into information and information into insight. Even the best-built machines need proper predictive maintenance to remain productive and reach their maximum work life.