For manufacturers, unplanned downtime has always been one of the most significant financial burdens. In some industries, unplanned downtime costs hundreds of thousands of dollars per hour. Predictive maintenance tools and technology have long been proven effective in reducing repair costs. Still, it’s more evident than ever that real-time data is essential to getting the most out of your predictive maintenance program.
With supply chain disruptions, increased inflation costs, labor shortages, and constantly changing consumer demands, businesses need to be resilient in their approach. COVID-19 has impacted the economy, leading to reduced training budgets, but the real test for manufacturers will be how they continue moving forward.
As manufacturers try to adapt to changing circumstances, relying on projections based on prior performance is not enough. Demand for some products has surged, and it’s impossible to gauge what will happen based on year-over-year metrics. Current economic projections are still wide-ranging, but businesses need to do everything possible to retain a competitive edge by reducing wasteful spending and meet shifting consumer demand.
While OEM guidelines can be a safe place to start with a machine maintenance plan, they are generally conservative and limited in their practical application. Machines have different maintenance needs depending on criticality, operating conditions, environment, and frequency of use. In the past, manufacturers have adopted either overly cautious or running-to-failure (RTF) maintenance strategies, which have drawbacks. With drastic shifts in demand seemingly overnight, the only possible way to effectively decide on equipment repairs is with real-time data.
Q: What is predictive maintenance?
A: Predictive maintenance is a proactive approach to maintaining equipment by monitoring its health and predicting when maintenance is needed based on real-time data.
Q: How can real-time data help manufacturers?
A: Real-time data helps manufacturers make informed decisions about equipment repairs, reduce wasteful spending, and better adapt to rapidly shifting consumer demands.
Q: What are the benefits of automation in predictive maintenance?
A: Automation in predictive maintenance streamlines processes, reduces the need for in-person labor, and ensures that essential machine health data is collected, even with a reduced physical workforce.
Final Thoughts
Real-time equipment health data is crucial for manufacturers as they face uncertain times and rapidly shifting consumer demands. By incorporating real-time data into their predictive maintenance programs, manufacturers can make informed decisions, reduce wasteful spending, and maintain a competitive edge in the market. With the help of IIoT-enabled devices and platforms like VibePro 24/7, manufacturers can stay connected to their equipment and ensure that essential machine health data is always available.
