The biggest costs of manufacturing—raw materials and energy—are subject to market forces and beyond any factory’s control. Yet, maintenance is a major balance sheet item with the potential for optimization.
Time is money—especially in today’s fast-paced manufacturing world. When a machine goes down and production stops, every minute comes with a cost. Predictive maintenance offers an alternative.
This method uses real-time insights, machine learning, and advanced analytics in industrial settings. Here, computers analyze sensor data and predict the remaining useful life of equipment. Then, engineers can schedule planned maintenance and reduce unexpected breakdowns and costs.
While the power of prediction sounds like science fiction, it’s reality. This article explores how it works, its advantages, and the hurdles manufacturers must overcome.
The ability to optimize manufacturing operations depends on understanding the shop floor. In reality, many shops are running with blind spots. Fragmented systems, manual data collection, and delayed reporting prevent modern systems from scaling. Companies need live monitoring and analytics.
Predictive maintenance and real-time monitoring work together to transform maintenance programs.
Real-time monitoring uses sensors and software to track equipment performance in operation. Predictive maintenance then builds on it. This method analyzes trends to detect early signs of wear, misalignment, and other issues before they lead to a major breakdown.
Without a real-time view of machine performance, predictive models lack the robust datasets needed for accurate forecasting. In this sense, real-time monitoring serves as the foundation upon which predictive maintenance is built.
The challenge is bringing these two elements together.
Companies have some work to do to get the full value of their digital investments. They may need to redesign maintenance processes, establish data flows, and invest in the team. Implementing changes in a 24/7 factory, though, is no small task.
Companies with the highest maturity and most effective maintenance systems have overcome several factors. Here's what has hampered the success of these programs elsewhere:
- Insufficient, inaccessible, or low-quality dataA modern manufacturing execution system (MES) enables real-time production tracking, monitoring, and analytics to give floor teams greater visibility.
It works by bringing previously siloed data sources into a unified dashboard. Automated IoT sensors can feed live OEE, cycle time, yield, and other critical KPI metrics into the system. These technologies give teams the real-time insights they need to proactively enhance equipment reliability, extend asset lifespan, and drive operational efficiency.
The best time to conduct maintenance and repairs is before the equipment fails. To enable this, manufacturers have to overcome a number of challenges. They must seek cheaper and more readily available sensors, higher data availability, next-level analytics talent, and a strong network of technical partners.
Despite the challenges, predictive maintenance is becoming a critical part of modern manufacturing. As technology advances, these systems will become more reliable, easier to use, and more affordable.
Technological advances in Industry 4.0 are leading to rapid innovation in Inernet of Things products, as well as the systems designed to manage factories and maintain equipment. These technologies alongside traditional, lean techniques are developing world-class factories with maintenance programs that serve as a strategic advantage.
Some companies are going a step further and adopting Industry 5.0. This presents tremendous opportunities to enhance equipment performance, productivity, and safety. While Industry 4.0 focuses on digitizing and connecting equipment, Industry 5.0 evolves by enabling systems to learn, adapt, and make autonomous decisions.
Successfully implementing a predictive maintenance program is more than just setting up a software solution on time and under budget. It’s about aligning strategy with execution, optimizing workflows, and fostering a culture of continuous improvement. That way, your team can unlock the full potential of the digital capabilities to bring manufacturing excellence.
MASS Group is a leading provider of MES solutions for the semiconductor, aerospace, and other highly discrete industries. The company's TME® platform provides end-to-end management of manufacturing processes, including process execution, equipment automation, materials management, and data analysis.
At MASS Group, we understand the importance of a software solution that reinforces good manufacturing practices while delivering comprehensive functionality. With over 25 years of experience, MASS Group has mastered the integration and rapid implementation of TME® MES without operational disruptions. This rapid deployment is backed by the TME® software solution that eliminates the need for scripting through easy configuration. MASS Group makes integration an accelerator, not an obstacle.
Talk to one of our experts and see how MASS Group can move your manufacturing forward.