The goal of the maintenance department of any production unit is to maximize the availability of machine tools. Poor maintenance strategy may reduce the unit’s productivity to a significant extent. Usually, it’s a tradeoff between ‘allowing the machine to run to failure’ (maximize useful life) and ‘scheduled preventive maintenance that could replace a potentially good part’ (maximize uptime).
Maximum utilization of machines can lead to severe machine damage owing to the wear and tear of parts. Resulting in downtime could be more time-consuming and expensive. Whereas scheduled maintenance can increase replacement cost overtime and may disrupt operations owing to frequent planned downtimes.
In this blog, we will discuss the potential of ‘Predictive Maintenance’ to break these tradeoffs. With the advent of Industry 4.0, manufacturers can turn their traditional facility into a ‘Smart Factory’ that leverages new technologies of sensors and connected devices.
The CNC machining center is an advanced manufacturing machine that can perform a variety of operations with high quality, high precision, and high surface finish. A CNC machining center can perform milling, drilling, and lathe operations.
The manufacture of discrete parts in the industry, such as gearboxes, partitions, frames, covers, etc., requires several types of machining operations such as milling, boring, drilling, tapping, and many other related operations. Conventionally, this production process had to be broken down into multiple working stages, and the operations on different machine tools were able to produce a finished product. This resulted in a large amount of delivery time and cost. This problem led to the conceptualization of a CNC machining center. Milling, lathing, and drilling operations on a single machine tool allow one machine to perform a greater variety of machining needs.
Intelligent Platform Services
Industrial Internet of Things (IIoT) allows manufacturers to create a ‘Smart Environment’ that works on the following components:
- Capture information from sensors to create a digital record of physical operation
- Advanced analytics and visualization of real-time data
- Apply algorithms to translate actions from the digital world to responses in the physical world
- Edge computing brings compute-intensive and latency-sensitive applications closer to end-user for real-time decision making
- Enterprise mobility solutions provide access to information that is relevant and important then by unlocking values at backend data and delivering user-centric actionable data
Application of IIoT to Machining Center
Today’s state-of-the-art Machining Centers need an equally sophisticated maintenance strategy. Predictive maintenance using IIoT technology can be the perfect answer to all the uncertainties of ‘Preventive Maintenance’.
Spindle vibrations, tool and coolant temperatures, machine oil viscosity can be indicators of machine wear and tear. Machining Centers equipped with such sensors will enable the maintenance crew to measure these parameters in real-time for further analytics and visualization. IIoT will also translate these data points into actionable tasks for the crew to perform at the machining center.
Overall Equipment Effective (OEE) dashboard will display real-time productivity at a granular (single machine) or a holistic (full machine shop) level for valuable insights into bottlenecks and efficiencies.
Predictive Maintenance by leveraging the enormous power of Industry 4.0 principles like IIoT, can be an answer to the great challenge faced by maintenance teams in the manufacturing industry, whether to adopt a Preventive Maintenance approach or allow machines to run to failure.
With intelligent technologies, manufacturing units now can implement Predictive Maintenance, and hence there is a shift from Preventive to Predictive Maintenance. Of course, there are certain areas where Preventive Maintenance is much more cost-effective, and hence while maintenance strategy is to be defined carefully and consciously.
Predictive maintenance will provide a sweat balance between expensive downtimes and operations disruptions. Apart from production units, principles of IoT can be implemented for predictive maintenance of heavy types of equipment in oil rigs, rolling mills in steel plants, turbines in power plants, etc.