By Mark Backus, Regional Product Manager for Machine Integration/Tooling Systems, Americas, Sandvik Coromant
In the fast-paced world of metalworking, the convergence of IoT, Industry 4.0, and connected machine monitoring is transforming manufacturing. IoT connects machines, sensors, and devices throughout the metalworking process, which allows for real-time data collection, analysis, and communication, resulting in a seamless flow of information across the entire value chain. This data can be transferred to a centralized machine monitoring system to identify potential issues or inefficiencies in real time for proactive maintenance and minimal unplanned downtime.
Whether a shop is just starting a digitalization journey or already incorporating Industry 4.0 solutions, the available technologies and vast data they produce and manage can be overwhelming. Let’s look at some parallels from the machining world to see how shops can better navigate the digital transformation landscape to find the right strategy and technology to improve their business.
Go beyond the lights
When shops depend on the green, yellow, and red andon lights to indicate operation status and utilization, they’re not making the best use of machine-generated data. If an operator sees a red light, what is that telling them? Has the machine crashed? Is engineering doing a test, or is the machine out of work material?
Some companies have in-house analytics that use historical machine data to assess processes after the fact. However, industry-specific connected machine monitoring systems may provide more useful real-time, in-depth analytics that capture and report the data underlying those red, yellow, and green lights.
For example, in metal cutting shops, that data is based on rules established between the condition monitoring software provider and the machining operation. These rules can follow industry-standard measurements for overall equipment effectiveness (OEE), incorporating machine utilization, availability performance, and production quality. These platforms capture and report data that machining operations determine as crucial for continuous improvement and lean manufacturing.
Start small and focus
When a shop has a lot of machines generating a lot of data, what data should it focus on? Apply classic lean principles to start. Identify persistent issues or bottlenecks — waste, unscheduled downtime, quality issues with specific parts or machines — that require more complete data to implement root cause analysis.
For example, many shops find that operators spend more time setting up than machining parts. Users can easily configure and track related parameters, including setup times, part loading/unloading time, and time spent on fixture changes, tool changes, or blow-off cycles, to zero in on waste and low utilization. More importantly, this real-time data is much more accurate for making operational changes or business decisions rapidly and confidently to achieve optimization goals.
Put sensors in the action
In lean manufacturing continuous improvement, a key step is to ask shop floor operators about their pain points and persistent issues. However, with today’s condition monitoring software and on-machine sensors, why not collect dynamic input directly from the machine — eliminating manual monitoring with stopwatches and spreadsheets?
For example, incorporating sensor-equipped driven cutting tool holders and turning adapters on a metal-cutting machine provides insight into where the work takes place. With embedded sensors, a smart driven tool holder system with IoT capabilities measures variables, such as cutting forces, torque, vibration, temperature, and real RPMs, showing the exact number of hours spent in production. This data can also be transmitted wirelessly to a central monitoring system, where advanced analytics algorithms can extract more valuable insights.
With a sensor-enabled driven tool holder solution, predictive maintenance becomes a reality. The system can detect early signs of tool wear or potential failures, allowing for more proactive tool replacement or adjustment to prevent unplanned downtime. These smart adapters can also interface with a machine PLC and provide valuable information on tool condition, machining parameters, and process stability. By analyzing vibration patterns and comparing them against predefined thresholds, the system can identify deviations that indicate tool wear, improper tool setup, or unstable cutting conditions.
Consider cloud-based condition monitoring
Cloud-based condition monitoring platforms offer multiple advantages compared to locally installed and networked systems. Many modern machine tools have high-speed Ethernet-based interfaces to easily connect tools and production floors to external networks and cloud-based applications, which support the advanced algorithms and processing power to perform complex, real-time analysis much better than on-premises servers.
With cloud-based solutions, users can see current machine states and historical performance anywhere in the world. Data is protected behind firewalls in compliance with strict government security protocols covering sensitive defense and intelligence applications. Platform providers manage and keep cloud-based applications up to date, relieving the shop’s IT department.
One further advantage is that cloud-based condition monitoring programs can be rapidly implemented without additional hardware to support multiple locations worldwide and enable remote support capabilities.
Seek industry expertise
It’s advantageous to select a condition monitoring software platform created by a manufacturer with in-depth expertise in your specific industry and who uses their own platform to improve their operations. Partners can provide technical support and help guide shops through their digitalization journeys, which can lead to much quicker returns on digital machining investments.
With IoT-enabled equipment and machines integrated into a machine monitoring platform, shops can get the insight they need to identify and reduce waste in their processes quickly. And with trusted expertise and support, shops can improve productivity and, in turn, their business.