Design Engineering

Six ways to unlock the power of IIoT for machining

By Mark Backus   

Materials Metal Fabrication Machine Building IIOT machining sandvik coromant

How machine monitoring systems provide a new level of informed decision-making on the shop floor.  

With IIoT-enabled machines, operators gain the insight needed to identify and reduce waste in their processes.

Connected technologies are creating powerful opportunities for the manufacturing industry. The Industrial Internet of Things (IIoT) enables connected machine monitoring and offers new possibilities for transparency, efficiency and productivity.

The integration of IIoT throughout the metalworking process, for example, can create more actionable and valuable data in real time than ever before. That data can then be aggregated and analyzed in a centralized machine monitoring system to help identify inefficiencies or potential failures before they become a serious problem. This powers a new level of informed decision-making on the shop floor and in the engineering room, allowing operations to minimize downtime, optimize processes and prove out tool paths for new parts.

But this digital transformation isn’t happening at the same pace in every workshop. Keeping up with technological change can be challenging, especially when there are quotas to fill and tight deadlines to meet. Let’s look at some parallels from metalworking that can help other shops navigate the ever-evolving technological landscape—no matter where they are on the digital transformation journey—to find the right tools, strategies and partners to innovate their business.



1. Go deeper than red, yellow and green andon lights

When shops only depend on the red, yellow and green andon lights to understand the status and utilization of their operations, they’re not making the best use of the data their machines are generating. A red light only tells a small part of the story to an operator. It doesn’t tell them whether the machine has crashed, engineering is doing a test or the machine is out of work material.

To solve for this, some companies use in-house analytics that take historical data exported from machines to assess their processes. But addressing problems after the fact severely limits opportunities for improvement.

Connected machine monitoring systems may provide a more useful solution, providing real-time, in-depth analytics of the data underlying red, yellow and green andon lights of a specific operation. A metal cutting shop may analyze its machine data based on custom rules established in collaboration between the condition monitoring software provider and the machining operation. 

These rules can follow industry-standard measurements for overall equipment effectiveness (OEE), incorporating factors such as machine utilization, availability performance and production quality. These platforms are designed to capture and report the kind of data crucial for machining operations to sustain their continuous improvement and lean manufacturing efforts.


2. Pinpoint your pain points

A shop has a lot of machines generating a lot of data, but how do operators determine which data to focus on to make the best use of condition monitoring software? The first step is to 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 their operators spend more time doing setup than actually machining parts. The right condition monitoring software can be configured to track key parameters, such as setup times; part loading/unloading time; and time spent on fixture changes, tool changes or blow-off cycles, among others.

Today’s machining condition monitoring platforms let users easily configure and track these data points and zero in on where time is being wasted and assets underutilized. More importantly, the data is more accurate and available in real time, enabling users to make informed operational changes or business decisions quickly and with confidence.


With embedded sensors, a smart driven tool holder system can measure variables like cutting forces, torque, vibration, temperature and real RPMs.

3. Use IIoT to get data at the tool level

It isn’t just your machines that can provide useful data. Shops that want to take data-driven production to the next level can also start collecting data at the tool level.

Incorporating sensor-equipped driven tool holders and turning adapters on a metal cutting machine, for example, provides insight where the work takes place. With embedded sensors, a smart driven tool holder system can measure variables like 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 to extract more valuable insights.

With a sensor-enabled driven tool holder solution, the system can also detect early signs of tool wear or potential failures, allowing for more proactive tool replacement or adjustment to prevent unplanned downtime. For example, if the connected tool holder system detects an unusual increase in cutting forces or excessive vibration, it sends an alert to the operator or maintenance team, notifying them of the need for an inspection or tool replacement.

Another example at the cutting tool level is the use of an intelligent turning adapter for deep boring bars. These sensor-equipped adapters use intelligent damping technology to minimize vibration while optimizing metal cutting operations. By integrating IIoT capabilities, they can offer real-time insights into machining processes and enable operators to make data-driven decisions for improved productivity and tool life.

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.


Cloud-based machine monitoring software is accessible from any tablet, smartphone or computer with an internet connection to enable remote monitoring.

4. Explore cloud-based condition monitoring

Cloud-based condition monitoring platforms offer multiple advantages compared to systems that must be installed and networked on servers at your operations. Many of the more recent machine tools have high-speed Ethernet-based interfaces that simplify the process of connecting tools and production floors to external networks and cloud-based applications.

The kind of complex, real-time analysis and reporting provided by these condition monitoring programs utilize advanced algorithms and significant processing power, which the cloud is much more able to support than on-premise servers. Cloud-based solutions offer the ability, from literally anywhere in the world, to see not only the current state of machines but also how those machines have performed since the first day they were connected.

With a cloud-based solution, data is protected behind firewalls, with condition monitoring providers offering systems that typically comply with strict government security protocols covering sensitive defense and intelligence applications. A cloud-based application is managed and kept up to date by the platform provider. This means the shop’s IT department is not required to maintain expertise in managing and updating this kind of application.


5. Use your machine analytics platform as an engineering tool

Beyond maximizing uptime in day-to-day production, machining insight platforms can play a big role in proving out processes to machine new parts. With the right platform, engineers can track new tool paths and cutting forces in real time, giving them up-to-the-minute insight on what is and isn’t working in a process. Engineers can use this insight to develop new machining methods for new parts more quickly, and even remotely.

The data is accurate enough that an engineer can determine, on the spot, whether they need to try a different tool, change an insert or use a new tool path to improve the process. The result can mean big improvements for new product setup. What might otherwise take a week of on-location engineering time and nearly half a dozen test parts can now be accomplished in one or two days with just one or two parts.


6. Choose a partner, not just a platform

There are many condition monitoring software platforms available that are developed for general industrial applications. However, these platforms may not offer the level of insight or support needed for the unique demands of the metal cutting industry. Finding a platform from a manufacturer with in-depth expertise in your specific industry will mean the system will be configured specifically for machining data.

Beyond the software, an expert condition monitoring partner who knows your industry will be able to provide essential advice and technical support throughout your digitalization journey. From planning and implementation to data analysis and other support services, the right partner can guide shops to quicker returns on a digital machining investment.


Mark Backus is the Regional Product Manager for Machine Integration/Tooling Systems, Americas, Sandvik Coromant.


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