The State of IoT Technology and Its Future in Manufacturing

PTC’s ThingWorx demonstrates applications from improvements in efficiency and quality, to data analytics and the human-machine interface.

(Stock image.)

(Stock image.)

Digital technologies offer the possibility of improving operational performance in many sectors. In the manufacturing industry, this area of improvement is Industry 4.0 or the Industrial Internet of Things (IIoT). Many organizations are investing in digital initiatives in IIoT, thanks to advances in connectivity, integration and ease of platform usability and management.

The way manufacturers think about IIoT has evolved over the last five years. The benefits of these new technologies mean that it has gone from being a novelty to a critical business system that many manufacturers rely on for their operations. However, challenges to achieving the full benefits of IIoT remain due to a combination of technical and organizational hurdles and the failure to utilize IIoT at scale.

One company has focused its IIoT strategy on connectivity for solving real-world manufacturing problems. PTC’s ThingWorx is a digital solution designed to target bottlenecks, root causes, and quality and efficiency issues.

How Is IIoT Being Used in Manufacturing Today?

Many automated machines in the manufacturing environment have been in factories for decades, and they often have different protocols and languages—introducing a connectivity challenge, which is one of the areas where IIoT can yield results.

Chris Baldwin, VP of Product Management at PTC, leads the development of ThingWorx and explains how the IIoT platform is being utilized in industry.

“We have world-class software that can interpret all those languages and messages from different vendors and technology,” said Baldwin. “Our Thing Model contextualizes all the different data points and messages from the machines and devices in the factory. It doesn’t only provide contextualized insights through machine learning and analytics; it also manifests the data in the form of applications for operators, line managers, and executives.”

The ThingWorx platform focuses mainly on areas of optimization. It looks for bottlenecks or efficiency challenges by tracking labor, equipment, materials or waste data. It then recommends different measures as a hypothesis and tracks the data over time to improve quality and yield or reduce waste.

One of the IoT challenges manufacturers face is the ability to replicate a process. Enterprise manufacturers typically want to repeat a success gained by the insights that technology like ThingWorx provides across other lines and facilities. Companies like PTC must be able to take similar results, data, challenges and problems and apply a standardized approach to them. However, different geographies and environments have different operating methods, so solutions must be customized, extended, and applied to meet local environments. This ability to improve quality and efficiency is always a priority but is especially critical when the supply chain is an issue, such as occurred during the pandemic.

Automated processing and packaging machine manufacturer IMA Group has 46 manufacturing sites across the globe. The company wanted to improve efficiency but realized it needed to get inside its processes to analyze production data. It also recognized the need to provide increased remote collaboration with its customers—and the pandemic increased the demand for digitization even more. The company utilized PTC’s ThingWorx for monitoring and automation scenarios across its many assets, including a customer-facing application that offered operators features to help improve efficiency, machine data statistics for smart line harmonization, and average performance for accurate production planning.

Another example of how IIoT can improve efficiency over thousands of assets and a large geographic area is that of Sunbelt Rentals. With a fleet of over 600,000 assets made by different OEMs, the company struggled to pull data from various data providers. It also had difficulties unlocking the value of that data until it was able to aggregate and integrate data onto a single platform via ThingWorx.

Improving the Human-Machine Interface

(Stock image.)

(Stock image.)

Industry experts have followed the evolution of mobile and web technology in the consumer space, and expectations related to the user experience have now filtered into manufacturing and engineering interfaces. Baldwin recalls the flaws in older generation interfaces, including the denseness of information on the screen, making for a challenging user experience. The visualization of manufacturing technology has improved considerably, as he explains.

“An automotive safety manufacturer we work with took a user-centered approach to their operation where they required monitors and dashboards to be designed such that anyone looking at the screen could see the three most important pieces of information from three meters away. At PTC, we take a lot of measures to ensure that not only is the information accurate, but it is also presented in the best way possible.”

Improving Data Analytics

The use of data analytics has matured in manufacturing operations to achieve more tangible outcomes, as two cases involving PTC clients illustrate. One involved an aeronautics and defense manufacturer experiencing issues with material placement, which was causing variability in its setup time—from line to line and shift to shift. The client had struggled to understand the issue with the patterns and the ultimate root cause of the problem, so PTC applied ThingWorx analytics.

“We added sensoring, collected certain data, observed for a while, and within three weeks, we were able to drive a 30 percent improvement in their machine availability because we were able to recommend proactively how to correctly feed and handle the material and make those adjustments in the production process.”

Another example of how improved analytics can lead to meaningful results involved an automotive tire company that was having problems with material preparation around the rubber and feedstock of the slicing process for the tires. The company’s operation had a high degree of variability, which meant it was losing a tire a minute and reaching only about 50 percent of its production targets and producing excess scrap and waste.

In addition to limiting 35 percent of unproductivity based on the flawed slicing process, PTC implemented a closed loop of continuous monitoring, resulting in the ability to auto-tune the machine based on an intelligent process of monitoring material and environmental conditions. The IIoT process resulted in the additional production of 85 tires per day and roughly $20 million of additional revenue.

The Future of IIoT

Baldwin believes that the closed-loop process described above represents the further evolution of the next generation of IIoT. He thinks the systems PTC is building now can sit on top of the typical programmable logic controllers (PLC), distributed control systems (DCS) and manufacturing execution systems (MES) to orchestrate an even more autonomous, intelligent process.

Digital innovation software companies like PTC face challenges in replicating results at scale—across facilities and plants—due to the age of some of the systems and the variability of the environments from factory to factory. Chris says that PTC is responding to local variability by adapting its solutions.

“As the systems adapt better, we’ll move into auto-deployment, auto-configuration—using methods like output variance constraints. More modern devices have more self-describing protocols, such that we’re able to understand what device we are talking to, what data we require from it, and what data is available without human involvement. It’s faster to set up, easier to deploy, and it requires less administration and integration activities, so it’s a faster return on investment.”

Some organizations believe that scaling high-impact IIoT use cases across all their manufacturing facilities is the key to creating an enterprise-wide foundation for transformation. An example of this is found in the intelligent power management company Eaton, which drew on PTC’s IIoT expertise to select use cases that could scale value quickly across the organization, including real-time performance monitoring, asset monitoring and utilization, and connected work cells. Leveraging digital functions such as machine alerts helps factory floor operators, but it also provides insights to plant managers and leadership teams, who can assess and compare performance across multiple plants.

Baldwin believes that soon, not only will IIoT processes become more autonomous, intelligent and interconnected, but they will also become more affordable for companies of all sizes to tap into, making it possible for more of them to realize the business benefits of the connected factory.