Belden

Brian Lieser has been with Belden for 15 years and is currently the executive vice president of the company’s Automation Solutions segment. He leads efforts to support customers through every stage of their digital transformation, leveraging Belden’s comprehensive connection solutions to drive improved outcomes. Previously, Lieser was vice president of global products for industrial automation solutions, overseeing product strategy, development and expansion across Asia and Europe. He has also held key leadership positions, including vice president in Neckartenzlingen, Germany. Lieser has a bachelor’s degree in aerospace engineering from the University of Minnesota and an MBA from the University of St. Thomas Opus School of Business.

Through This Article, Lieser Emphasizes The Importance Of Integrating Automation With Legacy Systems, Adapting To AI-Driven Workforce Changes And Reducing Industrial Waste Through Automation.

At a Glance:

• In a legacy environment, production and maintenance data are often manually entered, resulting in inaccuracies and incomplete information that prevents you from seeing the bigger picture.

• AI and ML will continue to gain traction in industrial automation, but they won’t eliminate the need for human operators. • To capitalize on automation, leaders will need to be comfortable encouraging innovation and out-of-the-box thinking to explore new technologies that foster a culture of experimentation.

Overcoming Challenges With Legacy System Integration

While every company’s challenges when integrating new automation technologies with legacy systems differ, there are some common hurdles we see across nearly every organization.

1. Lack of ways to share crucial data

One of the first steps in integrating automation into legacy systems involves ensuring data consistency and alignment. In a legacy environment, production and maintenance data are often entered manually. This results in data inaccuracies and incomplete information that prevents you from seeing the bigger picture. For example, data about condition monitoring can help teams evaluate device health on the plant floor. This data also supports predictive maintenance so components can be repaired before failure occurs. Other teams may benefit from this data, too. Feeding it into a maintenance management system can generate automated work orders when device performance falls outside specific parameters. New purchase orders can be created for new parts when they are needed. But for this to happen, data collection must be automated—not manual. This is a critical element of any automation strategy.

“Migration scenarios are key to carrying out digital transformation in a practical, cost-effective way according to the timeline. They help the industry prepare for the future while maximizing the investments the company has already made in technology and equipment.”

Automating data collection also addresses the issue of “trapped data,” another hurdle for many manufacturers. In these environments, when information is stored across different systems and in various formats, it becomes “trapped.” This makes the information difficult to access, share and use. By automating data collection and integration, siloed information becomes democratized. It’s available to everyone and usable.

2. Constrained capital budgets

 Rising business costs, fluctuations in demand and even talent shortages put pressure on capital budgets. To overcome this hurdle during automation integration, exploring solutions that don’t require your company to “go all in” on a new technology or digital transformation strategy is critical.

Major transformation doesn’t have to happen all at once or overnight. You can upgrade equipment over time and in alignment with your budget. Migration scenarios are key to carrying out digital transformation practically and cost-effectively according to the timeline. They help the industry prepare for the future while maximizing the investments the company has already made in technology and equipment.

3. Working with different systems and protocols

Interoperability and compatibility are critical to ensuring new and existing equipment coexist and operate efficiently. For example, it is not unusual to find different operational philosophies, design standards, architectures, protocols, manufacturers and generations of equipment in use within the same plant.

However, there are ways to integrate these systems and protocols so that legacy equipment can work alongside new equipment to exchange and use data securely, regardless of protocols or generation.

Belden helped a gas company overcome the challenges of working with its diverse systems and unique communications protocols. We did this by developing a way to poll the engines in a gas compression station to evaluate condition status and periodically check for changes or updates. The information is polled using Modbus communication protocol and sent to a Rockwell Automation processor using EtherNet/IP protocol. A ProSoft gateway then transfers data between the devices.

Shaping Humans’ Role With Evolving AI-Driven Industrial Landscape

Artificial intelligence (AI) and machine learning (ML) will continue to gain traction in industrial automation, but they won’t eliminate the need for human operators. Instead, these roles will evolve. Workers will no longer be constrained by having to perform routine tasks every day. They will become critical decision-makers, overseeing and managing automated systems and making choices based on the data being gathered and reported.

As a result, workers in this new environment will need strong problem-solving and analytical skills. They will need to analyze and interpret data and understand its story. They will also need effective communicators who can explain to various teams what AI and ML models report and what actions to take.

Reducing Industrial Waste Using Data

Automation can play a critical role in reducing waste and energy consumption. Automated data collection can ensure access to accurate, real-time data, which helps companies optimize their production processes to reduce waste. This data can also be used to automate production processes and perform tasks with high levels of precision and uniformity to decrease scrap, rework and energy use.

When used as part of a predictive maintenance program, automation can continuously monitor equipment and send alerts about potential problems before they result in failures. This improves uptime and extends the equipment lifecycle, lowering energy consumption and waste.

Key Advice For Future Leaders In An Automated World

Leaders must be prepared to shift their focus from managing team members who complete routine tasks to fostering innovation, making strategic decisions and building a workforce that can thrive in a tech-forward environment. Leaders will also play a critical role in planning for and promoting collaboration between human workers and automated systems. This may involve refining roles and responsibilities, hiring for new types of positions and ensuring seamless technology integration.

Finally, to capitalize on automation, leaders will need to be comfortable encouraging innovation and out-of-the-box thinking to explore new technologies. They will be responsible for fostering a culture of experimentation, encouraging team members to embrace change—even if it is initially uncomfortable—and striving for continuous improvement.