How to Enhance RPA Performance With Digital Twins

Business leaders often rely on robotic process automation (RPA) to help team members complete repetitive tasks more efficiently. This software-based approach involves tools recording and keeping the details of those duties, then replicating them with little or no human involvement. Digital twin testing can improve RPA performance, such as when people build these simulations to study processes and identify shortcomings.

Get In-Depth Information From Humans Tasked With Processes

Not all workplace duties will get completed faster or with fewer errors when people apply RPA. That’s why, in addition to pursuing digital twin testing, developers and other involved parties should strongly consider speaking to the employees whose jobs or responsibilities the RPA will ideally enhance.

One academic paper explores the application of RPA digital twins in the public sector. The researchers designed a digital twin representing four stages of business processes and then used it to mirror and optimize those responsibilities. A key research segment involved 41 semi-structured interviews with several administrative experts.

The digital twin developers used the associated insights to learn about the administrative professionals’ roles and how RPA could replicate them. A notable finding was that RPA digital twins are best suited to roles with low back-end content or low complexity with high front-end interactivity. Additionally, the researchers found that digital twins were less beneficial for large infrastructure projects relying on company-wide databases.

The researchers also identified user-centric process knowledge as valuable during the RPA and digital twin development stages. However, they acknowledged the limitations of only focusing on a few administrative tasks. A broader project scope could reveal other challenges.

The research team believes their conclusions will assist others interested in using digital twin testing for better RPA results. They discussed future research areas, including using their approach and digital twins to pinpoint the RPA development options that will perform reliably with minimal configuration.

They also recognized the value of a similar but longer investigation involving more data. For example, further interviews with workers to determine additional process details, including task complexity, could highlight other workplace responsibilities well-suited for RPA and digital twins.

Study Data to Tackle Bottlenecks

Many health care organizations face challenges linked to fluctuating demands and supply chain shortages. However, digital twins allow decision-makers to assess processes and identify the best process improvement opportunities.

Researchers combined RPA with a digital twin during work to support a 1,800-bed Singaporean hospital. They hoped to build an RPA solution to strengthen the hospital’s future supply chain.

A primary goal was to visualize how supplies moved throughout the facilities. During the study, the hospital used automated guided vehicles (AGV) to transport items ranging from cafeteria food to bandages. The associated digital twin testing required gathering various details, including 3D building information, transport routes, typical patient demand levels and elevator availability.

The team relied on digital twin testing to run various RPA simulations. Those allowed the participants to identify optimal delivery windows for each supply type. Much of the research involved measuring elevator use and how it differed since the AGVs travelled between different floors at the same times as hospital guests.

Eventually, the group used the digital twins to find the delivery sequences without bottlenecks or congestion. Additionally, running digital twin simulations to test different possibilities across days, weeks and months allowed seeing areas for improvement.

Some involved investing in additional AGVs and transport robots. However, other takeaways revealed movement flow specifics. For example, people would need to use 106 carts to meet a day’s food supply chain needs. Then, although the morning linen deliveries required 50 carts, those in the afternoon could occur with one fewer.

The researchers also learned it was only necessary to include essential building areas in their 3D models. Further, they recommended the hospital establish rules to govern traffic flow and create the conditions explored during digital twin testing.

Set Meaningful and Achievable Goals

People have used digital twins to get closer to well-defined aims, such as enhancing medical treatment outcomes or making it easier for customers to rent bikes. Any project combining RPA with digital twins is more likely to become successful if people have clear ideas of how the technology can help them overcome challenges.

An infrastructure services company in the United Kingdom has taken a data-driven approach to reducing road construction disruptions for more than a decade. Projections for a single year anticipated the business handling more than 2 million infrastructure-related transactions. Those overseeing the work use RPA to retrieve location-based asset data and manage the repeatable, high-volume tasks. Those duties include permitting, registrations and grid plotting.

Digitalization is a notable part of the company’s success, but workforce knowledge is another prominent factor. The highly skilled workers have in-depth knowledge of keeping projects on time and under budget while minimizing issues for members of the public who must keep using the areas under construction.

Infrastructure projects are also ideally suited for digital twin testing due to the coordination and large numbers of stakeholders involved. Feeding the above company’s data into a digital twin could alert parties to unforeseen obstacles they notice and address before construction begins.

Construction projects typically have numerous unknown variables that fluctuate as the work progresses. However, digital twin simulations can minimize those factors, giving people time to adjust. Using the digital twin allows for assessing details about traffic patterns, labour needs, administrative time frames and other specifics that could affect completion.

As the individuals involved examine how to get better outcomes from their RPA data, they should always proceed with goal-oriented mindsets. That way, they’ll stay focused on the desired outcomes rather than merely relying on digital twins because the option exists.

Take Advantage of RPA Data With Digital Twin Testing

Increasing RPA investments within a business can streamline processes, give people more time to handle complex responsibilities and reduce errors, among other benefits. However, the examples here show how testing various scenarios with digital twins can help people get the best results from their robotic process automation efforts. Then, users can uncover new insights revealing the best paths to meet goals and handle persistent challenges.

A best practice is to keep the people whose jobs the RPA will improve involved at every stage. Their knowledge can shape the development team’s priorities and show the best ways to enhance their work with technology.