Unlocking Manufacturing Efficiency: The Tangible Benefits of Digital Twins

The manufacturing sector faces immense challenges. Supply shortages, elevated demand and a volatile market force businesses to adopt new strategies to stay competitive.

Many manufacturers are turning to Industry 4.0 innovations, like industrial IoT, artificial intelligence and cloud computing, to boost productivity, reduce operating costs and respond to changing market conditions.

Digital twins, a new technology that can leverage IoT, AI and other technologies to simulate a high-fidelity copy of a real-world facility, could help offer owners a better understanding of plant operations and potential barriers to productivity.

What Are Digital Twins?

Digital twins are virtual representations of an existing object, product, workflow or facility. It is typically designed to match their source as accurately as possible — ideally, to the point that the twin can act as a replica.

For example, a building’s digital twin may be a one-to-one scale model. It may have the same HVAC systems, plumbing, lighting and even materials. Information from networked sensors, like IoT airflow, foot traffic and lighting monitors, can provide additional data.

The high fidelity of the replica allows end-users to leverage it for various purposes, including simulating, forecasting and visualizing building processes.

One end-user may take advantage of HVAC modeling and an airflow algorithm to identify weak points in a building’s air conditioning system. Another may use data from IoT devices to turn the digital twin into a real-time monitoring system that offers powerful visualizations on building networks and performance.

In addition to modeling a building, a business could also use digital twins to feature objects and processes at varying scales — from the company’s entire supply chain down to an individual plant machine or component.

The Digital Twin in Manufacturing

Digital twins offer a variety of potential benefits to manufacturing plant owners— including improved monitoring, streamlined quality control and data visualization.

Visualizing IIoT Data

Digital twins synergize well with IIoT monitoring fleets, which are becoming increasingly common in the manufacturing sector. Data from IIoT monitors can be used to create more accurate twins, improving the model’s forecasting power.

End-users can also visualize IIoT data using the digital twin, helping to reduce some of the confusion that can come with parsing the vast quantities of information IIoT systems may capture.

For example, a business can use IIoT and an existing plant digital twin to represent plant airflow, foot traffic or the movement of goods. If there are significant production bottlenecks in the facility — like a conveyor belt limiting plant throughput — this visualization can help managers identify them.

The same approach can also be used to identify layout inefficiencies, traffic bottlenecks, maintenance alerts or even potential safety violations.

No matter what data an IIoT sensor tracks, it can be tied to a location represented somewhere in or on the digital twin, allowing managers to better understand valuable IIoT-captured information on the real-world performance of the plant.

Predictive Maintenance and Real-Time Equipment Monitoring

Networked sensors and machines can continuously report information on plant equipment performance. This data can be provided to a digital twin, providing managers with a bird’s-eye view of machinery’s health.

If a machine in the plant begins to behave unusually compared to a baseline, the system can alert managers, providing them with the exact location of the issue. A digital twin could make it possible to pinpoint the precise component that failed.

A preventive maintenance strategy combined with real-time monitoring can help owners drive down maintenance costs and reduce the risk of downtime.

AI makes it possible to go even further. Historical data from IIoT machine sensors, combined with manufacturer data, can be used to train an algorithm that may predict when machines will fail. Using the data a business already corrects means the algorithm can enable a predictive maintenance strategy to further reduce operating costs and downtime.

Planning Upgrades and Layout Changes

The digital twin can be particularly useful in auditing and planning upgrades or reorganization of the plant. For example, common line layout mistakes can become more obvious when you combine a digital twin with traffic or resource flow data showing where workers and goods are getting stuck.

A digital twin and HVAC system modeling allows for reviewing the current system’s effectiveness and simulating how a new HVAC operation would help improve airflow, boost plant comfort, and maintain site air quality.

Some businesses may need to meet industry standards on worker exposure to airborne particulate matter. Managers can use air quality models to simulate that exposure — helping them determine if an upgrade will be efficient enough to keep site workers safe.

Analyzing Plant Processes

Digital twins can help managers better understand how their plant operates and fits into the business’s overall structure. Digital twins can model workflows, processes and supply chains, and a combination can allow managers to “zoom out” from their plant and observe the flow of goods from warehouses and vendors.

The same technology can also allow managers to “zoom in” and view the movement of individual components and items throughout the plant. RFID trackers and similar devices attached to a pallet or part can provide managers with a picture of how goods travel through their plant and the manufacturing process.

Data from these systems can also help improve a site’s traceability initiatives. The right information can determine the source materials and manufacturing conditions for every item that comes off the production line.

Manufacturers that suspect issues with a particular lot or set of items can have managers review production data to identify the things most likely to be impacted, helping reduce the scope of a recall.

Using Digital Twins to Streamline Manufacturing Plant Processes

Digital twins may be one of the best tools manufacturers have for adapting to new market conditions.

Managers can use the technology to more effectively visualize data captured by an IIoT fleet or analyzed by AI algorithms. A digital twin can also help businesses simulate plant operations, identifying potential vulnerabilities or bottlenecks in workflows.

Digital twins could become an essential investment for manufacturers as market volatility and growing demand make manufacturing efficiency more important.