Technology for the supply chain

Businesses are looking to cutting-edge technologies such as AI, ML, and IoT technology solutions to reinvigorate their supply chain efforts. Industry insiders hope that “digital twins” could play a role in this balancing act.

“Digital twins” come from the software world and describe a copy of the real device or system that exists electronically in a virtual space. The goal is to create a “twin” that reflects a real work system along with the processes they are part of.

Fast Company more succinctly states that digital twins are “the process of using streams of data to create a digital representation of a real-world asset to enhance collaboration, information access, and decision-making.”

This is not futurama neither do things. By 2025, the market size for digital twins is expected to increase by around 40%, while more than 90% of IoT platforms are likely to leverage some aspect of digital twinning capability by 2026.

Manufacturers in the supply chain can use digital twins as a basis for alignment and local decision-making in the supply chain. Additionally, by using data and predictability results in digital twins and reducing physical prototyping requirements, teams and organizations will find more flexible testing scenarios that help save time and money.

More than a concept

Digital twins are more than a concept. Organizations can create a working twin to help teams further develop their products. The virtual product created with AI and machine learning helps to inform the physical product. Likewise, digital twin technology works in reverse. It is a two-way flow of information that helps refine products and processes.

For example, digital twin technology can show engineers exactly how a home or office building might hold up over time due to weather, extreme sun exposure, natural causes, or more. Then the engineers can build the structures with sensors to help monitor the buildings. The sensors collect and relay data about the nature of the physical structures. This could include important data on temperature, wind, energy use and more.

Once this data has been captured, it can be sent back and processed into the virtual twin. At this point, engineers use the virtual model for various exploratory practices. For example, they can examine the buildings to see how they are holding up to environmental stress. In addition, they can undergo simulations to check potential for improvement. All of this research is expected to yield valuable insights that can then be carried over into future iterations of the physical twin. All of this contributes to feeding a two-way flow of data and information.

Digital twins in materials management

Companies have been dealing with digital twins and data points for some time. What is exciting is that this technology can positively impact the supply chain by simulating large, complex processes, using real-time data and enormous computing power.

But to get there, companies must have clear visibility across their entire supply network. A disorganized inventory of material parts has slowed the transition to digital twin technology. In many organizations, the physical parts are stored in a chaotic manner. As a result, duplicate materials can occur and a company may not know which parts are bottlenecked or which materials are shared across the company.

In some warehouses, the indirect materials may be located in storage bins in multiple storage rooms in the network. Therefore, companies need to get organized before proceeding with the creation of digital twins.

Organization for indirect materials

Digital twin technology can help organize indirect materials. Understanding indirect materials like MRO and putting the pieces together can be a game changer.

The solution is there and does not require data or system overhauls of business processes. Instead, achieving Material Truth across the enterprise lays the foundation for the scalability and functionality of digital twin technologies.

Improve usability with AI technology

More than 90% of global procurement leaders, in a Globality survey, said they are moving quickly to transform existing operational processes and models to gain a competitive advantage. Additionally, they are focusing on new AI and ML technologies to get more value out of their data.

These leaders indicated that they are building digital and data teams to integrate these emerging technologies into their organizations. They expect valuable insights from these steps and are better prepared to adapt flexibly to economic or structural disruptions in their organizations.

It’s time for companies to move forward. An MRO supply ecosystem enables companies to streamline procurement processes on time and to the organization’s specifications. It’s about connecting supplier data to internal networks and between sites. This helps the company get closer to autonomous procurement.

By moving material data into an MRO intelligence platform and out of spreadsheets and ERP spreadsheets, optimizing digital networks and creating the basis for digital twin processes, a company can achieve consistency and governance of its material data.

Take a closer look. Upgrade your organization’s MRO management by investing in the efficiency and accuracy of new MRO technology.

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