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4 Things Decision Makers Should Know About Manufacturing And Supply Chain Responsiveness

Supply chain risk is something enterprises can’t eliminate. But learning how to mitigate and adapt to that risk differentiates successful businesses from those that could buckle under pressure.

Here are four steps decision-makers can take to ensure that their organizations’ supply chains are responsive and resilient.

1. Ask—and answer—the “what-if” constraint questions

It’s a manufacturer’s job to optimize production under all supply chain and operational conditions. To that end, manufacturers must come to terms with “what-if” questions: What if we don’t receive the required raw materials on time? What if vendors can’t fulfill our raw material orders in full? What if there’s a serious system breakdown and we get nothing?

Posing and formulating answers to what-if questions can help an organization confront tough supply chain situations and boost resilience. To best answer these questions, original equipment manufacturers (OEMs) can use modeling systems, advises Guillaume Vendroux, CEO of DELMIA, the supply chain solution at Dassault Systèmes.

Modeling systems are virtual simulations that enable manufacturers to predict how a system will behave under different supply chain scenarios so they can tweak operations in the real world.

“In a lot of cases, you can fully simulate production flow in the shop to the point where you can actually manage automation,” Vendroux says. Manufacturers need not test-drive prototypes of new products, since computer-driven simulations can predict outcomes more efficiently, he explains.

2. Deploy virtual twin technology

In manufacturing, the confluence of digital transformation and machine-to-machine communications from the Industrial Internet of Things (IIoT) has led to an evolution of these classic simulation models. The input of IIoT data from machines and the digitalization of all manufacturing processes—from engineering and manufacturing to supply chain and beyond—has created a unified virtual twin experience.

A digital representation of real-world data embedded within manufacturing processes, the virtual twin is revolutionary because it “fully describes the [manufacturing] process end to end, not just by verticals,” Vendroux says. In doing so, it captures all interdependencies and uses them to deliver optimized answers to what-if questions.

“We can use the virtual twin to control what’s happening on the shop floors, and the feedback is immediate and real. We’re actually inputting real-time data,” Vendroux says. “[If] something is not working right, you can revert to the virtual twin and optimize and define the next best path forward.”

What works in managing a shop floor works in managing a supply chain, too. Logistics decision-makers working with virtual twin technology can “apply a set of changing constraints, like moving suppliers [and] quantities, [to more quickly] learn how that affects outcomes,” Vendroux says. Different variables can be input to see what results emerge. “The key here is to gain resiliency, agility and speed.”

3. Lean on data optimization—not guesswork

The biggest advantage of the virtual twin is that it eliminates much of the human subjectivity that, despite the best intentions of logistics experts, remains somewhat inherent in their craft. “It’s optimization, not guesswork,” Vendroux says. “It’s about doing the hard work of trying all available solutions and arriving at the best one.”

Another significant advantage is the ability to handle complexity, which is especially important given today’s intricate global manufacturing supply networks. Vendroux asks that we imagine a supply chain situation that combines “quadruple sourcing for a given product” with “multimodal transport possibilities.” The sheer complexity of such a situation is daunting. But using virtual twins “to combine all those constraints gives you agility” in navigating and managing it, Vendroux says.

4. Start small—and include employees

A manufacturer that wants to put virtual twin technology to work should start small and add elements incrementally, Vendroux says.

A 3D representation of the organization’s manufacturing floor might serve as the first informational layer for its virtual twin. The company can use that layer to run simulations of different floor layouts and capture results. It might set itself to determining what arrangement of machine elements and human workers on a shop floor is most efficient, for example.

Another key to success is to focus on people, Vendroux says. “Digital transformation is a way for people to understand where they fit into the scheme of things. It’s about visibility, so you know where you are and you understand the impact your action will have on the rest of the system.” Here managers might determine what arrangement on a shop floor—or in a logistics facility—makes human workers productive, not to mention safe.

When it comes to supply chain responsiveness, meanwhile, virtual twins let companies access both short- and long-term insights.

“The long-term [profitability] of your company depends on your ability to strategize where you want to go and [how] to optimize the path to get there,” Vendroux says. Such strategizing and optimization are precisely what the virtual twin delivers: “You can use a virtual twin model for instantaneous optimization of performance and long-term strategic evolutions.”

A look toward the industrial future

At the Hannover Messe industry trade show, which took place in its namesake German city in May 2022, Dassault Systèmes demonstrated a leading-edge example of virtual twin technology in the form of its DELMIA solutions on the 3DEXPERIENCE platform, which is specifically tailored to drive supply chain responsiveness.

The French industrial technology leader also displayed a sustainability overlay that will make DELMIA invaluable for manufacturers who want to assess how various supply chain variables affect their carbon emissions, among other things.

Such startling technology will drive the next era of industrial production, making logistical planning more precise—and supply chains more responsive and resilient.

Manufacturers may not be able to prevent the next big supply chain challenge. But, with the right technology, they can take giant steps toward weathering it and even coming out ahead.


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