Manufacturers can use digital twins to conduct analyses of processes or operations to predict future performance.
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Manufacturers can use digital twins to conduct analyses of processes or operations to predict future performance.
Running simulation scenarios can help identify bottlenecks and avoid costly expenditures.
Digital twins models can be easily modified to evaluate new operating scenarios in the future.
Digital twins—essentially virtual representations or simulations of physical operations—allow manufacturers to see how a process or operation performs in real time and predict how it may perform in the future. This type of simulation will increasingly become table stakes in the smart factories of the future.
One RSM client, a midsize industrial food production company, used digital twins to optimize its bulk inventory management capabilities and ultimately determine which investments in personnel, storage tanks and other supporting storage capacity were necessary. Through simulation, the business was able to refocus investments on areas of the business that would yield more value. We explore the factors at play in putting this transformative technology into action.
At the outset of the project, the industrial food production company had numerous priorities: making operations as efficient as possible, improving business processes and reducing operating expenses while also prioritizing capital investment. To achieve those objectives, the company had purchased production line equipment that would enable it to produce a greater volume of product, but it needed to understand the upstream implications before increasing capacity.
In running a simulation that accounted for more staff, the scenario met the target sales goal, effectively reducing guesswork of how the business might need to augment staff to accommodate growth.
That’s where a simulation analysis proved helpful. The company fed operational data into a digital twin model and ran various simulations to determine the appropriate size of production equipment that would be needed to meet the production line demands. Solving that question had many variables, including product mixes, batch sizes, upstream processes’ capacity, new and existing equipment, and plans for future growth.
The main challenge was to determine whether the future-state production system could meet the company’s sales goal of producing an additional 9.5 million pounds of product per year, and how to make sure the organization understood the broader change and impact that growth would have on operations.
RSM’s engagement with the company involved a three-phase approach using digital twins to address that challenge:
The foundational importance of digital twin simulations lies in the fact that they can help businesses transform data-driven insights into real-world decisions.
Understanding specific inventory and staff levels is just one aspect of the use case for digital twin simulations. This technology also helps organizations understand the design and layout needs of their warehouse and production facilities and improve stakeholder understanding of impending changes by using 3D representations to explain the change and supporting rationale.
The simulation’s flexible model and dynamic scenario levers enabled the company to experiment with real-world variability that showed the range of expected performance across multiple simulation runs. Models are an enduring asset, and easily modified to evaluate new operating scenarios in the future.
The foundational importance of digital twin simulations lies in the fact that they can help businesses transform data-driven insights into real-world decisions. For many manufacturers, this capability will be paramount as economic and margin pressures require many companies to shift from a “grow-at-all-costs” strategy to one that focuses on profitability.
Businesses should investigate how digital twins might help them optimize operations through the evaluation of multiple potential scenarios, including:
All of this can ultimately help organizations better understand where to focus their investments and adapt operations as needed.
This article originally appeared in the Manufacturing Leadership Journal, a publication of the Manufacturing Leadership Council.