The Challenge
One of the largest semiconductor manufacturers globally faces significant challenges in managing its complex supply chain. With operations spanning across multiple regions, the company encountered issues such as:
- Improving the flow of products through the supply chain
- Reducing delivery times for semiconductors
- Increasing chip availability
- Managing rising costs and risks
Due to the complexity of the global supply chain and the many variables involved, these problems were difficult to address using traditional methods like Excel, which were time-consuming and not scalable. The need for a more advanced and repeatable solution became apparent, especially as global disruptions, such as the COVID-19 pandemic, exposed vulnerabilities in supply chains, particularly in regions heavily reliant on semiconductor production.
A key concern during this period was the company’s over-reliance on manufacturers in specific countries, which created bottlenecks when global demand for electronics surged. The pandemic highlighted the need for diversifying the supply chain to reduce reliance on specific regions and improve proximity to key markets.
The Solution
To address these challenges, the company adopted a digital twin approach to better understand, visualize, and optimize its supply chain at a strategic level. This digital twin provided real-time insights and allowed the company to run a variety of scenarios to improve decision-making. The digital twin was used for several key tasks, including:
- Optimizing the network for existing products
- Designing the network for new product launches
- Analyzing the impacts of mergers and acquisitions
- Reducing end-to-end throughput times
- Considering carbon emissions in network design decisions
One critical use case of the digital twin occurred when the company faced the closure of its Shanghai distribution center due to COVID-19. Instead of reacting blindly to the situation, the company used its digital twin to run scenarios that modeled the impact of the closure. This allowed the company to analyze where to store its products and assess the cost and delivery time implications. The digital twin provided valuable insights, enabling quick, informed decisions during the disruption.
Results
The implementation of the digital twin and advanced network design tools allowed the company to improve its supply chain management in several ways:
- Optimizing the distribution and production footprint to enhance efficiency
- Enabling the company to integrate new products into the network seamlessly
- Reducing reliance on complex spreadsheets and consolidating data in one place
- Modeling carbon emissions to support sustainability goals and reduce environmental impact
- Enhancing business continuity planning by providing a proactive approach to handling disruptions
By upgrading its supply chain management tools and adopting a more data-driven, scenario-based approach, the company gained the ability to make more strategic decisions in response to both anticipated and unexpected challenges. The digital twin not only helped the company address short-term disruptions but also allowed it to future-proof its supply chain by optimizing for cost, service levels, and sustainability.
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