Digital Twins: Transforming Manufacturing Processes Through Virtual Replication

Digital twins can rapidly drive operational efficiency, scale capacity, and increase resilience in manufacturing firms. Real-time virtual replication of the factory deepens understanding of complex physical systems and production operations, optimizes production scheduling, and simulates scenarios to understand the impact of potential actions.

Digital twins support fast, cost-effective decision-making. For instance, manufacturing leaders can use virtual replication to improve production visibility by enhancing demand forecasting, inventory processes, manufacturing flexibility, and real-time visibility of the factory floor.

Digital Twin Uses

The use of digital twins depends on the manufacturing firm’s operations:

  • During the initial investment and build of a factory, a digital twin can validate the layout design, optimize the footprint, estimate the inventory size, and evaluate spatial parameters for assets such as clearance, ergonomics, and employee movements within a cell.
  • Established manufacturing firms can use digital twins to predict production bottlenecks.
  • Live data can be used to model stochastic processes, inventory buffers, material travel times, and changeovers.
  • Insights from digital twins can be applied to optimize production schedules, balance lines, and prioritize continuous improvement opportunities.

Digital Twin Cases

The following case demonstrates how digital twins provided value for one manufacturing firm:

  • Digital twins redesigned the production schedule and compressed overtime requirements at an assembly plant to create a 5-7% monthly cost saving.
  • Virtual replication simulated real-time production line bottlenecks and uncovered manufacturing process blockages.
  • The model was integrated into the manufacturing execution system (MES) platforms, Internet of Things (IoT) devices, and inventory databases to optimize product line sequencing and minimize downtime.
  • The results adhered to production line capacity, warehouse storage confines, and customer delivery requirements.

Similarly, digital twins provided value for a metal fabrication plant:

  • Digital twins identified ideal batch sizes and production sequences to optimize scheduling thousands of potential product combinations across four parallel production lines.
  • An artificial intelligence (AI)-powered agent was trained to use the digital twin and reinforcement learning (RL) to build the optimal order sequence.
  • The RL algorithm created significant cost reduction and yield stability compared to manual scheduling.

Digital Twin Implementation

Limited awareness of digital twin capabilities, fragmented data landscapes inhibiting scalable solutions, and a lack of in-house talent to build and deploy virtual replication can hinder manufacturing firm leadership from implementing the models. Hiring talent to design and build digital twins can help.

Hire Manufacturing Talent to Build Digital Twins

Connectology can help source talent experienced in working with digital twins and other advanced manufacturing technologies. Contact us to learn more today.