How Digital Twins Drive Intelligent Edge in Manufacturing – Part 1

In the evolving landscape of the Internet of Things (IoT), the concept of digital twins has surged to the forefront of manufacturing innovation. According to Sukamal Banerjee, Corporate Vice President – ERS Sales (Hi Tech & Comm) and Head of IoTWoRKS at HCL Technologies, the industry is finally overcoming the technical hurdles that once prevented a true digital twin from being realized.

Digital twins are not a new idea. First coined in 2003, the term has even been applied in NASA’s Apollo program, where simulated models of spacecraft were paired with their physical counterparts. Today, advances in edge computing, 5G connectivity, and sensor technology enable manufacturers to create accurate, real‑time digital replicas of assets, processes, and entire production lines.

Gartner’s research predicts that by 2021, 50 % of industrial firms will adopt digital twins, reporting an average efficiency improvement of 10 %. A digital twin is essentially a live, sensor‑driven image of a physical object or system, linked by a continuous data stream—known as a digital thread—that captures the object’s current state and its historical evolution.

Beyond real‑time monitoring, digital twins store detailed historical profiles, allowing companies to conduct longitudinal analysis, predict failures, and refine operations over time. This capability is especially critical in manufacturing environments where complex machinery and human operators must work in close coordination.

Visualization: The Human Edge in Decision‑Making

Visual perception dominates human decision‑making. Factory managers traditionally relied on an elevated position to observe the entire production floor. As plant machinery becomes more sophisticated, that advantage diminishes. Computer‑based dashboards now provide data sheets and basic charts, but they often overwhelm managers with raw numbers.

A digital twin unifies the best of both worlds: it delivers real‑time data in a faithful visual replica of the physical asset. By filtering out non‑critical information and presenting key metrics—such as temperature, vibration, and wear—directly on the virtual model, decision‑makers can grasp complex status at a glance.

Moreover, digital twins enable dynamic visualization—360° views, micro‑ and macro‑scales—providing a flexible lens for inspection. The platform also supports instant benchmarking against historical performance or industry best‑practice benchmarks, revealing improvement opportunities and urgent concerns with unprecedented speed.

In the next installment, we’ll explore the second pivotal reason why digital twins will reshape manufacturing—and outline the strategic questions firms must answer before embarking on a digital twin journey.

Author: Sukamal Banerjee, Corporate Vice President – ERS Sales (Hi Tech & Comm) and Head of IoTWoRKS at HCL Technologies.