Beyond the Digital Twin: From Equipment Monitoring to Better Decision-Making

By March 27, 2018Internet of Things, PLM
Triple Self Portrait (Norman Rockwell, 1960)

Enterprise digital transformation initiatives that exploit the potential of the Internet of Things (IoT) are expanding the boundaries of newly-created managed networks of connected assets spread over large geographical areas.

Fundamentally, the industrial IoT helps asset owners to move away from traditional routine maintenance schedules and visual inspections and invest in new methods such as remote asset tracking and monitoring. Product organizations initiate highly optimized data-driven operations to drive greater efficiencies and cut costs of asset management and maintenance.

But forward-looking organizations do not stop there. They evaluate and deploy cyber-physical models that provide unprecedented visibility, insight and decision-making capabilities to optimize existing operations, and for new value creation through innovative customer-centric engagements and new revenue streams.

The Digital Twin

A digital twin is a live digital representation of a physical asset. It is a cyber-physical mockup of a connected device that represents both the physical instance and its broad business context in which it operates from inception to its end of life.

Digital twins act on behalf of connected physical objects by receiving alerts and notifications, sending instructions and updates, and provide real-time information to the owners, operators and maintainers of these assets on their state and condition.

Digital twins are an integral part of the assets’ control flow and lifecycle activities. Beyond mere remote connectivity, a digital twin is aware of and represents a broad spectrum of information and lifecycle activities such as configuration, service entitlement, and maintenance and upgrade history.

From Mere Awareness to Smart Decisions

The connected enterprise facilitates and accelerates the formation of a trusted network of digital twins. Always-connected products and customers provide a broad and deep insight, in real time if needed, across multiple markets, product configurations, and customer groups. A digital model that is constantly interacting with actual products and monitoring their operation and user interactions give product organizations an unprecedented ability to collect, organize, and analyze information from products and business activities, and curate and deliver deep and rich insight about all aspects of a product value chain.

The digitalization of the enterprise’s value chain radically redefines how well individual decision makers and the organization understand current products and customers, and how they use this wisdom to accelerate innovation, develop new products, and service and optimize existing ones.

Bridging the Chasm

Older product lifecycle paradigms are crudely separated by value chain activities and the PLM software systems supporting them. There is a distinct—and often difficult—handover from engineering to manufacturing, and an even bigger chasm between manufacturing to operations and after-sales service and maintenance.

The digital twin should serve as the central integration point for the numerous stakeholders working on or with the assets throughout the product lifecycle. And product-generated information and PDM-based 3D models and configuration information must be augmented by information and insight from sources that typically reside outside the traditional boundaries of the organizational enterprise software systems. For example, information about inventory levels, competitive products, and market intelligence should be systemized and used in simulations, statistical analyses and machine learning to drive better decision-making.

A connected enterprise that focuses on the curation of multidisciplinary information must strive to further expand the traditional boundaries of product-centric information and incorporate formal and informal social media information about product operations and customer interactions. Not only does human-generated data offer early warning signs and ongoing feedback about product failures and quality, but it also offers an unvarnished eye-opening testimonial about customer sentiment and attitudes towards product features and usability, and the strength of the brand.

Forward-looking organizations must become more “thinking”, intimately connected to all data sources and enabled with comprehensive and fast analytics and collaborative decision-making. The multidisciplinary decision-making processes driven by networked digital twins and social media help product organizations and individual decision-makers to see clearly, remove guesswork, and act intelligently and with confidence.


Image: Triple Self-Portrait (Norman Rockwell, 1960)
This article was sponsored by Siemens PLM