Distinct Digital Twins Have Emerged for Discrete and Process Industries

Executive Overview

A digital twin is a virtual representation of a physical system. With that commonly used short definition, many software categories – old and new - can be called a “digital twin.” This broad digital twin branding has led to confusion and chaos in both understanding what is really new and the appropriate applications. Supplier marketing teams are often motivated to maximize market reach and lead generation, which causes them to avoid being specific regarding suitable user applications and business benefits. Confusion abounds with both supplier sales teams and prospects often pursuing dead ends. The associated disillusionment and wasted time have become a significant market inhibitor.

The applications for digital twins have matured with distinct needs, business benefits, and use cases which include:

• Discrete industry in the product lifecycle value stream
• Process industry for improved asset management
• Building information modeling (BIM) for the design and construction of commercial buildings which can extend into operations
• Infrastructure for architecture, engineering, and construction projects
• Smart cities for planning and management

This report focuses on use cases in the value streams for discrete industry product lifecycle management (PLM) and process industry asset lifecycle management (ALM) including case stories. Key findings include:

• Discrete industries should consider digital twins for:
  • Assembly line simulation for the next upgrade
  • OEMs for a new recurring revenue stream
• Process industries should pursue digital twins for:
  • Improved plant upgrade or greenfield project management
  • Asset management and operations after handover
  • Digital twin application providers should assure its software can migrate from a project digital twin to a performance digital twin in the process industries

Scope for Digital Twins and Metaverse

ARC has reviewed over a hundred digital twin projects and researched the potential of an industrial metaverse. Even though the adoption of digital twins is a relatively recent phenomenon compared to other types of industrial software, applications have started to segment according to vertical industry needs. The concept of an industrial metaverse across an extended enterprise has also started to form. For digital twins, this report defines each segment along with applications, use cases, and business benefits.

From Predictive Maintenance to 3D Plant Model

Initially, digital twins were focused on combining process data (pressure, temperature, etc.) and equipment data (vibration, current, etc.) for robust predictive maintenance applications. The focus was on equipment with time-series data, data management, and predictive analytics. During the past five years, digital twins have matured and moved well beyond this specific use case. The expanded scope includes engineering data, dimensional accuracy, visualization, and business processes for plants, buildings, infrastructure, or cities. Now, digital twins address a broad set of comprehensive applications that involve information management using a 3D model.

Digital Twin Definition

The term “digital twin” appears in many vendors’ marketing programs with a wide variety of interpretations. The first step for a meaningful review and recommendations requires a definition and description of the term:

A digital twin is a virtual representation of a physical system including its environment and processes. The twin is dynamic through the exchange of information among the physical and virtual systems. Uses span across design optimization, preventing bad events, improved decision support, business process management, and cross-functional collaboration.

Each digital twin has these key aspects:

• A physical asset – equipment, unit, line, plant, infrastructure, or city
• Virtual representation of the asset
• Data federation or continuously synchronized data transfer
• Integration with related applications for automated business processes

The nature of a digital twin tends to change as the target asset scales up from small (equipment) to large (a plant or city). Small twins are often an algorithm for predictive maintenance (PdM), equipment operating performance (operator guidance), and energy management. Plant or city twins usually involve an enterprise application for information sharing, business process automation, and collaboration using a 3D model as the user interface for navigation and situational awareness.

Segmenting Digital Twins

The market for digital twins has matured into applications that have coalesced around specific industry segments. This includes discrete, process, commercial buildings, infrastructure (utilities, roads, and bridges), and smart cities. These digital twins are segmented into:

• Discrete Industry Digital Twins: Used in the discrete industries where OEMs manage the PLM value stream including as-designed, as-built, as-serviced, and servitization. Also, digital twins for assembly line design and commissioning shorten the time to production with reduced risk
• Process Industry Digital Twins: Applied to plants for information and business process management during:
  • Design and build project for a plant across potentially thousands of engineering and contractor personnel for engineering, procurement, and construction (EPC)
  • Operations and maintenance phase of a plant’s lifecycle across the asset management functions that are often departmental silos
• Building Information Modeling involves design and construction of commercial buildings. After handover, this type of twin can extend into operations for building management including new tenant buildouts, upgrades, office occupancy optimization, HVAC energy management, and security.
• Infrastructure Digital Twins are used in the design and build of architecture, engineering, and construction (AEC) projects including highways, bridges, airports, dams, utilities (power, telecommunications, and water), and a variety of other major infrastructure.
• City Digital Twins provide a platform for city planning and management including zoning, vehicle and pedestrian traffic, disaster response, utilities, infrastructure, hydraulic modeling, and carbon emissions.

This list of the leading applications for digital twins is not meant to be comprehensive and complete. Other less common uses exist for software models and simulation where the term ‘digital twin’ is being applied. The rest of this report focuses on digital twins that apply to the first two bullets: discrete industries with OEMs and process industries for plants.

Industrial Metaverse

The concept of an industrial metaverse goes beyond a big digital twin. It considers the interconnection of business centers within an enterprise, and in time may expand to encompass the extended enterprise of suppliers and customers. The focus typically becomes improved visibility and issue resolution across the materials management applications including order entry, enterprise resource management (ERP), manufacturing execution system (MES), and supply chain management (SCM) applications.

This industrial concept is very different from Meta’s (formerly Facebook) vision of a consumer digital twin for social networking with avatars and virtual reality (VR) goggles.

User Interface Driven Market Discontinuity

Those comfortable with using drop-down menus and dialog boxes may not recognize a current dynamic for software user interface (UX). Since they were in grade school, gamers have been using video games with a 3D environment. Rather than asset hierarchy trees and tables, they are comfortable with having a 3D user interface for navigation. As this gamer cohort move further in their careers to become engineering managers, their inherent preference for navigation using 3D models will increasingly impact software selection.

ARC believes we are likely in the early stages of a transition to a 3D model becoming the preferred means to navigate more comprehensive software applications. This represents a market discontinuity where the early adopters gain market share at the expense of laggards.

Table of Contents

• Executive Overview
• Scope for Digital Twins and Metaverse
• Discrete Industries for Augmenting PLM
• Process Industries: Augmenting ALM
• Digital Twin Case Stories
• Recommendations

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