Study
Commercial ProductionRecentModerate effect

Digital Twin Complexity Scales with Asset Lifecycle Stages

The sophistication and utility of a digital twin should evolve in tandem with the physical asset it represents, moving from basic data mirroring to complex predictive and prescriptive capabilities.

Applied System Innovation · 2023

01

Key Findings

  • 01Digital twins are not monolithic; their definition and application vary significantly.
  • 02A tiered approach (Levels of Digital Twinning) can effectively categorize digital twin complexity.
  • 03The UNI-TWIN model provides a structured method for assessing digital twin maturity and guiding investment.
02

Application

Design takeaway

Implement digital twins with a phased approach, scaling complexity and functionality as the physical asset progresses through its lifecycle, rather than aiming for a fully realized twin from inception.

How to apply

When designing or specifying a digital twin solution, map out the required capabilities for each phase of the asset's lifecycle (e.g., design, manufacturing, operation, maintenance, decommissioning) and plan the digital twin's evolution accordingly.

Project actions

  • 01Clearly define the scope and 'level' of your digital twin for your design project.
  • 02Justify why a specific LoDT is appropriate for your chosen product and its lifecycle stage.
03

Method & Evidence

AimHow can a framework be developed to categorize and assess the varying levels of complexity and functionality of digital twins throughout an asset's lifecycle?
MethodConceptual Framework Development and Case Study Validation
ProcedureThe research proposes a functional architecture for digital twinning, defining different Levels of Digital Twinning (LoDT) based on complexity and evolutionary capacity. A unified model (UNI-TWIN) was developed to help organizations assess their assets' LoDT and inform investment decisions. The model's applicability was validated through case studies in the road and rail sectors.
ContextEngineering asset management, particularly in infrastructure sectors like road and rail.

Variables

IVLifecycle stage of the physical asset
DVComplexity and functionality of the digital twin
CVType of asset, industry sector
04

Strengths & Limitations

Strengths

  • +Provides a much-needed conceptual framework for understanding digital twin variability.
  • +Offers a practical tool (UNI-TWIN) for assessment and decision-making.

Limitations

It might be difficult to fully simulate different LoDTs without advanced software or significant development time.

Reliability & validity

The conceptual nature of the framework and the limited scope of case studies may affect generalizability. Further validation with larger datasets and diverse industries is needed to establish robust reliability and validity.

Think critically

If a digital twin's value increases with its complexity, why would an organization ever choose a lower LoDT?

05

Design Principles

"Digital twin development should be iterative and adaptive, mirroring the lifecycle progression of the physical asset."

Understanding digital twins not as a static entity but as a dynamic, evolving construct allows for more strategic implementation and investment. This approach enables organizations to tailor digital twin development to specific lifecycle phases, optimizing resource allocation and maximizing value realization.

06

What This Means for Your Design

Think of a digital twin like a smartphone app that gets updated. It starts simple and gets more features as the product it represents gets older and needs more complex management.

How to use in your project

  • 1.Use the concept of Levels of Digital Twinning (LoDT) to justify the complexity and features of your digital twin prototype or simulation.
  • 2.Reference the UNI-TWIN model as a potential method for evaluating the maturity of digital twin concepts.
07

Add to My Project

08

Quick Cite

(2023). Reshaping the Digital Twin Construct with Levels of Digital Twinning (LoDT). Applied System Innovation. https://doi.org/10.3390/asi6060114 Retrieved from https://designdex.org/study/91b35241-c8ec-452b-bc31-cdcce11f1a37/digital-twin-complexity-scales-with-asset-lifecycle-stages

Paragraph starter

The development of digital twins should consider varying levels of complexity, or Levels of Digital Twinning (LoDT), that align with the lifecycle stages of the physical asset. This research proposes a framework where digital twins evolve from basic data representation to more advanced predictive and prescriptive functionalities, allowing for strategic investment and resource allocation tailored to specific operational needs.

09

Source

Applied System Innovation

Reshaping the Digital Twin Construct with Levels of Digital Twinning (LoDT)

journal · 2023

View source

Questions about this research

What does the research say about digital twin complexity scales with asset lifecycle stages?
Implement digital twins with a phased approach, scaling complexity and functionality as the physical asset progresses through its lifecycle, rather than aiming for a fully realized twin from inception. Evidence: Applied System Innovation (2023).
Why does "Digital Twin Complexity Scales with Asset Lifecycle Stages" matter for design?
Understanding digital twins not as a static entity but as a dynamic, evolving construct allows for more strategic implementation and investment. This approach enables organizations to tailor digital twin development to specific lifecycle phases, optimizing resource allocation and maximizing value realization.
How can designers apply this research?
Implement digital twins with a phased approach, scaling complexity and functionality as the physical asset progresses through its lifecycle, rather than aiming for a fully realized twin from inception.
What were the main findings?
Digital twins are not monolithic; their definition and application vary significantly.. A tiered approach (Levels of Digital Twinning) can effectively categorize digital twin complexity.. The UNI-TWIN model provides a structured method for assessing digital twin maturity and guiding investment.
What research method was used?
Conceptual Framework Development and Case Study Validation.
How strong is the evidence?
Evidence strength is rated Moderate effect, based on a 2023 journal from Applied System Innovation.
What should I do differently in my next project?
When designing or specifying a digital twin solution, map out the required capabilities for each phase of the asset's lifecycle (e.g., design, manufacturing, operation, maintenance, decommissioning) and plan the digital twin's evolution accordingly.
What are the limitations?
The proposed framework and model are conceptual and require further empirical testing across a broader range of industries and asset types.
Is there evidence that digital affects design outcomes?
Digital twins should be viewed as evolving systems with varying levels of complexity that align with the lifecycle stages of the physical asset they represent, and a structured model can help manage this evolution. Understanding digital twins not as a static entity but as a dynamic, evolving construct allows for more s Source: Applied System Innovation (2023).
Where does this digital twin research apply?
Engineering asset management, particularly in infrastructure sectors like road and rail. It sits within commercial production research on designdex.org.

Related research topics

digital design research · evidence on digital · does digital improve design outcomes · digital twin studies for designers · digital and digital twin findings · commercial production research evidence