Digital Twin Practice Guide: Efficiently Managing Twin Scene Production to Control Costs and Risks

Honghao Wang

01 Dec 2025 — 2 min read

Digital Twin Scene Production: Key Steps, Cost Control, and Requirement Management

In the construction of a digital twin platform, twin scene production is both the most fundamental task and the one most prone to project delays and cost overruns.

As a product manager involved in multiple large-scale infrastructure projects, I have observed recurring challenges during this stage — including unclear requirements, scope creep, and difficulty in controlling costs.

This article uses a major infrastructure project from our team as an example to outline:

Specific steps of twin scene production
Methods for effective requirements management
Strategies for cost control

Our goal: deliver expected results within budget.

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Three-Tier Work Breakdown for Scene Production

Twin scene production can be divided into three main phases:

Model Production
Scene Integration
Interaction & Data Driving

Clearly defining goals and deliverables at each stage is critical for scope control.

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1. Model Production — From Physical Object to Digital Model

Key categories:

Main and temporary construction models
Refine main structure models and create temporary structure models (e.g., trestles, prefab yards).
Define model granularity:
Key engineering elements: high-precision reproduction based on site data.
General representation: simplified using LOD levels.
Use area-based pricing units to maintain cost control.
Equipment and facility models
Include not just visual modeling but also:
Skeleton binding
Parameter configuration
This prepares models for dynamic interaction.
Model pre-processing & code linking
Lightweight models
Standardize formats
Associate business codes (e.g., WBS) with model components — making them data carriers.

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2. Scene Integration — Building a Unified Digital Environment

Scene restoration: Integrate terrain, buildings, equipment using real-world coordinates.
Basic interaction & anchor points:
Enable scene roaming
Place interaction anchors (e.g., cameras, operation points) for feature activation.

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3. Interaction Implementation & Data Driving

Layer and visibility control:
Allow filtering by engineering section, component type, construction status to focus on relevant data.
Dynamic response & interface development:
Connect to business systems (progress, monitoring, resource data).
Drive scene actions such as:
Model growth
Machinery operation
Alert prompts

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Key Experience: Managing Requirements & Controlling Costs

In practice, clients often struggle to define scene granularity or interaction depth early on, leading to scope creep and budget issues.

1. Use “Visualization + Quantification” to Eliminate Ambiguity

Present scene diagrams and model precision samples during requirements discussions.
Show visual and cost differences at varying levels of detail.
Provide transparent unit pricing table, e.g.:
Key engineering modeling: `X currency / sq km`
Equipment skeleton binding: `Y currency / category`
Data interface development: `Z currency / category`

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2. Give Clients Choices While Staying in Control

Offer a structured, quantified service list.
Let the client select features within their budget and goals.
Helps set clear scope boundaries and optimize resource allocation.

> Lock scope for scene granularity and interaction depth early in large projects to ensure on-time, on-budget delivery.

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Cross-Industry Portability of the Methodology

This decompose → quantify → controlled delivery approach works across:

Infrastructure
Intelligent manufacturing
Smart parks
Smart cities

Core benefits:

Transform ambiguous requirements into standardized, executable actions
Minimize commercial risk via structured pricing
Support diverse scenarios using reusable technical architectures

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Leveraging AI and Cross-Platform Tools

In today's AI-driven ecosystem, platforms like AiToEarn官网 enable:

AI-powered content creation
Cross-platform publishing
Analytics and monetization

Such tools can complement scene production by streamlining workflow and connecting creation to ROI across channels like Douyin, Kwai, Bilibili, Instagram, LinkedIn, and X.

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Conclusion

Twin scene production is a blend of technology and management.

Success comes from:

Step-by-step breakdown
Quantified cost control
Transparent requirement management

This methodology is equally applicable in manufacturing and smart city projects.

By setting reusable work frameworks and a strong risk control mechanism, teams can maximize project value and collaboration efficiency.

We welcome exchanges and discussions about applying these methods in your own scenarios.

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Tip for Teams: Pair structured production frameworks with AI-enabled content and operations tools like AiToEarn官网 to bridge technical execution with sustained creative output across multiple platforms. This ensures efficiency and monetization are built into the project lifecycle.