Manufacturing teams operate in environments where small mistakes can have outsized consequences. Safety and uptime depend on how well people understand the physical reality of the factory floor, not just how systems are supposed to work on paper.

Digital twins help close that gap. By creating accurate, visual representations of real production environments, teams gain a shared source of truth they can use to train operators, plan changes, document processes, and coordinate work across roles and locations.

In this article, we’ll look at how digital twins are being used in manufacturing today, with a focus on factory-level visibility and operational decision-making. You’ll see how 3D models ground data and workflows in real-world context to help teams work more safely and make better decisions day to day.

What is a digital twin in manufacturing?

Digital twins are used across the manufacturing lifecycle, from planning and production to operations and maintenance. They support training, space planning, and documentation, and they allow teams to review conditions or plan changes without interrupting live operations or putting people at risk.

In manufacturing, a digital twin is a visual representation of a physical product, machine, or workspace. It reflects real-world conditions and helps teams understand how equipment, processes, and environments actually operate on the factory floor.

In manufacturing, digital twins are typically used at four levels: individual assets, production lines, entire factories, and multi-site supply chains. Each level supports different goals, from monitoring equipment to coordinating operations across locations.

Matterport is strongest at the facility level, across multi-site use cases. These higher-level digital twins focus on capturing real facilities and connecting sites, giving teams the spatial context they need to plan work, document conditions, and collaborate without being on-site.

The table below breaks down the four levels of digital twins in manufacturing and explains when each one is most useful.

Industry 4.0: How digital twins and smart technology are transforming manufacturing

At the dawn of the 19th century, steam power and mechanization led to the first industrial revolution. Two centuries later, we find ourselves in the midst of Industry 4.0 — a digital transformation that integrates digital twin modeling, augmented reality, the Internet of Things (IoT), and machine learning to enhance manufacturing productivity and automation of many key processes.

According to Deloitte’s 2025 Smart Manufacturing and Operations Survey, 78% of respondents allocate more than 20% of their overall improvement budget toward smart manufacturing initiatives, and 88% expect investments to continue or increase in the next year. 

Industry 4.0 and digital twin adoption patterns vary by sector:

• Automotive: Complex production environments and frequent line changes create planning challenges. Digital twins are used to document and coordinate these environments, where factory-level twins help plan retooling, validate layouts, and align internal teams and suppliers without slowing production.

• Electronics and high-tech: Rapid product cycles and dense equipment layouts drive adoption. Digital twins give teams a reliable way to plan space, onboard new processes, and communicate changes when physical access is limited.

• Pharmaceuticals: Strict validation and access controls make in-person walkthroughs costly. Digital twins support remote review, training, and documentation while maintaining compliance and minimizing disruption.

• Chemicals: Hazardous environments and aging infrastructure increase risk. Digital twins provide a safer way to understand layouts, plan maintenance, and review procedures without exposing staff to unnecessary danger.

• Food and beverage: Continuous production and hygiene requirements restrict access to live facilities. Digital twins are used to support training, audits, and equipment planning without interrupting operations.

With Matterport, teams have access to a digital twin that models a physical space at one moment in time. When integrated with IoT sensors, those digital twins can extend beyond documentation to support real-time awareness and operational decision-making. Together, these technologies help manufacturers improve safety and automate processes while staying grounded in the realities of the factory floor.

8 examples of how digital twins are used in manufacturing

Digital twins are helping the manufacturing industry work faster and smarter. Digital twins can also help optimize factory floor configurations, decrease downtime, and give you a deeper understanding of the physical assets that you manage. Here are the top 8 examples of digital twin usage in manufacturing:

• Immersive, low-risk training for manufacturing employees

• Dimensionally accurate space planning and layout validation

• Predictive maintenance planning grounded in physical context

• Quality control and process documentation tied to real equipment

• Compliance reviews and audit preparation without site disruption

• Energy use modeling and sustainability planning

• Real-time operational insights when connected to live data sources

• Remote site visits, inspections, and collaboration without travel

1. New hire training

• Challenge: Training new operators is a significant investment. Classroom instruction often lacks physical context, while on-site training can be limited by noise, safety requirements, and active operations that make learning harder.

• Solution: Digital twins give new hires a safe, accessible way to learn before stepping onto the factory floor. Teams can annotate equipment with training notes and best practices, and link SOPs, checklists, manuals, photos, and videos directly to the locations where work is performed. Local Union 669 uses Matterport for this because, according to Jeffrey Van Rhyn Jr., Technology and Code Coordinator, “Matterport is a better alternative to giving apprentices more books to read and questions to answer” because “it gives them a real-live situation to navigate, so they will be confident and familiar on the job site.”

2. Space planning

• Challenge: As new machinery and workflow changes shift how space is used, planning updates with basic floor plans, schematics, or photos can lead to errors or miscommunication. Gaps in understanding often surface late, when changes are already underway.

• Solution: Digital twins provide a dimensionally accurate, photorealistic view of the facility that teams can use to plan changes with confidence. Matterport captures existing conditions and supports exports such as E57 point clouds, which can be brought into BIM and CAD tools like Revit or shared through Autodesk Construction Cloud (ACC). With an accurate model of the space, teams can review line changes or renovations before work begins, validate equipment placement, and plan work in a way that reduces downtime risk.

3. Predictive maintenance 

• Challenge: You never know when a machine is going to break down. An unexpected repair can slow production and lead to lost revenue, especially when teams struggle to find the right maintenance information quickly.

• Solution: Digital twins support predictive maintenance by linking asset repair details, manuals, and other critical documentation directly to equipment in the model. Matterport digital twins integrate with CMMS and EAM systems through APIs, bringing maintenance history, inspection data, and work orders into the same spatial view. When combined with data from IoT-connected devices, teams can review predictive alerts in context and plan repairs before failures occur.

4. Quality control

• Challenge: Maintaining consistent quality is difficult in complex production environments. When issues arise, teams must prove compliance with standards such as FDA, ISO, or GMP requirements, often with limited records of how equipment and layouts were set up at the time. Without a clear view of past conditions, root-cause investigations can be slow and uncertain.

• Solution: Digital twins create a time-stamped visual record of the production environment. Teams can review historical layouts, equipment placement, and surrounding context to understand what conditions existed when a quality issue occurred. This visual evidence supports faster root-cause analysis and more confident quality reviews.

5. Compliance

• Challenge: Audits take time and disrupt operations. Outdated drawings and incomplete documentation slow preparation, while on-site inspections add risk and travel overhead, especially across multiple facilities.

• Solution: Digital twins support virtual audits and pre-inspections using time-stamped visual records of layouts and safety controls. Teams can add notes and tags directly in the model to capture audit evidence in a consistent way. This creates a shared compliance hub that reduces disruption and limits travel.

6. Energy use modeling

• Challenge: Manufacturers face growing pressure to reduce energy use and emissions without impacting throughput. In complex facilities, waste often hides in utility systems that are difficult to visualize or document clearly.

• Solution: Digital twins make energy use easier to understand by mapping audit findings and energy data directly onto a 3D model of the facility. Teams can visually identify problem areas and plan upgrades or retrofits using accurate as-built conditions. This helps reduce waste while minimizing disruption to ongoing operations.

7. Real-time operational insights

• Challenge: Traditional dashboards show data without physical context. When performance issues are driven by layout or proximity, teams often need to be on-site to understand what’s actually happening, which slows response time.

• Solution: Digital twins let teams view IoT and machine data directly within a spatially accurate 3D model of the facility. Seeing data in place makes it easier to diagnose problems remotely and coordinate decisions across sites without waiting for in-person walkthroughs.

8. Remote site visits

• Challenge: Many manufacturers operate across multiple sites, which makes knowledge sharing and alignment difficult. In-person visits take time to schedule and often limit who can safely access the facility. At the same time, sensitive environments can’t be opened up freely without creating risk.

• Solution: Digital twins enable remote site visits that give internal teams, partners, and approved guests a clear view of the factory without travel. Stakeholders can walk the space virtually, understand layouts, and review conditions using a browser or mobile device. Access controls and permissions ensure only authorized viewers can see specific areas or information, protecting sensitive facility data while still enabling collaboration.

Create digital twins to streamline manufacturing processes with Matterport

Teams across the manufacturing sector are turning to Matterport to help them create dimensionally accurate 3D digital twins. Here are a few ways Matterport is helping manufacturing companies transform outcomes:

• Seafood producer Nordlaks partnered with Matterport to capture existing conditions during a major factory expansion. Teams use the scans inside Autodesk Construction Cloud to coordinate with suppliers across borders. The model supports collision reviews before equipment arrives. It also supports virtual inspections when people can’t be on-site. Tømmerås estimates the tools save him hours and reduce travel pressure.

• GSN is a manufacturing automation provider that uses Matterport digital twins for training on complex CNC systems. Teams store process steps and quality controls inside the model. They also store manuals and instructions there. This shortens the learning curve and reduces training costs. It also reduces risk to people and equipment during training.

• Global industrial manufacturer Siemens uses Matterport to review assembly line setups without gathering on the production floor. Stakeholders can meet in the model and examine details without noise constraints. Siemens also uses the Matterport SDK to place real-time IoT data inside the digital twin. That spatial context makes it easier to interpret what sensors report.

• Danone, a food and beverage manufacturer, worked with Matterport to reduce visits to production facilities with strict safety and quality protocols. Danone reports up to a 50% decrease in in-person site visits by company personnel. Teams use the model in meetings to review production lines and plan work. Danone also uses Tags to support training and documentation.

Want to learn more? Discover how teams are already using Matterport to work smarter and faster. And take a tour through the exciting world of digital twins to understand how this immersive digital technology is powering smart manufacturing.