We help manufacturers deploy and maintain digital twins to model, monitor and optimize the operation of equipment, systems and processes.
The success of implementing new factory assets, systems and processes relies on accurate designs and on-time deployment. These designs are often built using assumptions, empirical calculation and historical experiences, which makes it difficult to account for variability.
Deployments are frequently delayed due to changes identified during commissioning on the shop floor. This dependence on trial-and-error to address unforeseen variability is inefficient, introduces project delays, increases risk and limits flexibility for future layout improvements.
Digital twins deliver measurable business outcomes
- Up to 15% OEE improvement
- Up to 75% faster commissioning
- Up to 40% reduction in reactive maintenance
- Over 90% first-time operation success improvement
Unlock the Value of Digital Twins for Your Business
We help manufacturers rapidly deploy digital twins to optimize equipment design, shorten commissioning time, increase production throughput, improve training efficacy and reduce equipment maintenance cost.
Using virtual environments and AI new deployments can be efficiently evaluated and improved during the planning stages, before a single line is commissioned.
How We Help Companies Deploy Digital Twins
We build digital twins of varying complexity to meet the requirements of industrial and material handling organizations.
A digital representation of a basic part or component within a system that is used to model the lifecycle of a single part or product.
A digital aggregation of multiple object twins, that is used to model the interaction between components/parts over the system’s lifecycle.
A digital representation of the sequence of process steps that models the interaction of ingredients and/or components that combine to create an output product.
A representation of multiple system/process twins operating in a business-defined environment, modeling the highest order of systems to provide a macro-view of the environment.
Our methodology focuses on delivering immediate value, while enabling companies to scale and sustain the capabilities across the organization.
To prove the business value, we apply a minimum viable product (MVP) approach to digital twin projects, addressing the highest-impact use cases first, before scaling the solution to additional opportunities.
- Assess the organization’s readiness
- Define clear strategy
- Identify high-impact use cases
- Gather modeling assets
- Build digital twin model with existing CAD
- Replicate real-world movements with control logic
- Analyze and optimize control logic via simulation/emulation
- Measure the results and make refinements
- Expand digital twin capability to more assets, systems and sites
- Transfer knowledge to resources that will own, operate and maintain models
- Increase adoption across all functions
- Measure and realize enterprise-wide value
Digital twins pair the virtual and physical worlds enabling informed decision-making through historical data analysis, real-time system monitoring, simulations and emulations.
Design Prototyping: Rapidly prototype engineering changes and validate with physically accurate simulation to identify and anticipate opportunities for design improvements.
Virtual Commissioning: Accelerate commissioning by developing and testing PLC code virtually.
Operations Research: Improve operations by optimizing scheduling, material routing, resource allocation and more via simulated optimization testing.
Production Execution/Optimization: Supervise and improve operations with remote monitoring, management, maintenance and assistance capabilities.
Immersive Experiences: Create compelling 3D experiences for operator training or sales to improve end-user product/system interaction.
Intelligent Model Training: Accelerate the training and deployment of AI into production systems with robust and physically accurate simulation.