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Digital Twins For Production System Design

The current process for designing an entire production system is a difficult and daunting task which needs to be coordinated between multiple groups. This complex task often involves some combination of loosely connected processes such as a gigantic excel spreadsheet or database calculations, a Monte Carlo and/or discrete event simulations and other diagramming and process mapping tools. All of this is loosely held together with a simple project management schedule for design, build, integrate, and test but this is insufficient because it is lacking any representation of the production environment and constraints. It often results in an isolated and disconnected process design because the full system view is never understood let alone analyzed. Instead the analysis ends at the shop or equipment level and begins to become overwhelming at the higher levels due the scaling level of complexity.


Missing the full depth of analysis greatly increases risk and uncertainty across all aspects of the program. It impacts the entire process and associated stakeholders even before production starts which often has a ripple effect through the entire lifespan. Due to the complexity, it is difficult to have accurate and timely results for economic profit modeling from production delivery (sales), capital investments in new or refurbished facilities, product engineering changes for producibility enhancements, cash flow modeling, workforce forecasting and more. This carries over into the beginning of production, when it actually starts, where the first few units are far more costly than estimated. Ultimately, it negatively impacts the time to profitability, customer satisfaction and business viability.

On a more granular level this also impacts the productivity and morale of the manufacturing workforce and leaders. They are now saddled with significantly higher levels of VUCA: volatility, uncertainty, complexity and ambiguity, in their jobs. This directly impacts safety, quality, morale, and ordinary business outcomes like throughput and on-time, in full delivery. Leaders are left with FAR more noise in the system than signal and, using today's common "rear view mirror" metrics can't see up from down, important from not important, priority issues vs. others, and so they’re stuck in circular quagmire that’s incredibly difficult to get out of.


There are some solutions that can take the burden of VUCA out of production system design and startup.

Leveraging Digital Twins with graph based solutions can provide visual aides and analysis of complex systems and processes. This highlights bottlenecks, deficiencies and ultimately risk. When it is iteratively and concurrently developed with Product Engineering definition it allows teams to collaborate and achieve true cross functionality. Using it early in program life cycles and, in conjunction with numerous Industrial and Systems Engineering practices increases feasibility, viability, risk avoidance and strategic options for the production systems. A few we commonly encounter are, Little's Law, Theory of Constraints and Critical Chain Simulation Modeling, Network Analytics, Statistical Process Control, and Lean Six Sigma.

A digital twin is a virtual representation of a physical asset, process or system that can be used to simulate and analyze its behavior in a digital environment. In the context of production engineering, digital twin modeling refers to the use of digital twin technology to create virtual models of production systems, equipment, and processes. This can include creating digital replicas of individual components, as well as entire production lines or factories.

From a financial perspective, which is something we all should care about, this will help with inventory forecasting, factory layout and optimization (use and occupancy), capital investments in new or refurbished facilities, cash flow optimization, return on working capital and more.

Collinear Group has the right mix of total product lifecycle domain expertise including deep manufacturing expertise in all types of environments integrated seamlessly with digital enablement and transformation solutions. We have a trusted ecosystem of technology and solutions providers that, when aligned to customer requirements, can result in powerful, long lasting solutions.

For more information please contact


David Prestin is a Collinear Group senior consultant and for over 20 years has served in industrial and systems engineering leadership positions at aerospace OEMs. David helps aerospace OEM and Tier 1 companies leverage today’s cutting-edge network analytics and technology to streamline complexity out of design, supply chain and manufacturing processes to cut costs and utilize a dynamic workforce more efficiently.


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