Representative End User Clients
Representative Automation Clients
Representative Software Clients
As industrial operators contend with rising energy costs, sustainability pressures, and increasing process complexity, process simulation and optimization (PSO) continues to play an important role in how performance improvements are identified and evaluated. This is particularly true for mature, energy-intensive industries such as pulp and paper.
In a recent discussion with analysts from ARC Advisory Group, Aurel Systems described how its dynamic simulation platform, CADSIM Plus, is being applied across a range of use cases. While historically used for engineering analysis, the platform is increasingly being extended into advanced online applications such as operator training simulators, online dynamic data reconciliation, and real-time optimization, the latter two of which are now used to implement and deploy process digital twins.
A Focus on Dynamic Simulation
Aurel Systems distributes and supports CADSIM Plus, a dynamic, first-principles process simulator with an established presence in the chemical and pulp and paper industries and growing adoption in areas such as food processing, mineral processing, and select oil and gas applications.
CADSIM Plus emphasizes the dynamic behavior of industrial processes as they evolve over time. This includes handling recycle streams, interacting process units, and the action of PID control loops under transient operating conditions, which are impossible to capture in static models. This level of dynamic fidelity becomes increasingly important as simulation models move beyond theoretical design questions toward supporting operational use cases, where understanding how a plant responds to change is often more valuable than identifying an idealized steady state.
Extending Models Beyond Offline Analysis
One area of ongoing development discussed during the briefing was dynamic data reconciliation, where a first-principles model is used to continuously correct live plant data. Rather than treating simulation models as static engineering artifacts, this approach allows them to evolve alongside everyday plant operations, handling process upsets and events such as startups and shutdowns.
Reconciled “actionable” process data can then serve as an input to a range of higher-level applications, including performance dashboards, advisory optimization tools, and energy or emissions analysis. In these cases, the simulator does not replace existing control systems but instead provides an additional analytical layer that can help contextualize operational data.
During the discussion, Aurel Systems emphasized a hybrid modeling approach, combining physics-based simulation with selective use of data-driven methods. Rather than positioning artificial intelligence as a standalone solution, AI is applied where relationships are difficult to describe explicitly, while first-principles models continue to represent known process behavior. This reflects a broader industry view that practical digital twins often rely on multiple modeling techniques rather than a single methodology.
Digital Twins in Operational Context
Some of Aurel Systems’ most advanced digital twin work to date has been deployed in pulp and paper facilities. This industry is characterized by aging assets, high energy intensity, and relatively tight operating margins.
In one example discussed, a full-process digital twin was used to track live operating conditions, evaluate optimal operating targets under varying production rates, and provide advisory recommendations to operators in an open-loop configuration. The project illustrated how continuous, incremental optimization can be applied in an operational environment, even when full automation is not immediately feasible.
Adoption Depends More on People Than Technology
A recurring theme throughout the conversation was that technical capability alone rarely determines the success of digital twin initiatives. Instead, adoption is often constrained by factors such as operator trust, clarity of recommendations, and the ability to integrate new tools into established workflows.
To address this, Aurel Systems typically emphasizes open-loop optimization in early deployments, allowing operators to evaluate and validate recommendations before any move toward closed-loop control. Over time, the system effectively becomes an expert system, shaped through consultation with experienced operators, process engineers, and domain specialists whose knowledge is embedded directly into the model’s behavior. This incremental approach reflects lessons learned across many PSO projects, where over-automation can undermine confidence and limit long-term use.
Positioning in a Vendor-Dense Market
In industries such as pulp and paper, optimization and digital twin capabilities are often bundled into broader automation or equipment offerings from large OEMs. While this can simplify procurement, it may also limit flexibility, particularly for sites with heterogeneous control environments.
As a smaller, specialized vendor, Aurel Systems tends to position its platform as complementary to existing automation systems rather than as a replacement. The company highlighted its emphasis on transparent, physics-based models and its ability to integrate with third-party control systems and partner ecosystems.
A Long-Established Company Adapting to a Changing Market
Founded in 1977, Aurel Systems is a long-standing provider of engineering software and services for the chemical engineering community. For more than 40 years, the company has developed tools used by engineers to model, analyze, and improve chemical processes, most notably through its CADSIM Plus process simulation software. In addition to software and training, Aurel supports clients with engineering services such as dynamic process modeling, data reconciliation, and the development of online optimization applications, often working alongside in-house or consulting engineering teams.
As PSO and digital twins transition from isolated projects to operational infrastructure, vendors that combine rigorous physical modeling with practical deployment experience and attention to human adoption factors are likely to remain relevant, particularly in industries where process nuance and operational variability are central concerns. From an ARC Advisory Group perspective, Aurel Systems illustrates how specialized PSO vendors continue to occupy an important niche within this evolving landscape.