From digital model to full Digital Twin: the future of simulation tools

Although the term "Digital Twin" currently seems to be a trending word and its meaning is sometimes muddled, it generally refers to a digital representation of a physical process or system including the associated technical data. In the food industry, this often refers to a digital representation of a plant, process or logistics movement. Despite the varying interpretations, attention to this term also has advantages. Because of the attention, the concept, as generally defined, is becoming increasingly important. The rise of Artificial Intelligence and the growing need to take a more sustainable and efficient approach to designing processes and production sites also contribute to this.

Engineering and project management

Digital tools for master planning, operations management, logistics and supply chain optimization are evolving rapidly. ONDRAF/NIRAS, an independent engineering firm based in the Netherlands with also offices in countries such as Denmark, the United Kingdom, Ireland, Poland, South Africa and Australia, is at the center of these developments. What sets ONDRAF/NIRAS apart is not only the ability to create simulation models, but also the expertise available to collect crucial data for this purpose, identify the level of detail and develop relevant scenarios. What makes the company truly unique is the ability to later convert these results into concrete steps such as engineering, project management, procurement and other follow-up steps, when realizing or optimizing processes and plants.

ONDRAF/NIRAS Netherlands has been active within the food industry for decades. Within the company, process and packaging engineering, including associated project management, are firmly established. In addition to these specialties, ONDRAF/NIRAS also offers services in the field of digital design, architecture and energy management. What characterizes the company is its in-depth (food) technological knowledge and attention to hygienic design and sustainability.

Degree of complexity of simulation models

Currently, what ONDRAF/NIRAS considers to be a Digital Twin is not yet fully used in practice. In fact, what is often referred to as a Digital Twin more often turns out to be a simulation model that can be classified rather as a Digital Model. Both, a Digital Twin and a Digital Model, are digital representations of physical processes or systems designed to enable understanding and modeling. The distinction between the two is in the level of complexity. A Digital Twin stands out as the more advanced of the two because it is connected to the real world and can exchange real-time data with the digital model and real life processes. A Digital Model is somewhat less advanced in that data exchange takes place through human input and analysis, rather than automatically. Nevertheless, a Digital Model offers just as much potential for visualization, review and analysis of scenarios, making it valuable for gaining insights that can be applied for real life forecasting and optimization.

Simulations, digital models, play a crucial role in assessing the impact of uncertain factors, improving KPIs, identifying problems and reducing unnecessary margins in engineering. The use of such simulation makes the design process cost-effective, less risky and easier to understand, which improves the accuracy of changes actually implemented.

Within a capacity project, ONDRAF/NIRAS used simulation software to evaluate various concepts of a new sorting line. "The simulations provided valuable insights into the performance of the designed system, allowing us to make adjustments to both the control philosophy, as well as the layout of the new line. This virtual approach proved crucial to identify and resolve potential challenges before physical implementation."

Both existing and new production plants and logistics systems can be simulated. Simulation models can be continuously supplemented with data, allowing ongoing optimizations, new planning and adjustments to be easily tested.

Sustainability

Simulations provide clarity when choosing different equipment by allowing them to test the effects of various parameters on a process or packaging line, as well as logistical movements. This allows us to observe how systems behave.The use of simulations results in shortened start-up times and reduces the need for extensive physical testing or costly adjustments once the plant is set up. 

The current area of focus within manufacturing processes is efficient use of energy. Simulation models offer the possibility to map and interrelate energy consumers. By taking various factors into account and by testing these parameters, it is possible to design the most energy-efficient process. This can yield significant savings in terms of emissions, but certainly also in terms of costs.

The future of simulation

Compared to conventional scenario assessment methods and calculations, simulations distinguish themselves by providing a thorough understanding of the situation. Currently, ONDRAF/NIRAS' simulations focus mainly on specific aspects of processes in the food and beverage, life sciences and logistics sectors. The possibility of actually moving to the Digital Twin principle where data exchange will be the addition is being explored. Especially in highly automated environments, ONDRAF/NIRAS benefits from the abundance of available data, where a simulation can verify whether a plant is fully exploiting its potential or still offering untapped opportunities. AI, automation and equipment connectivity are increasing the availability and quality of this data.

As part of a project to recover heat, the use of simulations produced significant results. The challenge lay in optimizing the use of heat and cold streams, paying attention to seasons and temperatures. A simulation allowed maximum efficiency to be achieved, surplus heat and cold streams to be used strategically, and critical process steps to be reviewed. These results included not only improvements in operational efficiency and cost savings, but also providing compelling evidence of the value of simulation in the early stages of complex projects.