(BIM)-Process-Simulation
From Digital Model to Real-World Success
Using simulation to investigate complex problems is one of the founding principles of our company. Simulation studies help optimize construction and execution strategies, design complex facilities, and increase the productivity of work processes.
Our experienced simulation modelers combine digital expertise with in-depth industry knowledge from construction and mining, helping you develop solutions that work in practice.
Process simulation is particularly well suited to projects using the BIM (Building Information Modeling) methodology, as it offers a wide range of benefits closely aligned with the core principles of BIM. In short, combining process simulation with BIM enables holistic, optimized, and collaborative planning and execution of construction projects, resulting in greater efficiency, higher quality, and lower risk.
Beyond BIM, process simulation can also be applied in sectors such as the energy industry to increase efficiency, minimize risks, and reduce costs.
What Is Process Simulation?
What Is Process Simulation?
Process simulation is a computer-based method for replicating and analyzing the flow and behavior of one or more processes in a virtual environment. It creates a digital twin of a project: an abstracted representation of reality, regardless of whether its real-world counterpart already exists or is still in the planning stage. Simulations of this kind are used in a wide range of fields, such as production, logistics, manufacturing, chemicals, and business process analysis. SD Engineering demonstrates that process simulation can also deliver real value in sectors such as construction and mining.
Process simulation is typically used to better plan and control the workflows and costs of a project. In this safe, cost-effective planning environment, the desired key performance indicators can be collected at any time to compare different options and make complex relationships easier to understand. For example, alternative production systems can be tested digitally without halting current operations for the experiment, which could otherwise lead to costly downtime.
Overall, process simulation helps to better understand complex processes within defined boundaries, make them more efficient, and minimize risks before they are implemented in the real world.
How Does Process Simulation Work?
Process simulation relies on an accurate representation of the processes being simulated. These processes are captured in the simulation software in the form of state diagrams.
A state chart is a graphical model that shows the various states of a system and the transitions between them. A state represents a specific configuration of the system at a given point in time. Transitions between states are shown as arrows and indicate how the system moves from one state to another. Each transition is triggered by an event or a condition, such as the expiration of a specified duration.
The logic of every actor in a process simulation is described using these state diagrams. The simulation model then executes the modeled process flows virtually, either autonomously or, if required, with manual input from a user. This can continue indefinitely or until a defined goal has been reached. In subsequent steps, additional constraints or key performance indicators can be added to the simulation.
Interactive Example
To illustrate how process simulation works, an interactive model of a sample process simulation is embedded below. The simulated processes are deliberately kept simple: one or more trucks shuttle between two locations and are loaded and unloaded at each one. Only one truck can be unloaded at a time at each location.
Input values can be adjusted using controls such as sliders, buttons, and text fields. These let you set the number of trucks as well as the loading and unloading times at the storage sites. The model time can be adjusted using the control bar at the bottom. To reset the simulation and enter new input values, press the “Stop” button at the bottom of the simulation.
Advantages
Because a simulation is a (simplified) representation of reality, it allows many things to be done faster and at lower cost than implementing the scenario under investigation in the real world. When comparing different options, there is no need to build expensive prototypes for each case; instead, the model is simply adjusted for each test.
Of course, processes and objects that do not yet exist in reality can also be modeled. In this case, the simulation represents what reality is intended to look like for the planned processes. Even simple animations of the simulation foster a better understanding of, and greater confidence in, the planned project.
At the same time, because a simulation is built from processes that are modeled as precisely as possible and depend on one another, it delivers more accurate results than calculations based purely on average values. For example, bottlenecks can be identified this way, allowing planning inaccuracies to be detected and eliminated at an early stage.
Furthermore, simulation models make it possible to run a wide range of parameter studies, which is especially valuable when input values are uncertain. Where needed, parameters can be randomized and analyzed in a targeted way. A common example is the failure probability of resources. This makes it possible to answer questions about how such factors affect the overall system represented in the simulation.
Challenges
A process simulation is only ever as good and accurate as the input data it is based on. If an incorrect input value is entered, there is a high probability that the simulation results will no longer accurately reflect the scenario being simulated. In addition, a simulation is theoretical by nature: it can only account for unplanned failures if they have been explicitly specified beforehand.
It should also be noted that a simulation always involves a certain degree of simplification in order to keep the processes manageable. As a rule, this simplification is tailored to the scenario being simulated so that its effect on the results is minimal. However, if the simulation results are to be used as an exact schedule for just-in-time production, for example, even these small deviations may have an impact.
Scope of Services
PROCESS MAPPING
Process analysis begins by documenting the current state and possible target states. These are then represented as processes in process maps (BPMN, EPC, etc.), which form the basis for developing one or more concepts for process-oriented information management.
REPORTING AND ANALYSIS
We provide the simulation results in dynamic, interactive dashboards. We can also prepare the results as a presentation or report, for example, and deliver video content ranging from simple 3D visualizations to high-quality renderings.
MODEL DEVELOPMENT
Based on the process analysis, a Java-based multimethod process model is developed. Depending on the project, this combines agent-based simulation, discrete-event simulation, and system dynamics.
USER TOOLS
We can also extend the simulation with a user-friendly interface that allows it to be controlled interactively. The simulation can then be provided either as a cloud-based solution or as a standalone application. We can also provide user training, user manuals, and ongoing support.
