What is the industrial process simulation and how does it work?

Now that we know what a discrete event is and how it works in the systems they compose, we can move on to the following question: How does process simulation work?

Like any system that helps to establish a hypothesis to verify events, it needs a theoretical principle. For better understanding, we present a small glossary.

• System: elements that work in coordination with the same purpose.
• State variables: set necessary to define a system at certain times, depending on the event’s temporal evolution. Two types emerge from this, the discrete ones mentioned before and the continuous ones.
• Simulation models: systems’ representation thorough logical and qualitative relationships between each component. Next, you will find the types of simulations or models.
• Static: systems in a particular state of time that do not move.
• Dynamic: contrary to the previous one, it is a system that evolves in time.
• Deterministic: A model that does not contain random variables. They are facts and almost certainties about an event that will occur to know the result.
• Stochastics: events determined by at least one variable that is not random. They are also an application to processes, algorithms, and models with analyzable magnitudes or events’ concatenation.
• Continuous: they are variables that change continuously over time.
• Discrete: To better explain them, we need to know that they are state variables that change at determined instants of time and not continuously. Depending on how you want to review it, most of the process in an organization or production can be described as a series of separate and discrete events that occur at certain times and can affect the entire system.

Knowing this terminology, we can explain the theoretical foundation of industrial simulation processes.

In theory, when we apply simulation software, it will be possible to determine the process behavior based on analyzing the variables involved. The advantage that this represents is related to cost savings. In other words, by resorting to a simulation, a company can avoid experimenting with larger-scale impacts, which may be more challenging to solve.

A simulation makes it possible to detect dangerous factors for production and minimize them to make decisions, and improve planning, and operation, as well.

An example of a process simulation can be a cosmetics company that receives a box of special red colorants for a new makeup line. Start the project; we can observe actions such as the color application of color, the manufacture of cosmetics, packaging, and shipping.

The colorants will be in a simulation model, the entity, and shades of red, number of colors, quantity, and quality will be the attributes. All these elements are part of the resources that will determine the variables examined in the system, but more can be considered depending on the objective of the analysis.

Advantages and disadvantages of simulation

As an industrial production tool, every complex system analysis method can have pros and cons; knowing them may help to understand a project better.

One of the main advantages is reliability when deciding on the process that will impact the system.

We understand these changes can be reflected in time, quality, machinery, product quality, labor, maintenance, etc. For example, when simulating to demonstrate that integrating biodegradable plastic in bottle manufacture of bottles can have benefits in quality, production time, consume preference, among other impacts.

Secondly, the improvement can be considered as another simulation’s benefit. With a 3D model, the status of a complete production line can be reviewed, visualizing defects, areas for improvement, and phases of the system.

Simulation development allows maintaining an operation in its best state, since it helps to find needs or opportunities such as the distribution of workloads, identification of bottlenecks and finally, carrying out planning supported by predictive models.

It is important to mention that there are disadvantages, such as some simulation models that may represent a higher economic cost and, in the time spent. In each modeling project, resources are used that, if they don’t bear fruit, mean expenses instead of investments, to name it in some way.

Speaking of time, when used without a clear objective or measurement tools, the data required for simulation may not be obtained, creating a model that doesn't represent reality.

It is advisable to consider both positive and negative aspects before carrying out the simulation. In this way, it is possible to know the impacts that a change in the system will generate. At Autmix Process we have advanced technology and specialized industrial software tools to provide simulations that improve your industrial systems. Contact us.

Industrial simulation applications

The simulation of industrial processes can be applied in different fields or production phases, in the design or development of products, and in the machinery’s check-up. Let’s see some examples.

• Optimization of machines in operation: the simulation can help to improve the equipment's performance, guaranteeing maximum efficiency and compliance with the expected result.

• Industrial complex systems audit: by performing the components' simulation, creating a daily environment that contemplates discrete events and identifies variables such as load, equipment failures, or changes during operation. In this way, more efficient, safer and less risky industrial complexes are created.

• Reliability and productivity analysis: identification of possible risky points, evaluating the impact of changes or decisions made in production, which are complex to evaluate in real life. One of the methods used in the simulations is the RAM Analysis (Reliability, Availability, and Maintainability) a proactive study to diagnose the performance of a process in a specific period.

• Production capacity optimization: simulations are an advanced tool for evaluating the performance of a system and identifying anomalies that affect productivity and efficiency.

• Improve logistics: complete check of the supply chain, from suppliers to inventories in stock.

• Health and safety monitoring: a simulation model determines the production's health and safety conditions in production, finding improvement areas.

Industrial process simulation phases

A simulation of industrial processes involves phases that will mark the progress and help to determine its success. It is a methodology for obtaining the necessary knowledge to make qualitative and quantitative arguments and then, evaluate design options. The following are the steps.

1. Problem approach: in the initial stage, a specialist in process analyzes the situation, contemplating the information provided previously. Currently, the objectives, expected results, test plan, time, variables, events, and statics are presented by the client.

2. Conceptual model design: a conceptual model will show elements of characteristics involved in the process and the constant repetition of events. It is carried out considering the objectives, logical, and mathematical relationships as necessary.

3. Data collection: recognition and examination of data for its introduction to the model.

4. Verification and validation: it is the model accreditation, and it’s about checking that the simulation is ok between reality and the virtual environment created.

5. Results analysis: detection of issues and thus, provide recommendations based on the opportunities found.

6. Documentation: the compilation of the simulation project carried out, with graphics and clear information, making it easy to show every step in the process. Applications and software can help with a good user interface, to have a comfortable interaction between devices and operators to generate status logs.

7. Implementation: put into practice the decisions made, thanks to the simulation. In this last phase, it's recommendable to receive accompaniment from the provider or process specialist to obtain advisory and consultancy.

Industrial Process Simulation Software Features

Simulation processes are sets of equations to represent systems in a domain of interest. Therefore, integrating digital technologies such as software and application facilitate detections and subsequent improvement of each process, depending on the objective. There are simulations that are applied to different types of projects, industries or sectors, some functions are described in the next list:

• Product simulation and testing: it helps manufacturers verify and validate the intended use of a product and the manufacturing capacity of a production plant.
• Process integration: a solution to connect workflows across engineering domains by applying automation and process management tools.
• Industrial space design: with the use of programs such as CAD and CAE, a design or workflow model is made to optimize the requirements established in the projects.
• SPDM: also known as Simulation of Processes and Data Management, as the name indicates, is a tool to manage different processes in virtual or real environments, this is an option that achieves traceability across all performance domains, leveraging connected simulation.
• 3D modeling: it is one of the most recurring methodologies in the subject of process simulation because it visualizes bottlenecks and other problems to be visually identified. In some cases, it allows us to obtain a statical analysis of the production and the behavior of the workflows.
• Virtual Reality and Augmented Reality: these tools are not “software”, but they are powerful and hyper-useful for seeing the interaction between computers and real environments. For proper operation, support is required as another instrument that communicates the user with the gadget. Some software that many experts recommend for developing these tools is Vuforia and Unity.

In the industry, the application of simulation programs or tools is mainly related to 4 tasks that are prototyping, maintenance and repair, video transmission and live data visualization.

It is important to mention that defining the industrial process simulation, model design, and the methodology that will be applied definitively will have a strong influence on the real company system. Contact an Autmix Process specialist and find the right option for a process simulation with positive results that promote the improvement of your industrial systems.