WellsTechDigital Simulation

The advantages of digital simulation

01
Cost savings

Reduce the cost of creating physical prototypes or conducting experiments. For example, you can reduce manufacturing and development costs by virtually simulating to test performance and reliability before making a major investment, such as building a new plant, expanding an existing facility, or mass-producing a new product.
02
Reduce time

Reduce the time required for physical experiments or tests. You can quickly test different scenarios and analyze the results with event-driven progression in a virtual environment.
03
Design refinement

In the early stages of a product or process, virtual simulation can help you compare different design options and find the optimal design.
04
Provide a safe test environment

Test systems in hazardous conditions or environments and evaluate the safety, especially for worker mobility and work environments that are difficult to review from blueprints alone. This is important in many industries, including automotive, batteries, shipbuilding, semiconductors, and more.
05
Data collection and analysis

Digital simulation can assist in collecting and analyzing data that is difficult to obtain in the real world. For example, you can simulate the behavior of sensor data in different scenarios to see how it responds.

Deployment process

01Define goals and scope
- 1. Clearly define the goals and scope of the simulation to determine which parts of the processes or system will be covered
02Data collection and analysis
- 1. Collect and analyze the necessary data from the production site.
  2. Initial data includes basic information such as production volumes, cycles, resource usage, etc
03Modeling
- 1. Develop a simulation model to reflect the key elements and interactions of the production process
  2. Model processes, equipment, personnel, etc. by converting them into a library and ensuring reusability
04Simulation Develoment and Validation
- 1. Develop a real-world simulation based on the model
  2. Initially start with simple models and validate as the complexity of the system increases
05Parameter adjustment and optimization
- 1. Optimize the parameters of the model to better match the actual production environment.
  2. Optimization aims to improve production, minimize resource use, etc.
06Simulation running and result analysis
- 1. Run the developed simulation and analyze the results
  2. Evaluate different scenarios that may occur in the production process through simulation
07Decision-making and improvement planning
- 1. Make decisions based on the simulation results and develop a plan to improve the production process
  2. Improvement plans aim to improve productivity, increase resource efficiency, etc.
08Real-world application and monitoring
- 1. Apply the improvement plan to the actual production environment and monitor the changes to ensure they match the simulation results
  2. Periodically update the simulation and make improvements as needed