Simulation modeling, if used properly,
can help manufacturers identify and eliminate risks,
ensure proper production operations,
maximize enterprise value and contribute to success. maximize business value and contribute to success.
Mimicry can be a powerful tool for the entire project, allowing the project team to visualize many aspects of the production line during the design phase.
There are many questions that must be answered in order to plan a new production line or retrofit an existing one, including:
Technology designed to visualize a production line and bring it to life before it is developed is now more accessible than ever. 3D PDFs or videos can be viewed electronically, and many software programs can already integrate directly with virtual reality (VR) headset eyes, allowing the staff involved to access precise, interactive production line layouts.
This visualization helps everyone understand design parameters more effectively and reach **** knowledge on the final design. Smartphone apps and headsets using augmented reality (AR) technology, for example, can project 3D models into an existing space to provide an alternative view of the production line. Static or dynamic modeling can show interferences and obstacles and help avoid them in the initial stages of a project.
During the design phase, visualization can also be utilized in another way: to highlight the dynamics of the product's movement under different constraints. Simulation enables the user to set the operating parameters of the line - machine and conveyor speeds, conveyor length, equipment position, control behavior - and see how the system performs under different parameters. Animated simulation often reveals potential design issues with the line that are often difficult or impossible to detect when looking at line layouts or spreadsheets.
The importance of simulation can be seen in a recent example of an application that needed to fill 4 cartons at a time and then push all 4 cartons out of the machine at the same time. While the average machine speed was 100 cartons per minute, the actual instantaneous output of the machine was 0 or 200 cartons per minute. When the machine is unloading, if the conveyor is not running at twice the average speed, the cartons will re-enter the machine as they exit, preventing the machine from loading new empty cartons.
On the surface, the speed appears to be correct, but in reality, the machine may be found to be blocked. With a simulation model, the problem can be recognized at the design stage, so it can be corrected before installation.
Physical modeling is a valuable tool if you want to understand how a product interacts in real time on a production line. Designers can see the pattern of product displacement on the conveyor and adjust the conveyor design accordingly to maintain control of the product.
Previously, this could be accomplished with educated guesses and computer-aided design (CAD) layouts. However, in some special applications, such as the dynamics of dough rolling on a conveyor belt are difficult to predict or accurately visualize. Physical modeling is very demanding on computer hardware. Target models can be created. Lessons learned from smaller models can be applied to larger models.
Even with well-designed production lines, machine downtime is inevitable. The impact of undefined downtime is difficult to predict. Manufacturers may be hesitant to establish buffers, believing they will hide problems or encourage disengaged operators. Depending on the machine design, some buffers have a minimal impact on performance and can result in unnecessary capital expenditures. Simulation can model scenarios and consider normal operating conditions to determine the optimal number, location, and capacity of buffers to improve line performance and avoid unnecessary costs.
Another important area where simulation can help is in controlling the production line. Early in the design process, before the programmable logic controllers (PLCs) are in place, simulation models allow the design team to consider how they will be controlled. This allows the placement of photoelectric and other sensors to be tested and optimized before the equipment is purchased.
Perhaps the most critical time to use simulation is when the PLC program is ready for testing. Some modeling software can be connected to the PLC, and the model sends signals to the PLC from the simulated sensors and responds to PLC signals to its simulated motors. Instead of manually tracing code or trying to visualize performance using a human-machine interface (HMI), the control engineer can use a realistic, responsive system to debug the control. The sensor arrangement can be precisely fine-tuned in the model.
HMI programs can use the model to test with the PLC, and because the model is controlled by the PLC, pressing a button in the HMI simulates a real-time production scenario. Therefore, using the simulation model can greatly reduce the startup time for production line commissioning.
The process of connecting the simulation model to the PLC also facilitates training. New PLC or HMI programmers can identify errors, test new ideas, and build confidence in a low-risk environment prior to live production. Line operators can learn how to run the line and learn the new PLC program before installation.
Simulation also provides other indirect benefits. Gaining background knowledge of the dynamics of the production line allows the modeling programmer to ask questions early in the design process that would normally have been addressed later in development. Meeting schedule requirements is another benefit of simulation. Often, the production line has already been designed and installed, but due to various constraints, it can only be started and commissioned before the PLC program is complete.
If the model is tested before it goes to the factory, it helps validate the program faster. However, simulation has its limitations. The model output is only good enough if the inputs or assumptions are good enough. Simulation can't predict factors such as poor operator habits, bad materials, or condensate buildup. It is important to revisit and adjust the model to ensure it reflects accurate application conditions and behavior.
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