Optimize production line design using simulation modeling

Simulated modeling, when used correctly, can identify and eliminate risks, maximize value, and contribute to successful outcomes. Ask yourself these five questions to ensure the model reflects realistic behavior and constraints.

Simulation can be a powerful tool during a project and allows the project team to visualize many aspects of the production line during the design phase. To plan a new production line or modify an existing line, you need to answer many questions, including:

  1. What will this line produce?
  2. How fast will it work?
  3. What line efficiency can I expect?
  4. How does this device fit into my space?
  5. If conveyors are used, what are the restrictions? (What is the capacity of the conveyor? What will happen to the line during the shutdown and how long will it take for operation to resume? Where to place the balancing sections so that they are as efficient as possible? Will existing conveyors or unit operations be reused?)

Line visualization and pre-development technologies are more affordable than ever. PDFs or 3D videos can be viewed electronically, and many software now integrate directly with virtual reality (VR) headsets, allowing stakeholders to enter a precise interactive row layout.

This visualization helps everyone better understand the design parameters and reach consensus on the final design. Augmented reality (AR) apps and headsets can project the 3D model into the existing space to provide another view of the line. Static or dynamic modeling shows interferences and obstacles and avoids these problems at the beginning of the project.

Another way to use visualization in the design phase is to emphasize the dynamics of product movement under various constraints. Simulation allows the user to define many line operating parameters – machine and conveyor speeds, conveyor lengths, equipment locations, control behavior – and monitor system behavior within these various parameters. Animated simulations often reveal potential line design issues that are difficult or impossible to see when looking at a line layout or table.

Simulation and time

The importance of simulation can be illustrated by a recent example of a machine that filled four cartons at a time and then pushed all four cartons out of the machine at the same time. Although the average speed of the machine was 100 cartons per minute, the actual instantaneous output of the machine was 0 or 200 cartons per minute. If the conveyor at the exit of the machine did not rotate twice as fast as the average speed, the boxes would return to the machine on exiting and prevent the machine from filling new empty boxes.

The balancing section offered on the line shows the degree of accumulation. All images courtesy of Dennis Group

The speeds looked right on paper, but the machine was stuck. The simulation model identified this problem at the design stage so that it could be corrected before installation.

Physical modeling is a valuable tool when you want to understand real-time product interactions on a line. Designers can see how products will move on the conveyor and fine-tune the conveyor design to ensure product control. The simulation can show how products clump or jam in the hopper or on the storage table. An example simulation shows how a leveling section would be used for frozen dough balls.

Previously, this was done using an informed estimate or layout preview created using CAD. However, the dynamics of dough movement on a conveyor belt are difficult to predict or visualize accurately. Modeling based on physical properties is hardware intensive. It is possible to create targeted models. Experience gained on smaller models can be applied to larger models.

CTL1904 MAG2 F3 Simulation DennisGroup Fig4Simulation model and API tag interactions help identify and resolve issues earlier in the design process, saving time and money

The choice of equipment can reduce costs

Even with the best-designed line, machine downtime is inevitable. The impact of random variable downtime can be very difficult to predict. Manufacturers may be reluctant to create balancing sections and storage spaces, thinking they hide problems or reduce operator motivation. Some balancing sections have minimal effect on performance due to machine configuration, resulting in unnecessary capital expenditure. The simulation can model scenarios and consider normal operating conditions to determine the optimal number, location and capacity of balancing sections to increase line performance and avoid unnecessary expense.

Another important factor where simulation can help is how the line is controlled. At an early stage in the design process, when there is not yet a programmable logic controller (PLC), the model allows the design team to consider commands. The location of photocells and other sensors can be tested and optimized before purchasing the device.

Probably the most critical time to use simulation is when the PLC program is ready to be tested. Some modeling software can be connected to a PLC. The model sends signals to the PLC from the simulated sensors and responds to signals from the PLC sent to the simulated motors. Control engineers can debug controls using a realistic, responsive system instead of manually tracing code or trying to visualize behavior through the HMI. The location of the sensors can be adjusted in the model within centimeters of the optimal location in the real world.

Using the model, the HMI program can also be tested with the PLC, and since the model is controlled by the PLC, buttons pressed in the HMI will mimic real-time production scenarios. The use of a simulation model therefore considerably reduces the time required to commission the line.

The process of connecting the simulation model to the PLC is also beneficial for training. A new PLC or HMI programmer can identify bugs, test new ideas, and gain confidence in a low-risk environment before they are implemented in real production. Line operators can test line operation and the behavior of new API programs before installation.

Find out the problem earlier

CTL1904 MAG2 F3 Simulation DennisGroup Fig3Modeling frozen dough balls based on physical properties introduces key product characteristics into the model

Simulation has other indirect benefits. Based on knowledge of line dynamics, the modeling programmer can ask questions early in the design process that would normally be answered at a later stage of development. Another advantage is keeping to the schedule. Too often the line is designed and installed, but due to limitations, commissioning activities must be performed before the PLC program can be completed. If the model is tested before implementation at the operational level, this will contribute to a faster validation of the program.

Simulation has its limits. The output of the model is only as good as its inputs or assumptions. The simulation cannot predict poor operator habits, poor material quality, or condensation buildup. It is important to review the model and adjust it to reflect behavior and limitations.

Christy Starner is Director of Simulation and Modeling at Dennis Group. Edited by Chris Vavra, Editor of Control Engineering, This email address is protected from spam. You need JavaScript enabled to view it.

Leave a Comment