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Dynamic Core with Mimic Maximizes ROI for Processing Plant
By Pierce Wu
Product: Mimic Simulation

This case study shows the return on investment (ROI) for a control system modernization project that used Dynamic Core with Mimic for dynamic simulation. The results of this case study were used to justify continued use of dynamic simulation for future process improvement and control system modernization projects.

Project Overview

A processing plant in the Food & Beverage industry planned a control system modernization from a legacy distributed control system to Emerson's DeltaV. Process areas within the plant, affection in the control system upgrade, included Reactors, Chemical additions and Storage. The decision was made to use a dynamic simulator for control system testing and operator training. The IO modeling of the simulation scope was approximately 1000 points. Dynamic Core with Mimic was used for the dynamic simulation approach across all process areas.

MYNAH Technologies was contracted to support the building of the model, the control system configuration, and plant operations team. The assignment of responsibility of the dynamic simulation on the project is shown in the table below.

Model Building Internal Testing Factory Acceptance Testing
MYNAH Simulation Team X X X
Control System Configuration Team X X
Plant Operations Team X

Project Challenges

  1. Configuring the control system properly and correctly throughout the project. In past projects, the plant operations team had to budget extra time and effort for fixing control system configuration issues that were not addressed in the control configuration FAT.
  2. Making sure operators are trained and comfortable with the process control operation. In the past, this customer experienced production delays due to operators that were not thoroughly trained on the control system or the process.

Dynamic Core with Mimic Solution

  1. By applying the appropriate level and fidelity of dynamic simulation, Dynamic Core with Mimic, the control system configuration was tested and checked out throughout the different stages of the project, including internal control system configuration testing and FAT. This saved the time spent fixing the control system configuration post FAT on previous projects.
  2. With the same dynamic simulation, operators were able to become familiar with the control system during and after the FAT, eliminating production delays due to operator training during process commissioning.
  3. Dynamic simulation allowed both of these project teams to accomplish their goals ahead of schedule.

Results

Time Saved:

3 weeks in commissioning | 1 week for control engineer + 2 weeks for plant personnel
Time typically spent resolving control configuration issues after control configuration FAT when simulation is not used during configuration.

3 weeks in training operators | 1 week for control engineer + 2 weeks for plant personnel
Time typically spent allowing operators and plant personnel to become comfortable with the new system. Using simulation during control configuration eliminated the need for this training as plant personnel became very familiar with the system having been involved in operating/testing during control configuration FAT.

6 weeks in production time
Using simulation to test configuration and train operators, the plant was up and producing ahead of schedule.

Control System Configuration Team Perspective

According to the control system configuration team, using Dynamic Core with Mimic testing the control system and identifying problems was made much easier during the FAT. In the past, the team had used low fidelity simulation inside of the control configuration, and it proved less effective in testing the configuration. The configuration team, as well as plant personnel, felt much more confident and comfortable with the configuration after testing with Mimic.

For this specific project, there were 16 weeks budgeted for the FAT, and only 12 weeks were used, saving 3 weeks from the project schedule. The FAT time was reduced 20%, saving the time of both the plant personnel and control system configuration team. In addition, the project was ready for production 3 weeks earlier.

Return on Investment

For this project, the cost of the simulation investment was $250 per I/O point. This cost includes the control system simulator license, Mimic license, model development and testing support services, configuration or setup services, virtual server hardware and software licenses, as shown below.

The quantified return on investment associated with the use of of the dynamic simulation was $2,100 per I/O point. These "hard dollar" savings were attributed to reduced time to production and manpower savings as shown below. "Soft dollar" savings of better trained operators, reduced risk in the control system configuration, and operating procedure verification are not included in these cost savings.

  • The Control System Configuration Team saved resources that would have been spent on a longer FAT.
  • Plant Resources saved time that would have been spent resolving issues in the control system and training operators after the FAT was completed.
  • The plant was able to begin production 6 weeks ahead of schedule increasing the return on investment of the control system modernization project.

Other Benefits of the use of Dynamic Simulation

Other "soft dollar" benefits of using Dynamic Core with Mimic were experienced during the project that are not included in the return on investment savings above.

Simulation provided more efficient problem solving during control system testing. In one example, the control configuration team reported an issue that a process value didn’t follow the set point for a particular module. Using the dynamic simulation, it was determined that the control module was not configured properly and the issue was quickly resolved.

Simulation helped the control system configuration team identify equipment module issues and enhance their understanding of the process. For example, during some equipment module control, a series of valves will open and the tank is expected to increase the level with the material flowing in the tank. However, in several cases, the level was not increased and the team helped identified that the equipment modules were not configured correctly to open the related valve to let the flow fill the tank. The issue was identified and resolved afterwards.

Ongoing operator training and control system testing is supported with the simulation system without disrupting plant production.


Conclusion

In this particular case, the savings and return on investment were immediate, the project executed smoothly and with confidence, and the installed simulation system is available for future operator training and control configuration testing.