Achieve Model Operations

Plants can solve a range of problems by leveraging design models

By Rob Hockley and Ron Beck

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Additional effort is necessary to make these automated models even more robust, read in additional real-time plant data and reconcile conflicting plant data (e.g., measured mass flows in and out of a unit that don’t balance).

The final level of modeling in operations employs real-time closed-loop models, with their results implemented in an automated way to optimize processes. These systems require additional effort to make the system fully robust and safe. However, they promise even greater benefits, particularly where processes need to respond to predictable variability (e.g., in feedstock characteristics).

Chemical companies already are realizing significant benefits in plant operations from each of these approaches [6]. The experience reported by INEOS is instructive. It used a modeling approach to optimize heat exchanger monitoring and cleaning in its vacuum distillation units, saving more than $3 million dollars per unit per year [7].

Future directions

 

The biggest challenges in integrated engineering are along two fronts:
  • for collaboration between engineering disciplines; and
  • for moving rigorous analytical models into the operating environment.

The effort required to build discipline-specific and plant-specific models coupled with the need to hide the complexity of these models from people performing specific roles have driven innovations in modeling tools. Here are some key developments:

Modularized systems. Process modeling systems can be redesigned for re-use in a modular fashion throughout an asset’s lifecycle. One example is the physical properties database. AspenTech now offers its as a re-usable resource, a “standardized component” for a number of different model-based applications. This ensures maximum flexibility and consistency regardless of choice of modeling tools.

Another example is the unit operations models. These can be modularized so they are usable by systems ranging from simulation, basic engineering, optimization, economic evaluation to advanced process control.

User console and simplicity. New concepts build the workflow right into the user interface — presenting the appropriate analytical models and tools to users depending upon their role, the phase of a project and their position in the workflow.

Models in engineering. This provides the capability to call models from downstream in the design process, including basic design, start-up and control (without looping back to the modeling group). Modeling can be performed in-plant without intervention by design engineering.

Common engineering data backbone. A lifecycle database incorporates unit operations models, process, equipment and instrumentation data and control information to facilitate lifecycle optimization.

Realize real benefits

Process engineering models created during conceptual design increasingly are being applied downstream in the design process and operations, thanks to developments that make these analytical models usable by other disciplines and plant staff. This is leading to measurable savings in dollars, energy, time and staffing.

Future work by software innovators will lead to the modularization of unit operations models and increased ease of use and integration of work processes. Rigorous models are destined to become even more widely used and more valuable tools in the operation and optimization of process facilities.

 

 


 

**Rob Hockley is a Warrington, U.K.,-based senior consultant for Aspen Technology, Inc. Ron Beck, is marketing manager for Aspen Technology in Burlington, Mass. E-mail them at rob.hockley@aspentech.com and ron.beck@aspentech.com.

References

  1. Mullick, S. and V. Dhole, “Consider integrated plant design and engineering,” p. 81, Hydrocarbon Proc. (Dec. 2007).
  2. Lofton, W. and L. Dansby, “Adding value by integrating process engineering concepts and cost estimating,” Presented at AspenWorld 2002 Conference (Oct. 2002).
  3. Wiesel, A. and A. Polt, “Paradigm shifts in conceptual process optimization,” AspenTech User Group Meeting, Frankfurt, Germany (Apr. 2007).
  4. Donkers, M., “Runaway reaction hazard assessment within Shell International Chemicals,” available online at www.safetynet.de.
  5. Cox, R. et al., “Can simulation technology enable a paradigm shift in process control? Modeling for the rest of us,” p. 1,542, Computers & Chem. Eng. (Sept. 12, 2006).
  6. Pres, R. and P. S. Peyrigain, “Minimizing VDU heat exchanger fouling through application of rigorous modeling,” presented at Aspen HTFS Annual User Group Meeting, Cologne, Germany (Dec. 2006).
  7. Griffith, J. et al., “Advances in front-end engineering workflow and integration,” p. 32, Hydrocarbon Eng. (Jan. 2008).
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