Biggest Opportunities for Process Control Improvement – The Operator (Training Part 1)

Around 1984, there was a breakthrough in use of simulation for checkout and training. Software packages, such as MIMIC and its predecessor SIMVOX, automatically generated tieback simulations from the configuration and the input and output (I/O) cards and emulated the serial communication between the simulation and the DCS. These packages enabled the simulation to read all of the DCS outputs and send back all of the corresponding DCS inputs. Besides inherently providing a test of the I/O channel assignments, the simulation was separated from the DCS and expanded to cover the entire plant. The tieback simulation sent back the proper motor run contacts for the valve limit switch positions for discrete I/O that was particularly critical for batch operations. For control loops, the process variables was the PID controller output multiplied by a process gain and possibly delayed and filtered to simulate process dynamics. For indicators, fixed values were entered. A method was developed to switch these fixed values and to zero out loop process variables based on whether a flow path was established. A 1 or 0 status of each pump and valve in the piping path were multiplied together to determined the status. Ramps triggered by path status were added to simulate batch and startup responses. Batch operations could be run 100 times faster than real time, and be reset. Failures could be introduced. In Monsanto, these customized tieback simulations were credited with reducing the time to checkout and startup a DCS by 60% or more. By 1986 all Monsanto projects used the software package and its associated methodology and by 1994 nearly all of Monsanto’s 100 operating units were controlled by a DCS. The rapid deployment of the DCS had immediate benefits in terms of safer and more efficient operation plus provided a basis for a program of process control improvement over the next 6 years that lead to 4% further reduction in the cost of goods.

The tieback simulations with pathway logic and custom ramps achieved rapid education of the operators on how to effectively use displays and configuration. To develop better process understanding, the tieback simulations were in some cases enhanced by first principle process models. While the lack of a standard methodology resulted in custom process models of limited scope that were difficult to keep updated, the concept of a process model being connected to an actual DCS forever changed the landscape of process simulation. Up until this time process simulations for operator training used very expensive emulations of the control system at a cost of 200 thousand to 2 million dollars. Most nuclear power plants and some chemical plants and refineries went this route. However, it was not practical to include the detailed features of the control loops (e.g. structure, form, modes, and feedforward), sequences, batch executives, and the operator interface (e.g. displays and historian). Attempts to match and maintain were costly and prone to over simplification. The use of the actual DCS allowed the dynamic simulation to focus on the modeling of the process. The development of packages such as DeltaV Simulate Pro provided the ability to download the actual configuration and displays to a personal computer creating a virtual plant eliminating the need for the DCS console and controllers without any emulation or translation of the control system for training.

Plants are losing experienced operators and engineers so there is an even great potential benefit from periodic operator training. How can we provide training systems that wow decision makers when there may be no one left in the plant to support or even appreciate process simulations for operator training? I don’t have all the answers but here are some key aspects based on my experience:

(1) Live demos of virtual plants for key processes

(2) Online process metrics

(3) Expansion of audience beyond operations to process, control, and maintenance

(4) Modular and generic framework

(5) Ability to run slow processes much faster than real time

(6) Focus on process dynamics and interactions

(7) Readily increasing levels of fidelity for flexible cost and performance

For a perspective of the importance of the operator and some possibilities of online process metrics, check out the Dec 28 entry in the “Tuning and Control System Performance” Category. Next week we will look at some approaches to make the first principle process model more flexible in terms of cost and performance.