Robust Control
Stabilize Processes to Improve Yield Without Investments in Physical Plant or New Process Technologies.
Dividing process variability by its mean yields the red line, which plots for actual plant data a threefold reduction in variance in a refining process subsequent to the implementation of Robust Control.
Large industrial systems have many parameters to be controlled and many levers for control. Individual controllers acting independently and without knowledge of one another can render a system noisy or even unstable. Increasing emphasis on controlling process variation by industries as diverse as oil refining, pharmaceuticals, and food processing reflects a growing understanding that reducing variation, because it increases throughput, has the potential to reduce costs and increase profits in the absence of significant investments in new process technologies.
That inexplicable variations in key process parameters persist despite substantial capital investments in state-of-the-art control systems for well-established production systems is a consequence of failing to take into account all of the sources of variation in a process and the interactions among them. The physical characteristics of a process, the control paradigm employed to regulate it, and the people who execute and monitor it are all sources of variation.
Robust process control is transforming us into a learning organization. Every process problem is now viewed as an opportunity for learning and process improvement. We do not just gather data; we convert these data to valuable information for process analysis.
The Robust Control methodology focuses attention and problem-solving resources exclusively on process disruptions. It is a staged approach that involves:
- simplifying a process,
- identifying and stabilizing the bottleneck,
- synchronizing the other stages with the bottleneck,
- and standardizing procedures to ensure that the gains that are realized are maintained.
In a glucose factory plagued by highly variable output—standard deviation was on the order of 22%—operators routinely monitored 2,000 input points and continuously adjusted some 40 controls. The implementation of Robust Control reduced input points from 2,000 to 40 and controls from 40 to 5. Variation was reduced by 75% and throughput increased by 15%. When the methodology was implemented at five other plants productivity gains on the order of 10%–50% were realized across the six refineries.
- The aggregate capacity increase was valued at $300 million, equivalent to the cost of erecting a new refinery with a capacity of 1,000 tons per day.
- Additional savings in supplies and utilities were on the order of $3.5 million per year and finished goods inventory was reduced by more than 30%.
- Customers rewarded corresponding improvements in customer service with larger contracts over extended periods.
Moreover, because existing processes can be run at higher capacity and with better precision under Robust Control, the company elected, in lieu of developing new, more expensive processes, to buy other companies′ plants and run their processes more efficiently.
Robust Control has transformed our operators from fire fighters to process innovators.
A refiner of non-ferrous metals that implemented Robust Control achieved reductions of nearly 80% in the incidence of unknown disruptions and more than 70% in total disruptions over the course of a five-week experiment. Benchmarks made subsequent to expanding the implementation revealed reductions in disruptions in every critical process parameter. Aggregate gains from the implementation of Robust Control included:
- a threefold reduction in process variability and concomitant improvement in the quality of output,
- a 25% capacity increase,
- and attendant savings in operations and maintenance.
The company not only maintained these gains, but deployed the same techniques in a host of other refining processes with equally dramatic results.
Reducing variation in key process parameters has relevance in a diverse range of continuous process-based industries due to the potential to increase profits and reduce costs with little or no investment in new physical plant or process technologies.