The classic view of Abnormal Condition Management is to identify an abnormal condition and respond appropriately. Over the past decade, industry has become very good at identifying situations that are purely safety related, notes Peter Martin, vice president and general manager of Performance Management, in Foxboro, Mass., for the London-based Invensys.
The problem today, according to Martin, is that a huge number of abnormal conditions are not safety related, but can still greatly impact the bottom line. Some of the sources of business-driven abnormal situations include fluctuating energy costs, deregulation and changes in product demand.
Martin cites the relationship Invensys has with chemical manufacturer BASF as a good example of addressing non-safety related abnormal situations to improve overall profitability.
BASF has a large manufacturing site in Freeport, Texas, which includes 16 plants that make specialty chemicals used in coatings, solvents and polymers. Management at the site employed financial systems that were too slow to take advantage of real-time process changes and opportunities. As well, says Martin, “The information from the financial systems was not detailed enough to be actionable in supporting operational best practices.”
The company contracted with Invensys to evaluate one of its manufacturing lines and develop a real-time performance management system that met business and operational goals. As a first step, Invensys worked with BASF operations personnel to identify the site manufacturing strategy and the economic and non-economic algorithms for each process unit in the line that contributes to the overall strategy. Next, the algorithms were implemented in the control systems on a real-time basis to provide technicians with strategic data that matched the time constant of the process. If the time constant of the process was 10 seconds, for instance, data was served to the technician at that rate.
As part of the control system, technicians use a Performance Dashboard from Invensys that lays out the key performance metrics of the manufacturing strategy. Technicians were instructed to run the plant as usual, but when they had free time, to monitor the Dashboard and make changes that would drive feedback trends in the right direction. For example, technicians could adjust—within the engineering limits—inputs, such as process variable setpoints, and assess the impact on outputs, such as cost and profit trends. Once the process was out of alarm conditions, technicians could monitor the performance of the plant and respond to changes, such as fluctuating energy costs.
The first day the Dashboard was implemented, not much changed, because technicians were learning how their behaviors could impact the system based on real-time feedback. Soon technicians started managing the unit much more efficiently. BASF reports that the project contributed to significant cost reductions in a key manufacturing area. Now, the technicians are doing more than just running the unit, they’re managing the business according to the BASF financial strategy. They can identify events that occur, such as load changes of a steam line, and respond in ways that are most profitable to the plant. The Dashboard will be expanded to other units in a drive to turn abnormal situations into profit opportunities.