The chemical industry, like other manufacturing sectors, has dramatically benefited from the enormous strides being made in electronics. Many of the gains have come from allowing companies to react faster and better to changing conditions in their plants and marketplaces. Now, however, interest in smart plants, which place more emphasis on predicting rather than reacting, is growing.
Certainly, smart plant concepts such as predictive maintenance and predictive control are not new to the chemical industry. However, as Lou Cabano, president of Pathfinder LLC, an engineering firm in Cherry Hill, N.J., notes, “Smart plants have been more hoopla than tangible results so far.” But that is changing, he adds.
Tom Buckley, vice president of Aspen Technology Inc., based in Seattle, certainly agrees. “A number of leading chemical companies want to go beyond achieving better, timely response to achieving better, timely prediction.”
Significant progress in enabling technologies makes such a transition more feasible, both technically and economically. Continuing increases in microprocessor power and speed, and data storage density allow powerful capabilities to be built right into field devices. In addition, these developments have enabled analytical techniques like near infrared to move from the laboratory to the field. Meanwhile, the increasing availability of wireless devices makes getting data from remote or inaccessible locations more feasible. At the same time, fieldbus developments are enhancing communication by enabling much more information to be handled and facilitating interoperability among devices from different manufacturers.
Andrew Ogden-Swift, Southampton, England-based director of advanced development for Honeywell, speaks for many when he says there’s a lot more interest now in predictive maintenance. A May survey by Chromalox, a Pittsburgh-based vendor of heating systems, certainly underscores that. Only 5% of those surveyed now have temperature-control systems with diagnostic or preventive maintenance capabilities. However, 75% say they expect to have these capabilities in two years. (The survey also indicates that use of wireless devices will double in two years.) Doug White, vice president for Emerson Process Management, Houston, reckons that far less than half of all process plants now have any sort of predictive maintenance capabilities.
Actual implementations of predictive maintenance have led to significant gains, says White. Potential production from existing equipment typically increases 1-3% because of fewer unscheduled shutdowns, while unplanned maintenance costs decrease 10-30%. The return on investment can be among the highest of any possible plant expenditure, he adds.
Ron Durham, leader of maintenance services for NOVA Chemicals, Joffre, Alberta, says that the availability of new technology and the potential savings from improved reliability are the key drivers at his company. Predictive maintenance should figure in the plans of any company whose goal is to follow best practices, he adds.
Vendors certainly are responding to this increased interest.
In April, Emerson Process Management, Austin, Texas, extended its PlantWeb architecture by introducing what it calls a new class of smart instruments for monitoring machinery health. The initial offering, the CSI 9210, is designed specifically for AC-motor/centrifugal-pump trains. It uses vibration, motor flux, rpm, temperature inputs and embedded diagnostics to spot problems like pump cavitation and imbalance, motor electrical overloading, bearing failure and coupling misalignment. It is said to be the first such device to use the Foundation Fieldbus communications protocol.
“The CSI 9210 Machinery Health Transmitter can alert our operators in real time when equipment problems start to manifest,” says John Rezabek, controls specialist for BP Chemicals, Lima, Ohio.
Motor/pump trains were targeted first, notes Brian Humes, vice president and general manager for Emerson, because they are so common at plants and are responsible for so many problems. Emerson plans to introduce such monitoring devices for motor/centrifugal fan, motor/rotary blower, motor/gearbox/pump, motor/compressor and turbine/pump trains.
Another good candidate for predictive maintenance is the ubiquitous heat exchanger, says Kevin Fitzgerald, senior program director, new ventures, for Invensys Process Systems, Foxboro, Mass. “The key is to bring in not just vibration data, but operating information in a contextual fashion.” A model that uses such data along with temperature, pressure and flow rate can better monitor fouling.
Invensys introduced enhancements to its Avantis CM (condition monitoring) software in March, including rules-based data handling that can be used for predictive maintenance, says Fitzgerald.
Operating companies are asking for online, real-time sensing of heat-exchanger and furnace efficiencies, vibration and corrosion, and other asset-health indicators, notes Ogden-Smith. Developing new sensors for such duties might require innovative approaches to achieve easy installation and reduced costs, he says, adding that wireless technology certainly will play a role.
Expanded use of preventive maintenance doesn’t depend on new technology, though. Fitzgerald says that a lot of the opportunities will be in the basics, employing established technologies more effectively.
Getting more data isn’t enough, he cautions. Making sure that data are crosschecked and validated is an important issue. “This is not now adequately addressed or recognized in preventive maintenance. Vendors of sensors should be doing more to provide enhanced diagnostics and self-checking at the device level.” He adds, however, “Many times diagnostics require looking beyond the particular device at the broader context of multiple instruments and data reconciliation among them. Device-level diagnostics can help — and are the wave of the future — but are not the complete answer.”