The powerful combination of smart devices and communication networks has great potential for helping industrial plants achieve significant gains in productivity and efficiency. But making that happen requires companies to use the information from their production equipment to change their asset management and maintenance practices.
Take the example of two plants owned by the same company but located on opposite sides of the globe. The two sites made the same products, using identical production equipment, quality specifications and automation systems. They both spent a similar amount of time on maintenance. Yet one plant was experiencing constant failures, shutdowns and quality issues, while the other was performing to goals. Why?
Proactive vs. reactive maintenance
An analysis by ABB’s Process Automation Service found the answer. Kevin Starr, R&D manager, said their findings revealed the root cause of the disparity: the plant experiencing difficulties operated under a run-to-failure philosophy for maintenance, spending nearly 35 percent of maintenance time on unscheduled corrective procedures. In contrast, the plant meeting its goals spent only 8 percent of maintenance time on unscheduled activities. More revealing, 34 percent of its maintenance time was spent on preventive maintenance, and another 12 percent on optimizing assets. Employees at the proactive plant also received more than three times the amount of training as those working at the reactive plant.
Unfortunately, this lack of training is not uncommon at plants with a reactive approach to asset management, according to Starr. “The thinking is that once the system breaks, we know what to fix, so why train? This is a mistake and results in frustrated engineers who take longer to solve a problem and are unsure of the best practices to use to make sure the problem does not come back,” he says. “Proactive-minded clients, on the other hand, have seen the benefits of this service philosophy. They see training and certification as an investment to ensure not only that results don’t erode, but that production and quality performance continue to improve.”
Asset reliability as performance indicator
The methodologies for managing assets to ensure reliable performance first began to be developed by the airline and power industries and the U.S. military in the 1970s, according to Augie DiGiovanni, vice president of reliability key accounts for Emerson Process Management (www2.emersonprocess.com). “In the last 10-15 years, an understanding of the value of asset reliability as a plant performance issue has spread to all industries.”
Many universities began offering programs in reliability management, DiGiovanni says, and graduates are now entering leadership positions in operations and maintenance at many companies. “They’re realizing that their plants are not executing the reliability methodologies they learned in school,” he explains. “When they experience too many failure events and issues, they recognize that this can’t go on.”
DiGiovanni works to develop and drive reliability performance for selected Emerson strategic accounts. The companies are involved in the oil and gas, chemical, refining, pulp and paper, power, metals and mining, and food and beverage industries. “They’re telling us that reliability is one of their top three business objectives,” he says.
Rank assets for criticality
Any reliability program must begin by ranking assets for criticality in terms of the potential impact of their failure on plant production, DiGiovanni says. Strategies then need to be developed to ensure the optimal performance of these critical assets and extend their operating life.
Finally, decisions must be made about what technologies and what data to use to determine asset health. Some examples include when and how often to measure motor vibration or motor stops and starts, or whether to use wireless vibration sensors or wireless mesh networks. “There are lots of new ways to get data now,” he says, “especially in places where it’s difficult or dangerous for humans to reach.”
Understand how work gets done
Having the right people resources and assuring they have the right skills or adequate training is another important aspect of reliability management, DiGiovanni says. It’s also essential to understand how work gets done in a plant.
“It takes multiple people with different skills and properly documented work orders that provide them with an understanding of what went wrong and what tools are needed to fix a device,” he explains. “Often a process needs to be improved, streamlined and documented to improve asset reliability. You also need really good KPIs such as availability and return on asset value, and you must be able to communicate all your findings in a work management system.“
Smart devices that can diagnose their own health and provide in-depth process information are key to improving asset management. “In essence, you can now see inside a valve or transmitter to determine how well it’s functioning. In the past that technology did not exist,” DiGiovanni says. “Software lets you analyze performance and detect a problem long before it begins, so that an operator or maintenance technician can be alerted to take action. And we’re definitely seeing more network or wireless connectivity to this information.”
Even more important is the cultural shift that is happening as new people enter industry. “When people don’t know technology and aren’t comfortable with computers, then they fear change. No one wants to have a catastrophic failure by doing something differently,” he says. “But as younger engineers enter the field, you’re seeing the culture of plants changing, the adoption of new work processes to take advantage of new technologies, the increasing utilization of data and an appreciation of its value in improving plant performance.”
Keeping it all working
The combination of the speed of technology change, the growth of automated systems and the decline in the number of plant personnel with the experience and skill set to maintain those systems is causing problems for manufacturers in all industries, says ABB’s Starr. “Seventy-five percent of all plants are running sub-optimally, and that’s being conservative. Systems are always degrading; even valves have moving parts.”
The first step in addressing the issue is to get the right balance between predictive, proactive and reactive maintenance, according to Starr. “There is no magic number, no strict definition for what is a good balance,” he says. “Although most people will say that keeping reactive maintenance at 20 percent or lower is optimum, the right service schedule depends on how critical an asset is to plant and process performance, as well as the customer’s objectives in terms of variability, cost and equipment wear.”
To help customers stay abreast of service issues, ABB has instituted a subscription service to monitor control loops. The Process Automation Service is designed for any industrial plant that converts raw materials to products, such as minerals, pulp and paper, metals, oil and gas, glass, power generation and transmission, and alternative energy.
“Often these companies don’t have the staff or time to do things correctly, so we’ve developed this proactive service that uses technology to reduce their effort and expand their reach,” Starr says. “We’ve begun monitoring more than 17,000 control loops for customers in the past six months alone.”
The remote monitoring service provides a dashboard to customers that accesses information from devices on their networks. Starr estimates that proactive monitoring services like ABB’s can save customers millions of dollars. “Today, secure network connections and the technical sophistication of automation have made possible a new world of remote enabled services,” he adds. “These new services dramatically reduce travel times and provide access to experts in seconds.”
He suggests plants install a service portal node on their network with read-only links to the control system as a security measure before allowing remote service access. This limits remote connections to the site and reduces the risk that service work could cause the control network to go down.
“Condition-based maintenance that allows you to repair or replace only what’s needed, vs. trial and error work based on historical schedules, can save a typical plant hundreds of thousands of dollars in costs and thousands of man hours every year,” Starr says.