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Predicting behavior

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Easily as important to the efficient operation of a metals plant as the production line is the best use of downtime to ensure the production line is offline as little as possible. Steel mill and other metals plant professionals are utilizing predictive maintenance technologies for routine and scheduled maintenance, as well as for responding to unexpected breakdowns and repairs in the mill’s furnaces, on the production line, in inventory control and even in logistics.

A maintenance tool of the 21st century, predictive maintenance uses software and nondestructive testing technologies, including infrared, acoustic, corona detection, vibration analysis, sound level measurements, oil analysis and other specific tests to evaluate the condition of mill equipment and avoid failures. Done properly, predictive maintenance allows more convenient scheduling of corrective maintenance. As a result, staff in the mill or plant can better plan maintenance work and maintain better inventory control over spare parts. Also, when executed correctly, predictive maintenance results in fewer planned outages and shorter planned production downtimes, increasing plant or mill availability.

Reactive maintenance programs, what some in the industry have described as a fire-fighting strategy, involves fixing machinery only when it stops working. The predictive maintenance approach stresses improving the function and design of production equipment. That switch in approach, however, does not come without cost. Predictive maintenance typically requires greater management commitment in terms of training, resources and integration.

During implementation of a predictive maintenance program, different decision-making processes are required, especially concerning the selection of the most suitable diagnostic techniques. A wrong decision can lead to the failure of a predictive maintenance program and its elimination, with subsequent economic losses.

Metals plants are becoming increasingly sophisticated in how they utilize predictive maintenance. That is particularly apparent in the global steel industry.

Tata Steel Ltd. in India has developed sophisticated predictive maintenance technology for continuous production. The procedure goes beyond the usual practice of monitoring the equipment condition using only a single parameter. The company’s Mechanical Technology Group reported that the predictive maintenance procedures employed monitor temperature, thermal profile, vibration, the condition of lubricants, and particle size count, synthesizing all the information for an accurate diagnosis. The Mechanical Technology Group analyzes the data online to get not only a list of possible problems but also the probability of their occurrence.

Depew, N.Y.-based IMI Sensors, a division of PCB Piezotronics Inc., points out that steel mills not only have typical fans, pumps, compressors, gearboxes and cooling towers but also have machines and processes unique to the steel industry. The machine sizes, machine designs, operating speeds, cycle times, batch operations and harsh mill environments often command the use of carefully selected sensors and methods for effective equipment monitoring. Ironmaking and steelmaking areas often have an abundance of large belt conveyors, critical ultra-low speed machines with limited rotation, critical large overhead cranes and large volume turbo blowers coupled with hot blast air at more than 2,300 degrees Fahrenheit, molten liquid iron, red hot slabs, potential carbon monoxide risks, and, of course, rolling and annealing mills.

The company’s Sensor Selection-IMI line of precision accelerometers, bearing fault detectors and output sensors help meet the needs of the company’s steel industry customers. IMI Sensors notes that while most sensors can be used in a wide range of applications, some sensors are better suited for the harsh conditions encountered in steel mill applications.

ArcelorMittal’s mill at Vanderbijlpark in South Africa is one of the world’s largest inland steel mills and the biggest supplier of flat steel products in sub-Saharan Africa. To keep all of the plant’s equipment up and running is the task of the Condition Monitoring Team at the Reliability Engineering Department of ArcelorMittal South Africa. The team uses many condition monitoring tools, including thermal imaging. To ensure proper operation of its production plants in Vanderbijlpark, ArcelorMittal South Africa uses FLIR thermal imaging cameras. This improves efficiency, safety, helps to avoid breakdowns and to minimize downtime.

“The advantage of using thermal imaging cameras is that you can see a problem developing long before it becomes visible to the naked eye, enabling you to make informed decisions regarding a suitable course of action. This leads to increased production, improved safety and increased equipment life span,” explains Douglas Glen, senior thermographer at the Condition Monitoring Team.

Much of the predictive maintenance work being performed for metals plants today originates from third-party providers. Ledyard, Conn.-based Emprise Corp. offers predictive maintenance services to a wide variety of clients, including U.S. Steel Corp. and its Great Lakes Fleet. The company’s machinery diagnostic services include comprehensive oil analysis packages, vibration analysis, electrical thermographic analysis and in-place dynamic balancing. Emprise designs, develops, installs, trains and supports custom predictive maintenance systems, thereby promoting competitiveness, productivity and cost-efficiency on a client-by-client basis.

“Our dedicated reliability engineers, computer programmers and technical personnel host a complementary range of skills and degrees, as well as commitment to an unparalleled work ethic,” Emprise tells clients. “They are trained in quick-response techniques, problem analysis, and custom design of predictive maintenance systems. They work closely with clients during development and setup, provide hands-on training and remain on-call when clients become self-sufficient.”

Minnesota’s Hibbing Taconite Co., managed by Cliffs Natural Resources Inc. on the state’s Mesabi Iron Range, has won industry awards in recent years for its lubrication program. The Minnesota taconite processor trained reliability engineers as Level 1 machine lubrication technicians in an aggressive condition monitoring program designed to help identify problems at an early stage of failure. The company’s program resulted in a 3.5-percent energy reduction by switching to synthetic gear oil with a one-year return on investment (ROI). The plant also installed predictive maintenance software to help company engineers with ultrasonic examination and laser alignment of bearings and shafts.

Azima DLI of Woburn, Mass., advises clients that there are “many issues involved in deciding whether to initiate a predictive maintenance program. Even if a program is already in place, it is often difficult to quantify the benefits of implementing a computer-based system.” Instrumentation can cost anywhere between $10,000 and $40,000 to install, and training can quickly add to that start-up cost. But the company, a major U.S, provider of predictive maintenance analytical services and products, notes that one overlooked benefit of a predictive maintenance program is increased safety. “Predictive maintenance provides the reassurance of safe, continued plant operation,” Azima DLI noted. “By reducing the likelihood of unexpected equipment breakdown, the safety of employees is improved. Although difficult to quantify, there is a definite economic benefit in improved employee and union relationships.”

The company added that money spent on an effective predictive maintenance strategy would be quickly returned in improved operating efficiencies, including reduction in lost production, reduced cost of maintenance, less likelihood of secondary damage to equipment, reduced inventories of spare parts, extension of the life of plant and mill equipment, and improved product quality.

Some firms specialize in component parts of a mill or metals plant. Irving, Texas-based Shermco Industries, for example, targets its predictive maintenance service to the electrical equipment that powers a mill or metals plant. “Nobody chooses to be blindsided by an electrical equipment failure,” the company said. “Costly failures blindside only those who don’t identify problems before they occur.”

Shermco’s comprehensive predictive maintenance program includes a package of visual inspection; online partial discharge analysis; vibration analysis; borescope inspection; alignment checks; infrared and thermal screening; ultrasound inspection; offline electrical testing; online motor testing; current signature analysis; oil diagnostics and lubrication analysis; motor shaft inspection; corona scanning; power quality and harmonic analysis; and SF6 gas analysis. Shermco’s engineers and field service technicians come to the customer’s mill or plant to perform an all-points audit of the electrical distribution system, applying the best practices and latest technology to keep assets operating efficiently.

Those who have committed to predictive maintenance swear by the process’s result. Aarrowcast Inc.’s foundry in Shawano, Wis., adopted a predictive maintenance plan in 2011. Today, the 52-page plan includes statistics, charts and instrument readings that help guide the foundry’s production.

Al Gambsky, predictive maintenance supervisor for the foundry, told the American Foundry Society that prior to adopting the new process, Aarrowcast repaired and replaced machinery and equipment parts on a scheduled basis. Like in a typical maintenance plan, some parts were replaced while they still had life in them; other equipment broke before being scheduled for replacement.

The iron casting foundry had undergone a major $20-million expansion in the late 1990s and had reported strong growth through the recession of 2008-09. But growth fell off following the recession, and the company determined to make the facility as efficient as possible. The 2011 predictive maintenance project resulted in the installation of motor condition monitoring, stroke monitoring and infrared thermography equipment on the three molding lines. Additional monitoring equipment was installed each year after 2011.

Metals manufacturers and processors are increasingly discovering that a well-designed predictive maintenance program can pay dividends in the long run.


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