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Alcoa Warrick Operations Smelter, a fully operating smelter in the United States, recently increased its use of predictive maintenance (PdM) as part of its larger Reliability Excellence (REX) program. REX is an Alcoa (www.alcoa.com) corporate initiative designed to reduce maintenance costs and achieve sustainable performance levels.
Figure 1. Alcoa’s Warrick site in Evansville, Indiana, was founded in 1960 and has an annual capacity of 269,000 metric tons.
Site-wide, there are more than 1,950 total Warrick Operations employees. The Evansville, Indiana, primary metals business includes five smelter potlines with a capacity of 269,000 metric tons per year, which supply molten aluminum to a rolling and finishing operation that supplies flat-rolled aluminum for use in food and beverage cans. The plant also provides metal for the lithographic printing industry. (Figure 1)
One area that needed improvement was the tracking of PdM information. Identified defects would, at times, fall through the cracks, and equipment would run to failure before repair. Smelter Engineering Manager Joseph Motz, CMRP, tasked reliability engineers and technicians with finding a better way to track information and create a cradle-to-grave system. “Defects must be tracked from the time they are found to the time they are proven to be fixed. Losing information halfway is unacceptable,” says Motz.
The process for tracking PdM information at Warrick had been less than optimal and did not provide feedback to technicians on defect correction progress. “Our predictive maintenance technicians would perform their work, send out reports, and then rarely ever hear anything back. They didn’t know if their work had changed anything for the better,” says Reliability Coordinator Josh Estep, CMRP. “Unfortunately, the only feedback that they would consistently receive was when equipment would fail unexpectedly. For predictive maintenance technicians, it is devastating to find that the underlying risk had been discovered and reported prior to the machine failing in service.”
Because their findings and recommendations were sent without feedback, visibility, or accountability, the predictive maintenance technicians never learned if the problem was fully remedied or if the root cause was repetitive in nature. The plant’s predictive maintenance team was eager to have a more meaningful role in the equation.
Without a centralized system, reports and information coming from different monitoring technologies were at risk of being lost and forgotten until failures occurred.
“Electrical reports were sent to an email distribution list, after which the planner was responsible for writing a work order and scheduling repairs,” explains Estep. “On the mechanical side, we used an Excel spreadsheet to log machine conditions and findings. The file was sent out once a month to an email distribution list, after which the planner became responsible for generating and tracking the work.
“The electrical program lacked a reporting tool to summarize and prioritize the work, and, while the mechanical program had these capabilities, it failed to provide timely feedback on equipment conditions,” says Estep. “Furthermore, both systems had a flaw in the lack of a closed-loop reporting system where machine defects stay in the system until proven through data that they are fixed. We needed this cradle-to-grave, closed-loop reporting to improve machine reliability.”
A new, centralized reliability tracking system was needed to automate the processes. The preferred system would increase employee engagement and satisfaction while achieving economic and regulatory goals, as well as contribute to the overall success of REX (Figure 2).
Figure 2. A new, centralized reliability tracking system was needed to automate the processes.
Web-based communications and handheld devices for tracking routes and capturing data would simplify the predictive process and encourage comprehensive recordkeeping. For instance, trend values such as temperature or current could be logged on handheld devices rather than tracked on paper. Captured data could include thermographic inspection results, including which equipment is down and what isn’t loaded or can’t be inspected. In lubrication rounds, technicians could enter whether an asset was greased, in addition to the amount of grease used. Housekeeping observations processed on the fly might include a machine making noise or leaking oil or an area of the plant requiring cleaning.
Alcoa Warrick Operations began using 24/7 Systems’ Web-based program called Tango in 2001 for the tracking of high-criticality AC induction motors. The asset-based tracking system helps the smelter to keep track of failure data and repairs, along with helping to locate suitable replacements. In 2008, when a better defect tracking system was being pursued for predictive maintenance, it was determined that Tango software made the most financial sense for the smelter. The system was already in place and there was already a history of cooperation between 24/7 Systems and Alcoa, not to mention it was a fraction of the cost of going with the other potential solutions.