More-intuitive, more-flexible software tools; cheaper and more-robust sensors; and a proliferation of mobile technologies are making predictive maintenance (PdM) more doable for a wider breadth of industrial facilities.
As Plant Services contributing editor Sheila Kennedy has noted, today's PdM-supporting tools, built with easier data sharing within and across plants in mind, "meet the need to reach beyond organizational confines for new points of view."
So who's putting a proactive, predictive approach to good use in their facilities? Let's look at three leaders.
1. Duke Energy
Sheila Kennedy shared this impressive case study last fall:
"As part of Duke Energy’s SmartGen project, a SmartM&D infrastructure was created to support a fleetwide network of sensors for online monitoring of critical plant equipment. All major rotating equipment was instrumented at more than 60 different plants. Around 30,000 total vibration and temperature sensors were installed; all of the equipment was modeled; and alarm levels were set. Now, anything out of normal operating range sends a notification to Duke’s main M&D center. Process data also is fed into the M&D Center. Oil analysis was consolidated so that 28 different sites now use the same laboratory; this allows one SME to review the analysis for approximately 130 generating units.
"Equipment failures cost millions of dollars in lost power generation, but Duke Energy’s reliability program is slashing the losses. Avoided costs totaled $4.3 million in 2014, even though SmartGen wasn’t fully operational at all the plants until late that year. In the first seven months of 2015, the avoided costs totaled $5.85 million."
2. The J.M. Smucker Co.
Are you ready for this jelly? Smucker's reliability team meets weekly with the operations team to plan out their next four weeks of maintenance scheduling. The teams refine their plans based on data gathered from PdM technologies as well as problems identified by operators during clean, inspect, and lubricate (CIL) rounds.
"We have begun to share our findings within the organization," Joe Anderson, PM and reliability leader at The J.M. Smucker Company, told Kennedy. "Data sharing is huge when trying to justify the need for scheduled line time to fix machine defects and also to develop credibility within the organization as experts on your assets. Everyone wins when everyone understands the importance of early failure detection and defect elimination."
He added: "Anytime you can drive defects out of your system, you will see improvements in safety, quality, environmental sustainability, throughputs, and plant stability."
3. Koch Fertilizer
Paul Dufresne, CMRP, recently shared this story about how a Koch facility overhauled its PdM program:
"The plant predictive maintenance (PdM) focus was on two primary technologies: vibration analysis and oil analysis. The plant was already executing both, but based on our failure data, it appeared that something was missing.
"The plant vibration program underwent an external audit/assessment from a third-party expert, and was overhauled to ensure that everything from initial point setup to missing points and routes are now being executed, and that performance metrics are in place to maintain the validity of the program.
"For the oil analysis program, the focus was on identifying and qualifying the equipment for acceptance into the program. The two primary goals of this program are to understand the condition of the oil and the condition of the equipment. Once identified the equipment was assessed for proper sampling point locations, the proper sampling hardware was identified and installed. The proper frequency, test slates and performance standards were also established. A complete tracking system and performance metrics were established and are tracked and reported monthly."
As Anderson and other successful PdM practitioners indicate, expanding and enhancing your facility's predictive maintenance program likely will require a shift in plant culture as much as in technology. To tackle the downtime and other production disruptions that result from a primarily reactive maintenance approach, cross-functional collaboration and consistent, continued education will be essential.
