Predictive Maintenance Environment in Food Processing Plants Provides Early Warning System

Maintenance is moving from preventive to predictive mode with condition monitoring, maintenance system upgrades and the promise of easier integration.

By Bob Sperber, contributing editor

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The effort is in large part aimed at raising the visibility of maintenance leaders to make them “true peer partners with their enterprise systems counterparts in the organization. If they don't, decisions will be made without their input,” says Alan Johnston, president of MIMOSA, the Management Open Systems Alliance and chair of Open O&M.

Why is this important? “Because,” he says, “the corporate guys don't generally come down to the maintenance department and ask those guys for their viewpoint on interoperability standards.”

The core MIMOSA architecture places equal importance on CBM, reliability engineering and maintenance management systems. In the MIMOSA model, “open condition management” starts with sensors, data input and manipulation, alarms and events, diagnostic health assessment and prognostic assessments. Vibration tests, portable data collectors and other tools are used at this “diagnostic health assessment” level. Systems today are generally limited at that level, and human intervention is needed to provide the actual “prognosis assessment” following judgments based on common sense and further studies into methodologies such as root-cause analyses.

“In the old days and at many companies today, the operations and maintenance guys turn weekly planning and scheduling meetings into screaming and shouting matches,” Johnston continues. Production stresses the need to meet production goals, and maintenance argues for preventive and corrective maintenance time. And operations would traditionally win that argument while maintenance is given second-class status.

 

Infrared thermography reveals the motor in the background is running much hotter than the one in the foreground, which is operating under similar load conditions. The reading indicates a bad bearing or some other problem that will soon cause motor failure.

 

Today, he says, more companies are using condition monitoring and additional data to conduct orderly, fully informed meetings where maintenance is a full participant in the discussion. With empirical data, the maintenance representative at the table can say to production, “Look, we’re both trying to achieve operational optimization. If you don’t let me do X, this week’s metrics may make production look good, but next week you may pay for it in quality, yield or safety.” Today’s data-driven and increasingly integrated systems “allow the maintenance guy to be an integral business partner to the operations guy.

“That's the important over-arching theme for the maintenance professional,” says Johnston. “It's no longer about carrying a greasy rag and a wrench. It’s about being a full peer partner in determining what needs to be done for the operation.”

The actual standards are generally from the engineering, automation and especially the information technology worlds. (For example: ODBC, SQL, OPC UA; industrial Ethernet; various sensor, field and device buses). The importance of integration at the top, enterprise level is critical, says Johnston, who has put on many frequent flyer miles promoting the importance of open, integrated maintenance from an enterprise risk management perspective.

Note to Management
“A cultural shift has been going on for the past 20 years in American industry,” says Steve Matthews, business manager for Predictive Maintenance Solutions. “Going forward, the most competitive companies will not be looking at their maintenance departments as cost centers but as profit centers. The real value of maintenance isn’t fixing things when they’re broken. The real value of a maintenance department is to deliver plant uptime.”

SAP, the enterprise vendor with an equally dominant maintenance module, is promoting a survey conducted by Reliabilityweb.com in which only 20 percent of respondents characterized their CMMS/EAM implementation as successful and 57 percent said that theirs failed to generate the anticipated return on investment. That doesn’t sound like cause for celebration. But things could be changing as technology standards like Open O&M (see above article) take root.

In his own pitch to industry, Matthews’ favorite survey is more optimistic for those in a preventive, condition-based maintenance mindset. He cites an Electric Power Research Institute study in which maintenance costs are figured in dollars per horsepower. Reactive or failure-based maintenance was $17, preventive was $13, which is or 24 percent lower, and predictive was $9, which is 47 percent lower than reactive/running to fail.

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