New tricks for old machines: don't run-to-fail, run-to-profit

How to make the transition from run-to-fail to run-to-profit

By Theresa Houck, associate editor

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How many companies want to buy more maintenance? None, obviously. Management wants to invest in predictability, cost-effectiveness and on-time delivery. Yet most plants still operate in run-to-fail mode and spend too much on repairs. This, despite the availability and affordability of both basic and advanced technologies that can be part of an effective predictive maintenance (PdM) program (Figure 1), and despite the myriad proven financial benefits of equipment reliability.

So why have so few plants made the move to PdM?

Many top managers simply don’t understand how reliability affects the bottom line, says Tracy Strawn, director of international programs with Marshall Institute in Raleigh, N.C. “Predictive maintenance is a tool for increasing uptime and production and reducing maintenance costs,” he says. “Maintenance personnel have to continuously demonstrate that to management with metrics.”

“Predictive maintenance programs have to be taken in context of the overall asset management life cycle,” says Dick MacDonald, senior vice president of product management with SPL WorldGroup, San Francisco, Calif., and former president and CEO of Synergen, which recently merged with SPL. “Companies need to look at asset management as a core competency — look at how the various assets work together, define the critical elements of the overall system, then tie it into a condition assessment program.”

Some organizations avoid starting a PdM program, or implement their programs incorrectly, because of misperceptions. For example, Strawn says manufacturers often pin their hopes on PdM to solve all their problems. “Predictive maintenance doesn’t fix anything — it simply identifies potential failures early so that appropriate corrective action can be taken. Identifying problems early can ensure maximum reliability and uptime at the lowest costs, but you still have to follow through on the corrective actions to realize that,” he explains.

Another misperception is that the technology itself will improve equipment reliability. “When you look at an asset’s entire maintenance program, PdM only represents about 15%,” says Sandra DiMatteo, director of marketing with Burlington, Ontario-based Ivara. “Most of the maintenance program is based on visual or some other sensory inspection that relies on the tradesperson. Technology simply provides a way to monitor or capture that.”

Then there are the workload and cultural barriers. Setting up a PdM program takes extra effort that can create resistance in the maintenance organization. “Maintenance managers often feel burdened implementing a predictive program,” observes Rich Padula, president of Syclo in Hoffman Estates, Ill. “It’s extra work for them.”

Understand costs of failures
A new definition of failure is emerging that no longer means equipment has stopped running. Plants that are using reliability, rather than maintenance, as the measure of performance define failure as “equipment that isn’t performing at the level at which we need it to perform.”

“We need to look at predictive maintenance not as a maintenance tool, but as a plant optimization tool,” says Keith Mobley, principal with Life Cycle Engineering (LCE), Charleston, S.C. “Your program should be set up to improve the reliability of equipment, the cost of goods sold and the life-cycle cost of the assets. It’s a never-ending journey if you do it right.”

Steelmaker Dofasco in Hamilton, Ontario, is Canada’s second largest steel manufacturer. In the late 1980s, the company embarked on a strategic project to evaluate its maintenance operations. The process that evolved over the following years created a different way of thinking about maintenance that focuses on equipment reliability in the context of “manufacturing process reliability.” This provides predictable, stable operations that allow Dofasco to meet its business objectives for customers.

“The key is to make sure there’s a line of sight to maximizing shareholder value,” explains Ron Thomas, Dofasco’s senior equipment reliability consultant and project manager. “We don’t talk about maintenance anymore, we talk about equipment reliability.”

The company’s equipment maintenance programs for individual assets are the focus of the company’s maintenance function. “We develop technically based equipment maintenance programs that identify the activities we need to maintain the level of capability of our assets,” Thomas explains. “Predictive maintenance is integrated into the asset’s equipment maintenance program. We rely fairly heavily on condition monitoring.”

Dofasco partnered with Ivara to commercialize Dofasco’s business process and the in-house condition monitoring software that Dofasco developed (now marketed by Ivara under the name Ivara EXP). The strategy for equipment reliability has five primary components:

  • Adopt a business process for equipment reliability.
  • Incorporate best practices for performing maintenance.
  • Support that process with enabling technology, such as CMMS software.
  • Develop an implementation approach that respects the change management approach to the process.
  • Sustain it through proactive management.

“Maintenance programs come and go, but a business process defines the way you do business,” Thomas says. “Using the business process is a tremendous integrator of technology and best practices. So a business process includes equipment maintenance, and has different elements, such as work identification, planning, scheduling, execution, follow-up, etc. When we design the equipment maintenance program, we consider predictive technologies.”

Québec Cartier Mining (QCM), based in Port-Cartier, Quebec, also has had success using reliability-driven maintenance solutions. QCM is one of the leading producers of iron ore products in North America. Using Ivara EXP software, the company has added $7 million to the bottom line through increased equipment availability and decreased operating costs.

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