Combined maintenance, energy strategies can boost productivity and cut costs

A proactive approach can identify equipment failure before it's a problem


When it comes to the effective management of resources, merging operational strategies—such as maintenance and energy consumption—is paramount. While not traditionally connected, equipment performance and energy consumption programs work together to effectively maintain machines and help optimize energy usage to keep costs in check.

But how do you merge two seemingly separate strategies? Find commonalities. In the case of maintenance and energy management, predictive monitoring is critical.

Instead of simply reacting to or correcting issues, plant managers who implement predictive strategies can proactively examine equipment for proper lubrication, vibration, and temperature levels—all signs that a machine is in good health. And when it comes to energy management, proactive monitoring can help optimize consumption. In addition, inadequately maintained equipment and systems are a major cause of energy waste. Together, these strategies can substantially reduce overall operating costs and boost productivity. 

An appropriate maintenance program

Proper maintenance of equipment can lead to increased productivity, decreased downtime, and reduced overall operating costs. But many manufacturers aren’t taking advantage of these benefits. Instead, manufacturers continue to spend as much as 40 %t of their operating costs on maintenance alone—factor in the cost of downtime and this number climbs even higher. Implementing a strategic, three-tiered maintenance approach that focuses on corrective, preventative, and predictive strategies can help decrease these expenditures.

A first step for many successful manufacturers is to perform an equipment criticality analysis. This analysis will help manufacturers identify potential issues, such as fail rate, mean time between fail rate, average length of downtime, and resulting negative business impacts for each machine and decipher between mission critical and noncritical equipment and processes.

Based on the analysis, a multistep approach, including corrective, preventative, and predictive maintenance, may be necessary for management of issues. Noncritical equipment will require a corrective maintenance program, while more critical equipment is best served with preventative and predictive approaches. At some point, however, all equipment may be in need of a corrective maintenance intervention, depending on the event. Predictive measures such as vibration analysis, thermographic imaging, and ultrasonic detection should be a focus for mission-critical equipment.

Corrective maintenance is one of the easiest maintenance strategies to implement. The concept here is when equipment breaks, fix it. Requiring limited investment, corrective maintenance programs are often popular. However, when equipment inevitably breaks, the shortcomings of this strategy quickly become apparent—unscheduled downtime, and its associated uncertainties and costs, can make it one of the most costly, not to mention frustrating, approaches available.

That’s not to say corrective maintenance is all bad. For equipment that is noncritical to production, like palletizers, torque wrenches, or forklifts, the minimal upfront cost and limited planned downtime associated with corrective maintenance can make it a sensible option. In addition, inexplicable breakdowns do occur—despite the best of predictive monitoring goals—and plants need to have a plan in place to address them.

Preventative maintenance, in contrast, aims to minimize unscheduled downtime and equipment failures through scheduled checkups that are based on previous failure events. This strategy—an intermediary between corrective and predictive activities—relies on repairs and maintenance based on visual inspection at fixed intervals, regardless of the equipment’s condition at the time. These types of inspections will help minimize unplanned breakdowns for equipment that is critical for plant operations.

For mission critical equipment, a predictive maintenance program is the best option. Using technologies such as vibration analysis and thermographic imaging to measure equipment condition, predictive maintenance helps assess when or if machinery will fail. Manufacturers must use this information to determine appropriate actions before the breakdown occurs. Economically, a predictive maintenance program will require larger upfront investments, but savings will accumulate over time as unscheduled downtime decreases and productivity increases.

Implementing a strategic, three-tiered maintenance approach can help manufacturers balance overall operation costs. It also allows them to take advantage of the specific advantages of each alternative. 

Predictive program makes sense

This same strategy of corrective, preventative, and predictive management can help improve energy efficiency. Increasingly, manufacturers are viewing energy management as a potential strategy for cost savings. When viewed as a production resource, energy can be managed as effectively as raw materials, equipment, or other production assets and can lead to decreased costs and increased productivity.

But how does a company get started? A maintenance program for equipment is an easily justifiable strategy; service contracts are even sold as part of the equipment investment. The value of a monitoring infrastructure to capture energy data is a bit harder to quantify.

Consider the three steps of a maintenance strategy. Energy management first requires an understanding of exactly where energy is being used throughout the plant, and how much of that energy use is critical to production. Is the majority of the energy consumed by certain machines? Are those machines running as expected?

Take a production line using compressed air. Is each compressor consuming its required amount of energy? If not, why not? In this manner, corrective actions—such as equipment repair and recalibration, or mechanical efficiency (i.e., installing variable frequency drives and motors)—can be applied to help improve efficiency of equipment operation and optimize energy consumption.

Second, by establishing a criticality of loads, such as prioritizing critical processes and equipment (for example, refrigeration or mixing) over noncritical loads (such as lighting or facility cooling), manufacturers can begin to identify strategic energy allocation during an energy event—such as a peak demand change—to prevent downtime or product loss.

Incrementally increasing energy intelligence is a key differentiator in how successful plants manage energy as a resource. By intelligently using plant floor data—already collected by historian systems, controllers, and production systems across the enterprise—manufacturers can understand equipment efficiency correlated to expected baseline performance. Through the process of reviewing performance and production data in terms of energy, approaches are transformed from reactive to predictive.

Through predictive monitoring, managers can look into their production data and begin tracking metrics such as peak demand and demand response times. This approach extends beyond simply confirming a line or machine is up and running, to helping make certain that it’s running at optimum levels. This is another common goal of both energy management and maintenance strategies.

By taking advantage of predictive control, operations managers can use the data to shift or curtail production during peak demand periods and implement demand response programs. The ability to respond to utility requests can offer significant savings on energy costs regardless of fluctuations in market prices. 

Effectively merging programs

The effective management of plant-floor resources begins with the establishing of business rules that are mutually beneficial in terms of maintenance and energy. This predictive mind-set focuses on a proactive versus a reactive environment, helping to ensure increased production and profits.

Plant managers, engineers, and operators should work with upper-level management to create business rules that effectively merge maintenance and energy strategies. By coming prepared with equipment criticality analysis and demand respond guidelines that clearly show profitability margins, the two groups can work together to develop a set of effective practices that benefit the entire organization.

When implementing a three-tiered maintenance strategy, manufacturers can reduce costs at the outset of the program by implementing a corrective approach for all machines. Organizations can realize longer-term savings through preventative and predictive measures for critical and mission critical machines. And operational costs can be further reduced by focusing on specific maintenance activities, such as condition monitoring, which help ensure optimal performance and in turn improve the energy efficiency of machines.

In addition to predictive maintenance, predictive energy management cuts costs by determining where, when, and how energy is being used and how it affects machine performance. By using production data and implementing demand response and energy efficiency programs, plants are experiencing significant savings on their utility bills.

An intentional and strategic maintenance program can lead to longer equipment lifecycles and better performing machines, ultimately reducing energy usage and lowering overall operating costs. Meanwhile, minimizing unscheduled downtime by limiting corrective and prescheduled maintenance activities on mission critical machines also helps increase productivity. Merging maintenance and energy management strategies for an overall emphasis on predictive manufacturing makes business sense and is an ideal way to achieve significant total cost of ownership savings on the plant floor. 

Mary Burgoon is market development manager, sustainable production; Jack Ecktman is program manager, storeroom and reliability services; and Jenifer Wright is global sustainable solutions leader for Rockwell Automation.

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