Profitability and Proactive Maintenance in Heat Treatment
Fluctuating energy costs, spikes in raw-material prices and the ever-increasing debate with changes nationwide over minimum-wage levels all add to the relentless pressure on the bottom line of an everyday heat treater. The question is: How do you take back control of your profitability and have funds to invest in a sustainable tomorrow?
At the heart of a sustainable heat-treat operation is a successful maintenance regime. Fluctuations in maintenance costs from month to month can test even the most profitable of operations and, unfortunately, can quickly limit the viability of those operating without a robust plan.
Surveys continue to show that most maintenance is reactive, and a survey back in 2011 showed that more than 36% of executives and managers across a wide range of capital-intensive industries said most maintenance is triggered by equipment failure. Research by the ARC Advisory Group states that ineffective maintenance management costs U.S. companies $60 billion annually.
Why is there still an emphasis on a reactive maintenance approach? Short-term financial pressures can encourage this seemingly low-cost approach because it requires less staff and low capital expense when everything is running normally. In the longer term, when sourcing expensive same-day parts and premium labor to get out of an emergency situation, these costs soon add up. The long-term costs of this approach have been estimated at 100x the cost of preventive maintenance. A well-cited everyday example is the regular oil change in a car engine. Typically, it costs $50 to change the oil, which is much less than the $5,000 cost of an engine replacement due to seizure/lack of oil.
What are the options?
If we go back to focus on the aim of heat-treat maintenance it should be to keep the equipment in operation for the desired life period with zero unplanned downtime. The typical furnace is a living, breathing animal (so to speak), and the heat and running effects over time will unfortunately reach a point where something breaks unless maintenance activities are carried out.
To aid ease of explanation, it is useful to compare current concepts of maintenance in terms of the human condition.
Is preventive or planned maintenance any good at achieving zero unplanned downtime? On the face of it, having certain checks in place based on historical trends and manufacturers’ recommendations seems like a sensible idea, and many heat-treat standards (including the automotive heat-treat standard CQI-9) do lead you down this path.
An example of planned maintenance would include the various pumping systems on vacuum furnaces. The manufacturers of these pumps will outline specific requirements for minor and major maintenance services typically based on the number of hours in use. However, this does not necessarily take into account the conditions in which the pump is operating (heat, dust, contamination, etc.).
The surprising truth, when this type of maintenance activity is analyzed in detail, is that an estimated 82% of equipment suffers not from a predictable failure pattern but from a random failure pattern. Based on this research, planned maintenance alone cannot achieve our zero unplanned downtime goal.
We do have other maintenance strategies at hand that can take real-time operating conditions into account and give feedback on how all these elements are performing. Predictive or condition-monitoring maintenance strategies rely on monitoring of machine systems to enable early indication of a potential future failure. This real-environment, real-time monitoring gives a more accurate assessment of the actual state of the equipment and has only been made possible through developments in sensor, data-collection system and software analysis technology.
Typical predictive technologies include oil analysis, IR thermography, vibration and ultrasonics as well as software solutions.
• Oil analysis has been carried out for a long time in the industry. Typically, the oil sample is sent to the oil supplier on a quarterly basis, and an analysis of cooling performance, water content, oxidation and other parameters are tested. If the results are not satisfactory, the oil can be cleaned or even completely replaced.
• Promoted by the insurance industry as a result of electrical fires from control panels, more and more companies are undertaking IR thermography of their control panels. The system is checked live (the use of a viewing window is very helpful) every six or 12 months to mainly assess for hot spots in wiring connections. The accompanying report from an IR inspection shows temperature across specific terminals to give a guide to the maintenance department to check connections and replace components if required.
• Out-of-balance fan conditions, if left unchecked, can create expensive damage to furnace components as well as reduce the effectiveness of the temperature circulation. Small vibration monitors can be added to the furnace fan and, if incorporated in the alarm strategy of the control system, can give early warnings of this condition.
• From a software perspective:
- Monitoring heat-up rates and percentage output values for gas-fired furnaces. The analysis can lead to identifying issues with air filters and/or incoming gas composition.
- Using additional sensors in the chamber to understand the temperature variability from batch to batch. Additional sensors in the hot and cold spots of the furnace (based on prior TUS readings/setup to AMS 2750E type-A or type-C instrumentation) provide a constant monitor of temperature variation (Fig. 1).
- Converting TUS data to heat maps (export to Excel) and comparison with previous surveys help to understand trends and predict the best time for insulation maintenance.
If predictive maintenance relies on detecting early-warning signs of failure and preventive or planned maintenance is based on adherence to a set schedule, do we still rely too heavily on symptoms rather than causes of failure (Table 1)?
The final strategy to outline is proactive maintenance. Proactive (the opposite of reactive) maintenance is performed to identity and eliminate the root cause of failure. The aim is to guarantee high reliability and longer service life and avoid expensive crash crisis situations.
New types of sensors, data-acquisition methods and software capabilities are driving the potential performance of the maintenance activity and aiding a more proactive approach. It has been estimated that proactive maintenance can yield tenfold savings over preventive and predictive strategies alone. Some examples are:
- Algorithms for controlling soot contamination in carbon-bearing atmospheres
- Reducing physical stress on heating elements by replacing mechanical contactors with electrical switches (SSR, SCR)
- Reducing electrical power overload situations using advanced SCR power controllers and sharing and shedding algorithms (Fig. 3)
- •Reducing instrument drift and breakdown by providing a controlled-temperature environment within the control panel
The following is an actual example of how a heat treater has leveraged data and maintenance activities to improve their operations. The existing heat-treat furnace was upgraded with new precision controls, additional sensors and an electronic data-acquisition system. The prior control system did not allow for analysis of data (paper-based system) and had limited sensors available to fully understand the performance of the furnace and base heating elements.
The furnace base was unreliable, and the base heating elements were prone to frequent failure. Trials were performed and data analyzed to improve the base brickwork design and reroute the elements. The design changes were made, and there have been no failures in elements since these changes were introduced. The new design of base brickwork also enabled a redesign of the fixtures that support the components. Prior stability issues were addressed, and this improved the health and safety aspects of loading.
The component loading plan was adjusted based on trials undertaken to fully understand temperature uniformity and gas path flows. The delivery of power to the furnace was able to be optimized by understanding the firing pattern of the furnace elements and changing power settings and offsets in the SCR/thyristor power controllers.
Improved uptime has been realized. The refurbishment has already extended the furnace life and lowered the maintenance costs by reducing the frequency of element replacements. The changes to the furnace also resulted in a 30% improvement in variation of heat-treated characteristics and enabled future business to be secured due to the optimized process performance.
Current and emerging technologies are driving future possibilities of maintenance more toward predictive and proactive maintenance strategies. Access to information in real time (Fig. 4) and utilizing advanced maintenance techniques help improve furnace reliability and uptime as well as optimize the maintenance budget to assist the entire heat-treat operation achieve sustainable profits.
Each shop floor is unique, with its own environment, heat, dust, etc. The only way to truly understand the situation is to collect data and use predictive algorithms to help provide insight into the required maintenance activity needed on your specific furnace. A thorough understanding of why parts fail can then be included in a proactive maintenance approach to eliminate the root cause of failure in order to create a more reliable furnace.
The author is presenting a paper at the upcoming ASM Heat Treat Show in Detroit, Mich. (October 20-22, 2015) that will outline current and emerging technologies to help improve maintenance and other activities in a heat-treat shop.
For more information: Contact Peter Sherwin, global digital marketing manager, Eurotherm by Schneider Electric, 44621 Guilford Drive, Suite 100, Ashburn VA, 20147; tel: 703-724-7300; fax: 703-724-7301; e-mail: Peter.Sherwin@schneider-electric.com; web: www.eurotherm.com
- Henry, Andrew and Nachlas, Joel, “Survey on Asset Management and Reliability Practices,” Virginia Polytechnic Institute and State University, January 2011
- Hollywood, Paula, “Predictive Maintenance Survey Reveals Drivers, Obstacles and the Future,” Plant Services, July 2012
- “Maintenance Resources What is Proactive Maintenance?” [Webpage] Retrieved from http://www.maintenanceresources.com/referencelibrary/oilanalysis/oa-what.htm, 2015
- Automation World, “Predictive Asset Management: A Success Story” [Webcast], Retrieved from http://www.automationworld.com/predictive-asset-management-success-story, July 2015
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- Christiansen, D. and Sherwin, P., “Predictive Strategies in Power Management,” Industrial Heating, June 2014