Continuous Energy Benchmarking for the Metalcasting Industry


elting operations are the dominant uses of energy within metalcasting busi-

nesses. And many other plant process- es depend on how efficient the melting production is. Detailed monitoring of furnace energy-usage can result in im- provements in production throughput and reductions in energy costs. AFS recently commissioned an

energy efficiency R&D project at several metalcasting facilities (AFS Research Project 12-13#03), utilizing advanced sub-metering that was connected to major energy consumption devices. Sub-meters provide useful insights about how energy is used in a foundry. It’s easy to know how much energy is purchased every month but it is difficult to know each machine’s energy usage and the overall cost impact of energy usage by a particular machine or process. Furnace operations was a ma-

jor focus area of the study but other machines can also consume significant amounts of energy. Different facilities and different processes have different sub-metering needs. Some frequently useful sub-metering measurements can be collected every two seconds and may include a range of metrics, including: • Te rate in which electricity is con- sumed (kW).

• Electric energy consumed for dif- ferent time periods (kWh).

• Compressed air and vacuum pressure. • Temperature, including melt tem- perature and equipment exterior surface temps.

• Run-time. • Natural gas consumption rate and total consumption.

• Oxygen or other gas consumption rate and totals.

• Production units including pounds per melt (batch) and pounds per day (time unit). Depending on the details of the

foundry, this type of information can be collected with sub-meter measure- ments of energy-intensive equipment frequently used in foundries. Examples

of the type of equipment that may be good candidates for sub-metering measurements include: • Furnaces. • Air compressors. • Hydraulic pumps. • Dust collectors. • HVAC.

AFS Research Study Results During the AFS study, both pro-

duction output and energy usage var- ied dramatically but not in tandem. Tap-to-tap furnace times, melt time per pound and other batch metrics all indicated large variations during most measurement periods from days to months. In many instances, the staff and management were unaware of the extent of these variations. Without detailed, time-resolved measure- ments, production metrics may not be apparent and so the root cause of monthly production variations is often unclear.

Te AFS study highlighted the value of sub-meter measurements to glean useful insights into furnace operations. Assessments of furnace utilization can benefit from tracking furnace power-levels during daily op- erations. By monitoring how long the furnace was using various power levels during each melt cycle and aggregat- ing this information over a longer time period (day, week, or month) ex- tremely useful insights can be created regarding furnace operations. Cor- relating tap-to-tap cycle time of the melt with common power level set- tings provided significant insight into the production variations. For this study, four power levels were selected as common settings during operations including Off, Hold, Medium and Full power levels. Findings included longer than expected “Hold” times, inappro- priate power settings during “Hold” periods and excessive use of “High” settings. Tis study also found that the furnace was “Off” at unusual times of the day. Recommendations to correct

some of these findings can result in total potential savings that exceeded $1 million per year with no capital expense requirements. In addition, for the AFS study,

special reports were developed to summarize how long the furnace was operated at each power-level setting (Off, Hold, Medium and Full power) and a scatter-gram plot showing hun- dreds of furnace cycles to help under- stand the overall statistical variations in furnace processes. Management could now monitor the relative ef- ficiency of the melting operations in near real time and be alerted when anomalies occurred. Summary reports by hour, day, week, month, were also created to easily review relative varia- tions in furnace operations over time. With this type of measurement and data presentation, unexpected varia- tions could be identified and mea- surements can be further analyzed during the relevant time period. Tis can result in more consistent opera- tions, increased throughput and lower energy costs. Such automated analysis and reporting represents an advanced form of benchmarking that is unique to the metalcasting industry. Another option is to develop manual

data collection at your plant. Simple charts recording the start times of im- portant parts of the cycle may help you identify developing issues or provide opportunities to improve operations. Automated data collection can include things like burner natural gas-usage rates, door open times, and casting times. For instance, these measure- ments may highlight that burner high fire and low-fire settings differ between similar furnaces. Other findings from simple charting efforts can assist staff in understanding variations in charge time and can help optimize processes.

You can contact Brian Reinke (AFS Energy Program Manager) at for more information on this study. Some of the sensors and equipment used in the AFS research project are available to AFS corporate members for studies at their plants.

August 2017 MODERN CASTING | 41

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