Melting operations are the dominant uses of energy within metalcasting businesses. And many other plant processes depend on how efficient the melting production is. Detailed monitoring of furnace energy-usage can result in improvements 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 major 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:
•    The rate in which electricity is consumed (kW).
•    Electric energy consumed for different time periods (kWh).
•    Compressed air and vacuum pressure.
•    Temperature, including melt temperature 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 measurements 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 production output and energy usage varied 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 measurements, production metrics may not be apparent and so the root cause of monthly production variations is often unclear.

The 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 operations.  By monitoring how long the furnace was using various power levels during each melt cycle and aggregating this information over a longer time period (day, week, or month) extremely useful insights can be created regarding furnace operations. Correlating tap-to-tap cycle time of the melt with common power level settings 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, inappropriate power settings during “Hold” periods and excessive use of “High” settings. This 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 hundreds of furnace cycles to help understand the overall statistical variations in furnace processes. Management could now monitor the relative efficiency 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 variations in furnace operations over time. With this type of measurement and data presentation, unexpected variations could be identified and measurements can be further analyzed during the relevant time period. This can result in more consistent operations, 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 important 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 measurements 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 breinke@tdi-energysolutions.com 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.

Click here to see this story as it appears in the August 2017 issue of Modern Casting