Highly adaptable, real-time measurement tools can measure and remotely monitor power-use and process status parameters to improve energy  efficiency in metalcasting facilities.

James Wiczer and Michael B. Wiczer, Sensor Energy, Vernon Hills, Illinois

(Click here to see the story as it appears in the April issue of Modern Casting.)

Manufacturing in the U.S. consists of many individual processes that often involve large, power-hungry industrial equipment consuming over $200 billion of electricity each year. Many of these processes require electricity as an input to produce process-specific outputs needed for the overall manufacturing process. These outputs can range from high-pressure air to focused heating, but all perform a vital step in the overall start-to-finish production process.

Few manufacturers know if they are using this electrical input in an efficient manner. Measurements have shown that manufacturing systems are frequently designed with a substantial overcapacity to accommodate anticipated growth in demand and to provide engineering margin to prevent a shortfall of equipment capacity under most scenarios.

In practice, manufacturers can easily determine if there is too little capacity in their production equipment because the output will not be adequate for the manufacturing process. Examples can include not enough air pressure to consistently drive the linear motion actuator tools, not enough hydraulic pressure for the molding press, or not enough heat to bring the subassembly parts to the necessary temperature to complete a metallurgical process.

However, what isn’t known by most manufacturers is if the equipment capacity is beyond their true needs for reasonable growth and some engineering margin. The problems with too much capacity are the ongoing annual costs for electricity, the costs of maintaining this unnecessary equipment capacity, the problems with determining how much extra capacity exists, and the impact on corporate culture from solving problems by committing extra resources to the issue.  For simplicity, we can exclude the unnecessary capital costs to acquire and install larger than necessary equipment and focus only on the additional energy operating costs. Measurements by our team and others indicate that in many cases, oversized equipment results in an unnecessary energy expenditure of 10% to 40% of the total annual operating energy costs.

In many instances, it is difficult to determine in advance exactly how much capacity is enough to achieve the desired output. Measurements and reviews of capacity requirements may not be possible until the manufacturing operations associated with a new process or a new machine have stabilized after the first 6-to-12 months of operations. Without knowing the right size for equipment in a particular manufacturing process, it is very difficult to not waste electricity on oversized equipment or time and money on undersized equipment.

In working with various manufacturers across several sectors, it was found an estimated 80% to 90% of manufacturers consume more electricity than they need.

One solution involves a system of multiple sensors to simultaneously measure both electricity input and the resulting output. Ideally, these measurement results will be available in real-time on the Internet for visualization and interpretation by key technical staff and other authorized stake holders. Although in many cases there is not a simple knob to turn that adjusts the input electrical power, often other factors will cause variations in the amount of electricity consumed. A multi-sensor monitoring solution will be able to measure changes in power input while monitoring the impact of these changes on key output parameters. This information can be used to determine exactly how much input power can be reduced while meeting the true requirements of the manufacturing process.

Custom Energy Efficiency

Prescriptive energy efficiency projects, where items like lighting fixtures are swapped out for a “prescribed” category of new replacements, play an important role in improving energy efficiency for certain types of energy uses, but they are limited to a subset of metalcasting facility energy use and typically do not include the majority of energy use. For further energy efficiency improvement projects, various types of real-time sensor measurements followed by multi-dimensional data analysis is required to achieve the desired reductions in energy consumptions.

Combining different types of sensor data to gain more knowledge than available from individual sensors is a valuable approach to transforming raw data into actionable information, but the technology to do it is complex. Sensing subsystems for monitoring different aspects of this problem are readily available but combining the information in a time synchronous manner becomes difficult as more sensing subsystems are included in the solution.

Technical obstacles exist to adding different types of sensors to supplement existing, commercial-off-the-shelf technologies (COTS) dedicated to measuring power use in a metalcasting facility. For example, to analyze furnace operations, melt temperature and melt weight may be needed in addition to gas or electricity consumption. Another example might be an efficiency improvement project focused on compressed air systems, in which header pipe air pressure and compressor outlet air flow measurements may be needed in addition to electrical power consumption data.

Some widely used types of energy monitoring meters may not be useful for energy efficiency projects due to their time resolution or the accessibility of their data. For example, electricity-use monitoring at 15-minute intervals between measurements (time resolution) will not be adequate to analyze some  compressed air systems that dynamically change operating parameters in 2 to 5-second time intervals. In order to correlate power with these types of dynamically changing parameters such as air pressure and air flow, better time resolution is needed. Similarly, foundry furnace efficiency projects probably need better than 15-minute time resolution to correlate temperature and melt weight with energy usage.

Although an initial energy efficiency project may utilize a simple power monitoring data logger, the challenge of adding synchronous process-indicating sensors to a “black-box” dedicated power data logger can be significant.

In addition to performing near-simultaneous measurements of disparate sensors, tools must be easy to use, low-cost and provide broad data accessibility to be successful in identifying return on investment (ROI) validated energy savings opportunities. If data are not easily accessible in real-time by facility personnel, the likelihood of an effective and successful energy project diminishes.

The process of identifying and validating energy-use reduction projects typically require energy-use monitoring tools. Costs associated with these tools must be included in the overall ROI analysis of energy efficiency improvement projects, including

• the acquisition cost of monitoring tools;
• engineering training costs associated with learning to use monitoring tools;
• the ongoing costs of retrieving power-use data;
• efforts to analyze power-use data;
• efforts to determine the best energy reduction project for a target manufacturing process;
• implementation costs of using the monitoring tools;
• efforts to analyze the cost-benefit ratio of the project against corporate ROI standards.

 

Depending on the selected monitoring tools, the skill level of the staff, and the specific details of the facility, some of these costs may be trivially small but other costs may be significant.

During the past 30+ years, many types of sensors have become smarter through the integration of network connectivity features, mixed analog and digital signal processing capabilities, on-chip data storage, and other digital electronic features. Some of the digital features that have made smart sensors particularly useful include the integration of real-time clocks, threshold activated alarms, virtual sensor creation through multi-sensor data fusion and CPU-based intelligent signal interpretation. Many of these advanced smart sensors are currently available as COTS integrated circuits.

To better utilize smart sensor technologies, a group of government, industry and academic sensor researchers have worked to create a family of standards for various types of wired and wireless smart sensors. This set of standards is known as the IEEE 1451.x family of smart sensor interfacing standards and provides a standard way to access data, format data and access electronic data sheets detailing various properties of the smart sensor.

Measurements in Metalcasting

The sensor interface hardware platform described in this article is based on a derivation of the original IEEE1451.2-1997 smart sensor interface standard. This smart interface enables the use of COTS legacy sensors (not smart sensors) to have many of the properties of advanced, integrated circuit based, “plug-and-play” smart sensors.

This approach was used to identify power usage and provide information to reduce power consumption in Midwest area casting facilities involved in melting several materials including brass alloys, gray iron, ductile iron, various types of steel, aluminum and zinc alloys.

Each smart interface measurement system provided the capability to remotely collect processed data continuously from eight diverse sensors at 2-second intervals.

These units also provided time stamped storage of sensor data in the data acquisition unit and shared this data with authorized local area network or Internet-based requestors. The in-unit storage feature enabled the continuous capture of data even if the network connection temporarily failed.

The data from the smart interface units was delivered via wireless Ethernet to PC-based, dashboard software designed to take advantage of the benefits of an IEEE 1451.2 interface. In addition to providing “at-a-glance” current status information of the various connected sensors, the dashboard provided historical data and analytical tools for the connected set of sensors.

Additionally, the dashboard data logging software created virtual sensors to facilitate time-correlation of sensor data. This data is globally available to Internet-based authorized users when the cloud-based data storage/web browser interface was enabled.

For many energy reducing projects, multiple types of sensors must be used to correlate power consumption with other key factors used in foundry processes. This measurement system is designed to synchronously collect sensor signals from current transformers and voltage probes combined with sensor signals from pressure sensors, flow sensors, process counters, vibration sensors, temperature sensors, humidity sensors and other process specific sensors. Better insights into opportunities for power-use reduction are gain through the ability to analyze power monitoring information with process-specific sensor signals correlated in time.

Compressed Air and Furnace Results

Figure 1 shows the combined power consumed by the three induction furnaces at a Midwest casting facility. Individual furnace power consumption information was analyzed in detail along with additional data about the melt process and other operational aspects. When this data was combined, the analysis showed opportunities for energy savings and production throughput gains based on small investments in additional operator training and the use of relatively inexpensive equipment enhancements. These measurements were used to validate the economic benefits of the process and equipment improvements.

Figures 2, 3 and 4 show the benefits of measuring equipment and process parameters simultaneously. For the compressed air system, significant savings were identified by a better understanding of the compressed air demand and air leakage rates at the facility. Figure 6 shows an overview diagram of the monitoring solution.

The results show that a monitoring solution using smart sensors can provide the required flexibility to implement successful energy efficiency improvement projects by leveraging information from a mixed set of sensor types. In addition to providing complex monitoring features in cost-effective, easy to use monitoring tools, smart sensor technologies facilitate the time correlation of various measured parameters. These technologies can help facility personnel stay engaged in the energy efficiency process by empowering staff with real-time, measured power consumption data combined with relevant process data that is readily accessible and easily understood.

Metalcasters can begin looking into taking a customized, data-driven approach to reducing energy in their facility by collecting the thoughts and experiences of operation personnel. These individuals can help suggest areas of the facility that might be good candidates for energy savings. Working with an energy consultant, at the direction and input of the people working in the casting facility, is an expeditious way to enact a data monitoring program.   
 

This article was based on a paper that was presented at the 117th Metalcasting Congress. The work described here led to an AFS Applied Research Award presented at the 118th Metalcasting Congress.