Nerd For Tech
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Nerd For Tech

Energy Monitoring and the Internet of Things

what things, you ask? well..

1. Significance of Problem

In Today’s challenging economic climate business owners are looking for new ways to curb costs. In order to do this they must understand, precisely, their existing costs, liabilities, and assets. A good place to start is to monitor the energy consumed in manufacturing their products. To provide some background, I am currently working at a tyre manufacturing plant where we have just recently implemented a thorough network of meters and gauges to determine the utilities being consumed by each department; namely Air, Steam and Electricity.

Up until now, there were limited meters and gauges present for process variable measurement. And those that were installed had only local display. This meant that there were very few values that were logged throughout the day because someone would have to physically go to the location and manually record the values. This also gave way to unreliable readings due to natural human error.

Another problem we faced was that any attempts made by the work-force to cut utility costs often went unnoticed as there were no reliable methods in place to determine the ‘before and after’ difference in cost saving.

We were also unable to determine exactly how much manufacturing cost each of our products incurred. Currently this cost is based on production volume and the sum of each utility bill as a whole without taking into consideration the different types of products being made (with certain products costing more than the others).

2. Impact of Solution

2.1 Troubleshooting

This project has helped us identify areas in which we suffer most losses. We are now able to troubleshoot problems much faster as well. Now each utility department manager can reach the source of a problem even before the consumer is notified about it. This is possible due to real time values being displayed with the option of adding alarms that can notify the relevant people via email of any discrepancies in measurement values. Since this project has been implemented we can now view process variables in real time. Air, steam, and electricity are amongst the major costs associated with our products. Real time monitoring and logging of these values has substituted manual logging methods giving way to better accuracy and more frequent data logging. Logging these parameters every 5 seconds gives us deeper insight into how frequently and quickly our energy demand changes. In the past it was difficult to identify temperature and pressure drops as they would sometimes take place during the night shift when swift counter measures could not be taken and thus the line manager would have to wait till the morning and report to the Manager about the loss in production due to process variables not being as required. With the introduction of EMS we are now able to identify the time and place where the pressure or temperature drops take place using the time series charts which can store data for up to months. This way the problem is diagnosed much faster and can subsequently be solved in a shorter period of time resulting in better yield, both qualitative and quantitatively.

2.2 Determining new projects’ viability

Now that we have a detailed view of our energy consumption it is a lot easier to determine how beneficial a new project can, or cannot, be before investing a large sum of money into it. This is especially helpful when vendors offer to give a demonstration of their product. For example, if a vendor is providing a motor with better efficiency that they claim will save on electricity consumption, we now have the tools to check exactly how much, if any, electricity was saved.

2.3 Product Costing

One of the greatest benefits this system provides is the ability to calculate the cost of each product category individually. By measuring the air, steam and electricity being consumed by each department , and dividing the total quantity produced by the former we can determine the unit cost of each item category. This will also help us evaluate employee performance by establishing benchmarks and providing incentives if energy consumed per unit is lower , or take corrective measures if it is higher.

2.4 Analysis and reporting

With all this data being fed into our systems the data must be organized and presented in such a way that is intuitive and readable to the relevant managers. The purpose of this system is somewhat lost if the data is left unfiltered and unsorted with these tasks being left for the managers to do. We have therefore condensed the information in HMI Screens with each department having their own. This helps with easy navigation and gives the relevant people quick access to the information they need. With this we have also implemented row level permissions by password protected screens. This ensures that only the people who are meant to have access to certain information can obtain it. This, however, is not the full extent of the EMS. Data analysis of these figures can improve our understanding of the manufacturing processes and help us optimize them further. Leveraging the power of the cloud we are also able to provide relevant department heads with daily reports of consumption and efficiency of production thereby enhancing accountability and ownership.

3. Architecture of Solution

3.1 Hardware configuration

3.2 Instruments

The project consists of a network of cables in cable trays coming from every meter and instrument and connecting them to the main panel. The method of connecting the energy meters is different from the rest of the instruments because of the signals i.e RS485 protocol for the energy analyzers and 4–20mA signal for the pressure, temperature and flow measuring devices.

3.3 Wiring

· RS485 can be looped together in series by connecting one meter to the next and finally taking a single cable from a number of meters looped together as displayed below:

· 4–20mA signals, however, require each device to be individually connected to the PLC analog module.

To help reduce the clutter of cables we decided to collectively bring all the 4–20mA wires (2 wires from each meter) into 2 main junction boxes from where two main multi-core cables carry the signals into the main panels. This can be seen in figure3.

3.4 Processing and Output

The main panel contains the programmable logic controller (or PLC) This device collects all the signals. Once all the signals have reached the PLC they are processed by applying different scaling and normalization techniques. After this they are stored and displayed on HMIs (Human machine interface) and/or desktop screens.

To leverage all the data we have used an internet gateway device to transmit this information to the cloud in real time. The gateway device has support for AWS IOT. What this means is that the data is being transmitted over MQTT protocol and is available to us in generic JSON format via API endpoints which we can integrate with any of our third party applications. This helps us use this data with other software to help gain a better overall view of operations. This also lets us perform real-time analysis to implement production forecasting and predictive maintenance.

Each one of the four computers shown above are installed with visualization software. This allows those computers to display customized visuals of the processes with real-time values being shown. These locations have been placed in such a way so that the managers of each utility have access to these screens for quick trouble-shooting and monitoring. We have also installed an internet gateway device for IOT access. This allows us to transmit values in real-time onto the cloud for further processing and analysis. Other cloud applications include threshold monitoring with notifications.

4. Going Further

So far we have just scratched the surface when it comes to the potential of this system. There is a lot more useful information that is hidden in the large amounts of data being stored. One such example is to observe electrical signatures for measuring batch production. To be specific, lets take the example of the mixing section where energy meters have been installed on large motors used to mix the rubber compounds. Every time a new batch is put into the mixing mill, the current (and therefore the consumed power) goes up significantly, followed by a drop as the batch is passed on to the next process. Already knowing how much a single batch weighs we can calculate the total production for a given period of time by multiplying the number of wave peaks during that time and the weight of a single batch.

Another use of this data can be to estimate when a machine might breakdown. There are certain electrical parameters that may be monitored to indicate equipment failure. For example, a bearing that is beginning to gall can put extra load on the motor. The extra load would then in turn cause the motor to draw extra current. If left unchecked this excessive current can overheat the winding and burn up the motor. With energy metering, however, we can now see if current values seem strange in any way and take action before failure. Apart from this, we can also determine equipment health on a regular basis.

5. Going even further

To sum this up, IOT is an emerging field with vast applications across any type of industry. When coupled with analytical tools, this combination can boost business growth and improve efficiency at the same time by using existing resources more responsibly. It condenses information into meaningful insights in order to supplement and empower existing professions by simplifying decision making processes.



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