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Accuracy of support unit's electric energy and compressed air consumption prediction models for a MAFAC KEA cleaning machine.
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Transparent energy flows within a factory are the prerequisite for energetic improvements of the involved production machines. With the ongoing digitalization of industrial production, innovative ways of creating energy transparency on the shop floor are emerging. Virtual energy metering points predict the power consumption of a regarded entity and...
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... electric power consumption of a water-based MAFAC KEA cleaning machine is predicted on machine and support unit level. Table 2 compares the prediction results from VMP models which are trained with machine-internal signals and thus model an IoT-compatible cleaning machine, to a brownfield cleaning machine for which only LED state signals are analyzed. ...Citations
... These methods are used to transform the electric energy metering device, realize the evaluation of the comprehensive benefit of the project, realize the effective exploration and analysis, and provide feasible and accurate methods and means. However, the determination of the weight value by these methods often focuses on subjective judgment, and it is easy to ignore the characteristics and exercises of the electric energy metering information [11][12][13]. At the same time, for electric energy metering information, it is complex and diversified data. ...
... This system outputs a value function for the DNS algorithm to determine the decision of the system, and the value function is represented by a nonlinear Q-function [26]. The current measurement and inspection result value function is Q (s, a), where s' represents the test result of the electric power at the next time point, and a' marks the best action in the next time point, and the best function value is selected in many experiments, as shown in formula (12) (12) Approximate the result of the judgment at the next time point to the actual state. It is necessary for r to reach the optimal weight state for the result a. Theoretically, the interactive robot behavior is updated to the weighted value w every time, and the DQN calculation method is the updated Q function. ...
... PLC and its I/O Modules and SFM Modules are connected to the Virtual environment through IOT. The virtual environment is specially designed for monitoring and controlling I/O Module of the PLC (Prasath et al., 2019;Sossenheimer et al., 2021). Virtual environment is developed by java or a specialized web designing tool. ...
... Load cell measures the actual weight of the product and it is given to PLC Analog Input Module. In addition to that the status of I/O is simultaneously uploaded in the virtual environment refer Figure 10 (Sossenheimer et al., 2021). ...
In past two decades, the automation of industrial machines is proliferating. Fourth industrial revolution (Industry 4.0) also focuses on industrial automation and artificial intelligence. As every technology has its ebb and flow, industrial automation also has huge scope in future and its own limitations. One of the major issues is in troubleshooting the virtually controlled machine. The biscuit making and baking machines are controlled using PLC I/O and HMI. The errors are rectified by taking feedback from machine’s component connections and supply connections. This helps us in troubleshooting the faults occurring in the connections and components used.
... Expert algorithms and machine learning were two examples of classification-based techniques. The name suggested that smart contracts are computer models taught by human professionals to solve complicated issues and made the same findings [20]. In the beginning, an expert system for detecting energy theft based on particular decision criteria was employed to detect the stealing [21,22]. ...
This article presents a novel method for diagnosing damaged rotor bars using random forests algorithm. A good motor and a defective motor with a broken rotor bar fault were used to get the transient electrical signal during motor starting. It retrieved 13 analytical time-domain characteristics from the starting short electrical signal to assess whether the engines functioned under standard or faulty conditions. An error check model based on random forest (ECM-RF) is proposed in this article. It reduces the number of attributes to two using the random forest’s feature essential aspects. When utilizing all available characteristics, the random forest accurately classified the motor state as either healthy or defective, with an efficiency of 94.8%, when simply using the K-means clustering and random forest. The random forest outperformed decision trees, Nave Bayes, linear discriminant analysis, and supporting vector machines classification models. As a result of the findings of the suggested technique, manufacturers can develop preventative maintenance programs.
... Non-intrusive load monitoring (NILM) captures power consumption signatures of machine tool components of specific machining processes (Sihag and Sangwan, 2020a). Due to the complex nature of the operation of machine tools, recent studies show that energy disaggregation of machine tools requires both high sampling frequency of sensors, mechanical understanding of machine tools, and appropriate selection of data analytics tools (Sossenheimer et al., 2019(Sossenheimer et al., , 2021. Although much effort has been dons for energy monitoring, it is still not a smart system. ...
Cleaning is critical to each location for a smooth surroundings which ends up in germs-loose surroundings. At instances, it appoints people for cleansing and will pay coins, and a number of the time cleanings are wanted in areas in which the presence of a dwelling being is unstable so it could not relegate humans in every spot. A few spots have a large ground vicinity in that spot for cleansing purposes, it wishes a couple of person so it required a few tactics to make up for those issues. In the headway of science, a robotic comes into the light, and computerization is an first-rate solution to this issue. This paper intends to foster an independent robotic that may flow with out ceaseless human direction. While doing marketplace studies, we got here to realize approximately some technical factors which may be improved. We additionally took a survey from a big network to apprehend their problems at the same time as cleansing in order that we are able to enhance the proposed version and make it user-friendly. The programmed cleanser robotic incorporates low-energy devouring digital elements, and it could paintings at low force. We proposed a self-ruling ground-cleansing robotic; this is operated through the Internet of factors and Raspberry Pi programming. The novel concept we have got used is to make power reusable and cooperate with different cleaners the use of numerous technologies. The renewable power-based “CleanO” will assist us to decrease the time and power and provide a residue/germs-loose climate.KeywordsCleanOFloor cleanerAutonomous ecofriendly deviceReusable energyIoT-based vacuum cleaner
Energy optimization of factory operations has gained increasing importance over recent years since it is understood as one way to counteract climate change. At the same time, the number of research teams working on energy-optimized factory operations has also increased. While many tools are useful in this area, our team has recognized the importance of a comprehensive framework to combine functionality for optimization, simulation, and communication with devices in the factory. Therefore, we developed a framework that provides a standardized interface to research energy-optimized factory operations with a rolling horizon approach. The optimization part of the framework is based on the OpenAI gym environment. The framework also provides connectors for multiple communication protocols including Open Platform Communication Unified Architecture and Modbus via Transmission Control Protocol. These facilities can be utilized to implement rolling horizon optimizations for factory systems easily and directly control devices in the factory with the optimization results. In this article, we present the framework and show some examples to prove the effectiveness of our approach.
