bluuebunny/crossref_metadata_2025 huggingface dataset:
Novel bio-waste of Cinnamomum Verum leaves-derived carbon coin cylinder-like as sustainable electrode material for symmetrical supercapacitor
Authors: Taer Erman , Yanti Novi , Apriwandi Apriwandi , Taslim Rika
Published: December 2023

Carbon material sourced from bio-organic waste is a promising electrode material exploration for the development of sustainable supercapacitor devices. Interestingly, their relatively environmentally benign sources and unlimited availability are the right choices to be developed as energy conversion systems and energy storage applications. Here, a novel high-potential bio-waste has been studied as a carbon source for electrode materials for symmetrical supercapacitor applications. Biomass materials were selected from Cinnamomum Verum leaves waste which was given a series of measurable and systematically structured treatments. Carbon precursor was synthesized with a simple strategy through a one/two-step activation ratio in an integrated pyrolysis system. Their chemical impregnation focused on H3PO4, ZnCl2, and H3PO4+ZnCl2 solutions. The renewal of the study was also highlighted in the design of a solid coin-like carbon cylinder material without additive binder. The solid carbon material that has been obtained has been evaluated for all dimensions including mass, thickness, diameter, and volume. In addition, the density of the coins that have been generated through density calculations is also reviewed. The density of the coin’s carbon shows a value of 0.98 g cm−3 with an average standard deviation of 0.08. The electrochemical properties of carbon electrode materials were studied through cyclic voltammetry (CV) and galvanostatic charge-discharge (GCD) analysis. In the two-system configuration, the optimized electrode exhibits a specific capacitance of 162.83 F g−1 at 1 A g−1 and 101 F g−1 at 10 A g−1. Furthermore, their performance is relatively high at a coulombic efficiency of around 76.23% with a capability rate of 63.11%. Moreover, the resulting energy density is 17.18 Wh kg−1 at a maximum power density of 125 W kg−1. Therefore, this study offers a new strategy to obtain carbon solid coin-like from bio-organic sources of Cinnamon Verum leaves as a high-quality electrode material to improve the performance of symmetric energy storage devices.
Identified potential of mangosteen peel agricultural waste as electrodes component of a supercapacitor: a study of electrochemical behaviour
Authors: Taer E , Nasution W M , Apriwandi A , Ginting R T , Taslim R
Published: December 2023

Renewable porous carbon from lignocellulose material as the basic material for supercapacitors is of great interest to researchers because of its high application potential while solving environmental problems. Biomass-based lignocellulose components are the main choice because of the extraordinary impact on the carbon structure they get. Here, the identification of the potential of lignocellulose biomass from mangosteen cultivars as source material for electrode materials for supercapacitors has been studied on their electrochemical behaviour. The electro-physico-chemical features are reviewed in detail through cyclic voltammetry (CV) and galvanostatic charge-discharge (GCD) analysis at different ranges of scan rates and current densities. The obtained electrode was prepared by adding 10% polyvinyl alcohol binder to 0.7 gr carbon powder. The supercapacitor cell design is prepared in a symmetrical shape bounded by an organic separator. In general, the electrochemical properties of the electrode materials that have been obtained confirm the normal electrical double-layer capacitor features with an indication of the presence of apparent capacitance. The highest specific capacitance was 153.31 at 1 A g−1. Furthermore, the energy output was recorded of 1.67 Wh kg−1. These results confirm that an electrochemical study of mangosteen peel-based carbon materials has been successfully carried out for supercapacitor energy storage applications.
The effect of pressure strength of porous concrete on the addition of natural pahae zeolite as a partial replacement of cement
Authors: Fynnisa Z , Frida Erna , Susilawati  , Bukit Nurdin , Zebua Hatta Maulana
Published: December 2023

Innovations regarding the manufacture of porous concrete continue to develop in Indonesia. One of the innovations in making concrete in this research is adding natural pahae zeolite originating from North Tapanuli as a partial replacement for cement in porous concrete. Porous concrete is made of 15x15x15 cm, which refers to the ACI 522R-10 method with a compressive strength test age of 7 days. Variations in the thigh natural pahae zeolite composition for reducing cement are 0%, 10%, and 20%. The compressive strength test of porous concrete showed increased values after adding thigh natural pahae zeolite. The highest increase in sample value was found with the addition of 10% of natural pahae zeolite, with a percentage increase in test results of 25.76%.
Application of Anisotropic Gold Nanomaterials in Plasmonic Sensors for Detection of Glyphosate
Authors: Iwantono  , Saputra Arif Darma , Taufik Hidayat HSB , Nurrahmawati Puji , Nafisah Suratun , Novaliza Mayta , Morsin Marlia , Awitdrus  , Agustino
Published: December 2023

The trend of using agrochemicals is increasing, especially glyphosate-based herbicides (GBH). The application of toxic chemicals as pest control in food crops carries a risk to human safety. Therefore, it is important to create a sensor for detection through Localized Surface Plasmon Resonance (LSPR) by utilizing anisotropic gold nanoparticles (AGN) to detect the presence of GBH contaminants in the form of malathion and temephos, with a detection level as low as three-part per million (ppm). AGN-based LSPR is successfully synthesized through an experimental technique using the Seed Mediated Growth Method (SMGM). The UV-Vis response showed two strong absorbances with a peak occurring around 500 to 600 nm, the peak within the transverse surface plasmon resonance range (t-SPR) corresponds to one aspect, while the peak within the spectral range extending from 700 nm to 900 nm corresponds to another aspect, namely Longitudinal Surface Plasmon Resonance (l-SPR). Anlysis of the FESEM photograph shows a structure consisting of two particles with different shapes, pentagonal pyramids and a bone shape. Pentagonal pyramids joined with a surface density of 64.43 ± 1,53 % and bone shape of 32,46 ± 1.53 %. This characterization shows strong and distinctive optical resonance in the near-infrared visible light spectrum, which is very suitable for LSPR sensors. It is necessary to fabricate an LSPR sensor device capable of detecting the presence of GBH by testing sensitivity, stability and repeatability. The sensitivity test results were evaluated by varying the synthesis time and concentration of contaminants in the AGN growth solution. It confirmed that the AGN-based LSPR sensor has a promising potential for GBH residue detection.
Design, simulation, and optimization of portable atmospheric water generator using vapor compression refrigeration system
Authors: Ayodha Ajiwiguna Tri , Kirom M R , Suprayogi
Published: December 2023

In this study, the conceptual design and optimization of a portable Atmospheric Water Generator that uses a vapor compression refrigeration system is investigated. The cooling system is needed to decrease the temperature of the ambient air to below its dewpoint. The cooling capacity of the vapor compression refrigeration system was 0.3 kW. The airflow velocity was then varied from 1.5 m/s to 5 m/s with an increment of 0.5 m/s. The diameter of the opening input feed air is 5.7 cm. The ambient air was assumed at 30 °C and 80% of relative humidity as the feed for the system. The results show that the maximum water production was 0.285 L/h which was produced by the air velocity at 2.5 m/s
Classification of Normal and Abnormal Heart Sounds Using Hjorth Features and LSTM – RNN Algorithm
Authors: Rizal A , Fauzi H , Wulandari D R , Zamhari D K
Published: December 2023

The stethoscope is a commonly used medical device for diagnosing a patient’s condition by listening to their heartbeat. This diagnostic technique is known as auscultation, where each heart sound heard through the stethoscope has a distinct pattern that depends on the person’s heart condition. Researchers have developed computational methods that automatically analyze heart sounds to overcome the subjective nature of auscultation. In this study, we utilized the Hjorth method for feature extraction and the Long Short-Term RNN algorithm for classifying the normal and abnormal heart sounds. With 100 epochs, two layers of LSTM-RNN, and one layer of Dense, the classification accuracy for distinguishing normal and abnormal sounds reached 71.95%. This research aims to contribute to the development of an accurate system for detecting normal and abnormal heart sounds.
Electrically activated zeolite for reducing seawater salinity
Authors: Wibowo Edy , Aditya Rahman , Ulya Naily , Rokhmat Mamat , Marwoto Putut , Sutisna
Published: December 2023

We have electrically activated natural zeolite (Clinoptilolite) to enhance the reduction ability of zeolite for seawater desalination. Activation was carried out using a voltage source of 8 V and 12 V for 0, 5, 10, 15, and 20 minutes. A salinometer is used to measure changes in seawater salinity after being treated with electrically activated zeolite. The salinity reduction value is expressed in percent reduction (η), which is measured every hour for 24 hours. Zeolite activated at a voltage of 8 V for 15 minutes was able to reduce seawater salinity by up to 5.7%. Zeolite activated at 12 V for 10 minutes was able to reduce salinity by up to 7.2%. Both values are higher compared to zeolite, which was thermally activated at 225 °C for 3 hours (4.8%). We have succeeded in increasing the adsorptivity of natural zeolite through a much shorter activation process with higher reduction efficiency compared to using thermal treatment, which takes up to 3 hours. Activation of zeolite using electric current can be a preferential option because it is carried out in an uncomplicated process in a brief time and does not involve the use of chemicals that have the potential to damage the environment.
Metaverse-based Water Level Simulator for the Festo MPS PA Workstation
Authors: Putawa R A , Wardana A N I , Tenggara A P
Published: December 2023

The compact workstation developed by Festo represents a bench-scale model for facilitating industrial process simulations in the laboratory and enabling students to study common control systems used in the industry directly. The latest development of the virtual Festo modular production system (MPS) process automation (PA) workstation has yet to be able to provide open access. In the virtual world, it needs interaction between the user, which still needs to be accommodated. This research attempts to develop a metaverse-based simulator of the Festo MPS PA workstation using the Roblox platform. This research focuses on designing a level control system, considering aspects such as the 3D model, control interface design, the implementation of system equations and controller algorithms, and the system’s response. The findings reveal Roblox’s potential in developing a virtual educational ecosystem for engineering, demonstrated by the design of an open-loop system with an average error of 11.4% compared to a real system. In the case of a closed-loop system with interactive PID control, the system response exhibits an average error of 8.03%.
Investigation of Performance Estimation Methods Validity of Thermoelectric Module
Authors: Ajiwiguna Tri Ayodha , Azizah A N , Suhendi A
Published: December 2023

The thermoelectric cooling system is now widely used in small-capacity applications. This system is designed to remove the heat by using a thermoelectric module thus the selected object can be maintained at the required range of temperature. The performance of the thermoelectric module system can be estimated by using the information from the technical datasheet issued by the manufacturer. Two commonly used methods for estimating the cooling capacity of the system are performance curve and energy balance. This study aims to investigate the accuracy of those two methods compared with the experimental results. The experiment was performed by maintaining the hot side temperature at 50 °C. To estimate the cooling capacity, the heat conduction on the stainless-steel block was calculated. The results showed the estimated cooling capacity of the thermoelectric system was up to 48% and 10.1% higher than the experimental result by using energy balance and performance curve methods, respectively. It implied that the performance curve method is more accurate than the energy balance method.
Design of mechanical digitalization automatic water level recorder for river water level monitoring
Authors: Soehartanto T , Radhy A , Alwi A M I
Published: December 2023

The Welang River Pasuruan has an Automatic Water Level Recorder (AWLR) tool that measures water levels at that location. This tool operates using mechanical movement to rotate the roller on the AWLR, causing the float to move up and down. This movement results in ink marks on the water level validator paper. The recorded water level data is then processed into an Excel chart. This study aims to digitize the AWLR tool so that the monitoring and calculation of the water level is more precise and can be monitored in online. The water level detector will work in real time using a rotary encoder sensor and data will be sent to database and monitor water level monitoring through a series of data processing which later the data will be sent via MiFi. The method of testing the 2-component connecting system is the accuracy of reading the water level and the accuracy of sending data. The results will be displayed every 1 second on the monitoring dashboard and a standard deviation of 0.0002792 and an error of 0.43% is obtained which indicates the accuracy of the reading is quite accurate and real time.
Automation System Architecture of pH Neutralization Process in Batik Wastewater Treatment Plant
Authors: Nazuwatussya’diyah  , Ekawati E , Pradipta J , Yulia E
Published: December 2023

Batik production in home industries needs support wastewater treatment in a limited space. Therefore, a modular-type, lab-scale wastewater treatment plant (WWTP) with a capacity of 87.75 liters and a dimension of 1.5 m × 0.75 m × 1 m has been constructed. The WWTP combines three significant processes: equalization, neutralization, and adsorption. This study focuses on the monitoring systems for the pH neutralization process. The system uses four microprocessors in a Master/Slave architecture and the I2C protocols for data communication between processors. The measuring instruments include pH, temperature, turbidity, and flow rate sensors. The actuators consist of submersible and peristaltic pumps. The operating range of pH, temperature, turbidity, and flow rate sensors are 0–14, 25–81.44℃, 0–3000 NTU, and 6.49–20.84 ml/s respectively. The pumps work in Pulse Width Modulation (PWM) mode with an operating range of 125–225 PWM. All sensors and actuators operate linearly within the operating range with a correlation coefficient of 0.97–1.
Development and Economic Analysis of Bioethanol Production from Palm (Arenga Pinatta) Biomass with Ionic Liquid Pretreatment Using SuperPro Designer Software
Authors: Maulidin I , Utami A R I , Sugiwati S , Darus L , Mel M , Maryana R
Published: December 2023

Bioethanol has many functions both as a chemical, food and as a source of energy. The development of bioethanol production is currently leading to the residue of the main product. So that in this study the biomass of arena or Arenga Pinatta was used with a large availability of waste. Therefore, a performance and economic analysis was carried out in the production of bioethanol from palm biomass with ionic liquid (IL) using SuperPro Designer (SPD) Software. As a preparatory stage, the process of testing the characteristics of the biomass is carried out to obtain the most optimal composition of palm sugar in bioethanol production. After simulating the conditions according to the experimental process on the most optimal palm biomass composition, it was found that the most optimal Ionic Liquid (IL) and biomass ratio was at 0.5 g/g with the ethanol concentration obtained at 90.6 g/L at 13 hours which corresponds to theoretical yield of 96% conversion of biomass to ethanol. Meanwhile, the production of ethanol in a factory for energy can minimize the price of ethanol by 30% from the initial price. Thus, with the abundant availability of biomass, bioethanol production with aren biomass has the potential to be developed in Indonesia
Design of Automation and Monitoring Systems for Filling Mineral Water Tanks Based on Android Applications
Authors: Putu Eka Widya Pratama I , Lailatul Mardiyah Yusvita
Published: December 2023

The PURE “ARH” refillable drinking water filling station located on Arief Rahman Hakim Street, Klampis Ngasem, is still not very practical and efficient. This is because the machine is still manual, operated by pressing a manual button to switch it on and off, and requires visual observation until the water container is filled. As a result, this creates uncertainty in the volume of water being filled. Therefore, in this research, an automated prototype and monitoring system for filling mineral water tanks based on an Android application were developed. The use of an HCSR04 ultrasonic sensor for mineral water tank detection at approximately 20 cm and an FS400A water flow sensor to determine the volume of water filled is employed. Subsequently, the results of mineral water tank’s water filling can be monitored, displaying the number of fillings and the volume of water filled, which are then sent to the Android application. Three mineral water tank sizes are used as samples: 5 liters, 15 liters, and 19 liters. The filling process allows configuration of the filling volume through the Android application, allowing refillable drinking water station owners to set their desired set points based on the mineral water tank’s capacity. The validation results of the FS400A G1 flow sensor shows an average error of 1.35%, resulting in an accuracy level of 98.65%, while the HC-SR04 ultrasonic sensor has an average error of 1.31% with an accuracy level of 98.69%. As for the testing of the filling mineral water tanks control system using the on-off control method, in this research, it has been successfully achieved with an error rate of 0.9% for a 5-liter set point, 1.3% for a 15-liter set point, and 2.4% for a 19-liter set point. From these results, it can be concluded that the water-filling control system operates effectively, as the actuator functions properly with a logic state of one (1), and once the set point is reached, the actuator turns off with a logic state of null (0).
Deep learning and acoustic approach for mechanical failure detection in industrial machinery
Authors: Qurthobi Ahmad , Maskeliūnas Rytis
Published: December 2023

Research into acoustic signal-based failure detection has developed into a subject that has attracted the attention of many researchers in recent years. Acoustic signal data collection can be performed without having to interrupt or stop the operation of the machine to be inspected. Therefore, it is very beneficial for the development of nondestructive testing and predictive maintenance. In this study, a collection of pump sound recordings that are part of the Malfunctioning Industrial Machine Investigation and Inspection dataset, known as the MIMII dataset, is used as test material. Several deep learning algorithms such as long short-term memory (LSTM), gate recurrent unit (GRU), autoencoder, and convolutional neural network (CNN) were involved and compared to determine their ability to detect failures. Based on the training results with 300 epochs and a learning rate of 10−6 it was found that CNN produced the classification with the highest accuracy compared to the other algorithms. In addition, the CNN algorithm is also capable of performing classification amidst the problem of imbalance in the amount of data.
Analysis of Pattern Recognition of Disorders in Children Using Artificial Neural Network (ANN) and Decision Tree Methods: A Case Study of Disorders in Children with Disabilities
Authors: Darmawan D , Rosdiana E , Andiani L , Muchtar F U W , Anggraeni D A , Ginting W , Maulana B N
Published: December 2023

In this era of globalization, technological developments in the field of digital information have greatly affected services in the health sector in healing and meeting public satisfaction. Digital technology-based services are needed by children with disabilities so that they can be given superior and effective treatment. Digital technology services are used as a clustering and pattern recognition system using Artificial Neural Network (ANN) and decision tree. The data collection process is done by taking a video of a child walking on a track in the form of manila cardboard whose feet have been colored with food coloring so that the footprints can be seen clearly. After that, Artificial Neural Network (ANN) and decision tree have two stages, namely the training stage and the testing stage. The training stage is carried out using 20 respondent data from children who walk. The testing stage is carried out using three new data that are different from the training stage. From these two methods, a high accuracy rate of 99.91% is obtained for ANN and close to 100% for decision trees.
The inconsistency of land use along the 10 m river buffer of East Kalibaru, Jakarta
Authors: Prayoga G , Siahaan L , Firmansyah F S , Mufawwaz T A , Liyantono  , Supalal Y A , Rahmawati  , Samputra N R A R
Published: December 2023

The East Kalibaru River extends from Depok/South Jakarta to northern Jakarta. Visually, the riverbank is crowded with settlements, even though the Ministerial Regulation of Public Works and Housing Number 28 Years 2015 has regulated the River Boundary Line, where rivers must have a 10 m wide buffer zone. This study aims to reveal the inconsistency of land use along the 10 m river buffer of East Kalibaru using a quantitative and qualitative descriptive approach using spatial data, river hydrology, and river water quality status for the analysis process. The river was categorized into three segments (upstream, midstream, and downstream). Using ArcGIS, delineation was carried out along the 10 m river buffer of East Kalibaru and then overlaid with land use data, resulting in land use type suitability. Land use suitability was evaluated by calculating the percentage of land area based on compliance with the regulations. The inconsistency of land use along the 10 m river buffer of East Kalibaru amounted to 46.25% (26.21 ha). The most significant land use inconsistency occurred in the midstream segment (68.24% or 13.23 ha), whereas the best was found in the downstream segment (26.54% or 4.36 ha). Residential and office & trade land use types dominate the inconsistency of land use. Residential areas are mainly found in the midstream segment, with an area reaching 47.42% or 9.19 ha. The government should gradually be disciplined the 46.25% inconsistent area because the river buffers must have 100% suitable land use to optimize the function of the river boundary.
Comparative review of Smart City from an urban planning perspective in Johor Bahru City and Petaling Jaya City
Authors: Bakhtiar I S , Samsudin N A
Published: December 2023

Smart cities are of great importance globally, and Malaysia recognizes this importance. The Malaysian government has launched various initiatives to encourage the ‘Smart City’ such as the framework (Malaysia Smart City Framework), blueprints, action plans, and standard, the Malaysian Standard for Smart Cities. The outlines the definitions, key principles, and strategies for adopting smart cities in Malaysia’s development. This study aimed to contribute to the understanding of smart city development in Malaysia and provide valuable insights for policymakers, urban planners, and researchers in their efforts to create sustainable and efficient cities. The objective of this study is to compare the approaches and outcomes of smart city development between Johor Bahru City, Johor, and Petaling Jaya City, Selangor. This has analyzed and comprehended the trends in various features of smart city development of the cities. The study found that Johor Bahru City is making more efforts to develop as a smart city through effective governance and strategic planning for short-term and long-term goals same as Petaling Jaya City but focuses more on a one-stop center which promotes community togetherness with the governance. Nevertheless, at the regional level, Johor Bahru City has the Iskandar Malaysia Smart City Framework promoting Sustainable Smart City Vision, followed by the Johor Smart City Blueprint at the state level, and implemented via blueprints at the local authorities, which sets it apart from Petaling Jaya City. Both cities have well-planned smart city initiatives that integrate technology, energy, and the environment, including support for smart city components that suit their needs. Despite facing challenges, the city serves as a model for smart and sustainable development.
Autonomous Wheelchair for Indoor Navigation
Authors: Chandana H R , Deepak M , Padanad Megha Anil , Satish B A
Published: December 2023

Wheelchairs are a very beneficial tool for commuting used by physically challenged people. But not everyone can make the wheelchair move on their own and often depend on help for movement of the wheelchair, making them dependent on constant support for every movement. Even when the physically challenged individuals are indoors, they end up being the dependent. The idea being proposed in the paper is develop a wheelchair that can make the movement of the wheelchair either automatic with inbuilt indoor navigation for easy navigation along with voice-based commands and joystick control for easy control. The wheelchair proved to be extremely beneficial for the physically challenged, at a relatively low cost.
Predictive analysis of Low power DC loads in Residential Buildings
Authors: Satish BA , Usha P
Published: December 2023

There has been a constant rise in use of loads powered from direct current (DC) among the residential loads. In the traditional Alternating Current (AC) grid voltage undergoes conversion multiple times before it reaches the loads requiring DC, which leads to substantial power loss in the converters. Implementation of a DC grid in the residential buildings can reduce the losses caused due to the conversions. The paper presents a prediction model for domestic low power DC loads which can be powered from a battery. The data of usage of the load as well as the data of the parameters on which the load usage is dependent on was collected over a period of a year. This data was fed to a Random forest-based machine learning algorithm to predict the usage of the loads in future. The state of charge (SOC) of the battery used to power the loads was compared with the load prediction to decide whether the load can be powered from the available power in the battery or not. This allowed the system to decide in real time on the source to be used to power the DC loads and providing the users a choice to change the load usage time in order to prevent power from being drawn from the AC grid.
Dynamic Modelling and Current Control for Switched Reluctance Motor Drives in Electric Vehicles
Authors: Ibrahim Muhammed A , Alsammak Ahmed Nasser B
Published: December 2023

The inherent features of the Switched Reluctance Motor (SRM) make it a promising applicant for further exploration and examination in various industrial sectors, to mention but a few electric vehicles. The mechanical development of this motor is characterized by its simplicity and cost-effectiveness. Including current controllers within an SRM drive control system is of utmost importance due to their substantial influence on drive performance, dynamic response, and noise and vibration performance. This study aims to improve the SRM drive system to achieve reliability and efficiency. A complete SRM drive system is designed, constructed, and evaluated to accomplish this objective. The contribution of this study is that the consequence of the current control band of hysteresis current control (HCC) on the phase current has been intensely investigated on high-frequency torque ripple, average torque and average switching frequency. This investigation has been performed simultaneously with soft-hysteresis current control and hard-hysteresis current control. Simulation results proved that the soft HCC gives the best results. A trade-off between switching frequency and high-frequency torque ripple has been performed based on choosing the best current control of the proposed model.
Maximum Torque per Ampere Technique for Switched Reluctance Motor Drive
Authors: Ibrahim Muhammed A , Alsammak Ahmed Nasser B.
Published: December 2023

Numerous researchers have investigated switched reluctance motors (SRMs) as a competitor to other electrical motors for usage in electric and hybrid vehicle appliances. SRMs are fault-tolerant and have a broad operating speed range. However, they have numerous drawbacks, such as high nonlinearity in machine models, complex control, and torque ripple. This study aims to improve the SRM drive system to attain maximum torque per ampere in a wide speed range. In the design and control of SRMs, maximizing torque per ampere (MTPA) is a crucial objective. MTPA refers to the strategy of achieving the maximum possible torque output for a given current input (amperes). This is essential for enhancing the efficiency and performance of the motor. The paper focuses on achieving MTPA in an SRM drive system-based commutation angle control. Utilizing a bacterial foraging optimization algorithm (BFOA), the suitable commutation angles at each operation point are determined. The intended technique is straightforward to realize and does not require complex algorithms. Simulation comparisons on an 8/6 SRM are also presented to validate the intended control technique. The results indicate that the MTPA has been enhanced by 6.961% compared to the conventional method.
Smart Shopping Trolley with Automated Billing
Authors: Venkata Sai Prasad K. , Karthik K. , Charan Kumar O. , Prathiksha B S , Salimath Kavana
Published: December 2023

In today’s context, people prefer buying groceries from supermarkets/hypermarkets. However, locating essential items in a supermarket can be time- consuming, and customers often have to wait in long billing queues to complete their purchases. The COVID-19 pandemic has further complicated matters, as maintaining social distance during the billing process is challenging. To address this significant challenge, this research proposes a smart trolley based on the Internet of Things (IoT) with an advanced billing system, aiming to make shopping easier, more secure, and to eliminate the need for standing in long queues. The proposed system comprises a smart trolley equipped with an LCD display, barcode scanner, and a Raspberry Pi. This innovative model aims to revolutionize the shopping experience by streamlining the process and mitigating administrative issues. The proposed framework holds promise for widespread implementation in real-world scenarios.
Thermal Power Plant Pollution Monitoring and Control using Internet of Things
Authors: Manoharan Mahalakshmi , Padma S , Madhubalan S , Arunkumar S , Kesavan D
Published: December 2023

In our day-to-day life, environmental degradation and global warming are essential factors to consider. These problems were caused due to the contamination of water, air, and soil with the waste generated by industries. The pollutants level generated by the industries to be measured and controlled by central and state pollution control board. The air pollutants are the major cause for the deterioration. The existing pollutant monitoring system are complicated, inaccurate, unreliable, delayed intimation and less efficient. Hence in mettur thermal power plant, the internet of things-based pollutant gas monitoring system has been implemented. This system consists of numerous gas sensors, Arduino UNO controller, ESP8266 Wi-Fi module, ubidots server and alarm. The pollutants measured are carbon monoxide (CO), suspended particulate matters (SPM), sulphur oxides (Sox), nitrogen oxides (Nox) in air. When the pollutants level of industry is crossed the limit, the pollution control board has been intimated the exact location of the industry through internet. The pollution control board can automatically send alert SMS and email to the respective industry. This system is suitable for the recent technology industrial internet of things. The electrostatic precipitator has been installed for pollutant control. It is proved that the proposed system is a very good replacement for the conventional monitoring system done by the human. It is acted as user friendly interface for the operation of the system and is reliable. The system has attained improved pollutant control, increased stability, and consistency of the power plant and finally the safety of the employees working in the power plants and mine areas.
Microgrid Protection Challenges and Solution
Authors: Modi Sangeeta , Usha P
Published: December 2023

Microgrids are embryonic as inspiring solution to the various concerns such as environmental, economic, depletion of the resources for the fuel availability and power mismatch. Microgrids are going to become one of the core components of the upcoming power system. So, it is essential to understand various issues and challenges in microgrid. Power management, constant voltage and frequency, control of various distributed generators and Protection of the microgrid are major areas of concern. Not much work has been done on the protection side of the microgrid. Detecting fault and obtaining the appropriate setting of the protective gear for unconventional topology of the microgrid is very challenging. In this work a solution has been proposed and implemented in microgrid controller (MGC) for fault detection and classification in a microgrid. Effectiveness of proposed method is tested in MATLAB /SIMULINK environment.
Optimal Power Flow Management in Microgrids using Distributed Energy Resources
Authors: Nagananda R , Gopiya Naik S
Published: December 2023

The effective and stable functioning of microgrids using distributed energy resources (DERs) is greatly dependent on ideal power stream management. To get the optimal power flow in microgrids, this study provides an inquiry into the use of cutting-edge optimization techniques. To fulfil load demand and consider DER requirements, system running costs must be kept to a minimum. The microgrid integrates a variety of distributed energy resources, including solar photovoltaic systems, wind turbines, and energy storage systems. The research examines several optimization strategies, such as mixed-integer programming, evolutionary algorithms, and linear programming, to decide on the best DER dispatch and scheduling. The findings give important information on how to efficiently use and manage distributed energy resources to raise the performance and resilience of microgrids.
Design of Switched Capacitor Multilevel Inverter with Selective Harmonic Elimination
Authors: Buddinni Chaitra D , Usha P
Published: December 2023

In this paper, Selective Harmonic Elimination (SHE) technique is applied to control multilevel inverters that can be used to eliminate the low order dominant harmonics. This is considered a low frequency technique, in which the switching angles are predetermined based on solving a system of transcendental equations. Newton Raphson is one among the heuristic techniques utilised for selective harmonic elimination. The proposed SHE strategy is simulated along with Sinusoidal Pulse Width Modulation (SPWM) technique and the harmonic distortions are measured and compared for both techniques in MATLAB/Simulink software.
Enhancing industry 5.0 goals through laser based additively Manufactured High-Performance Metals
Authors: Nyamekye P , Westman S , Tepponen V
Published: December 2023

In the current industry 4.0 (I4.0) and emerging Industry 5.0 (I5.0) eras, the integration of digitalization and sustainable goals is driving nature-centric and human-centric products. The production of these products are also creating digital supply chain that boosts agility and resiliency in operations, management, and supply chain interlinks. Additive manufacturing (AM), an element of I4.0, for instance, offers an integrated connection of all process steps and value chains using computer-based designing, data-driven simulations, cloud-based processing, storing, and managing software along seamless digital threads to create agile and resilient supply chain. The integration of AM and other I4.0 technologies enables greater flexibility offering intrinsic sustainable, human-centric and resilience advantages. Laser based additive manufacturing (LBAM), one of the subcategories of AM, offers opportunities to manufacture new intricate and conventionally impractical metal product designs in an ecological and economic competitive stance. High performance metals (HPMs) suited for high-stress and corrosive demanding applications are tough to machine and prone to thermal cracking in case of welding. Conventionally difficult and lengthy to manufacture yet unavoidable HPMs such as nickel alloys and titanium alloys are effortlessly possible via LBAM. Different industrial sectors that utilize these grades of metal alloys continue to adopt AM for the offered design flexibility for achieving goals such as customization, lightweight, on-demand manufacturing, raw material efficiency and cost saving. This study uses literature review and manufacturing case studies to demonstrate the flexibility and digital nature of LBAM towards I5.0 goals. The study objectively highlights the promising responsiveness of AM in the eventuality of supply disruptions that may be caused by sudden changes. The novelty of the study lies in the pragmatic emphasis on the potentials of LBAM and paired I4.0 technologies in revolutionizing the industry towards industry 5.0 goals. The study shows how I4.0 elements can be paired to enable operational efficiencies, lower carbon emissions, and foster sustainability in promoting I5.0 transformation. This study offers a fundamental understanding of the role of LBAM in the advancement of sustainability, human-centricity, and resilience.
Preliminary study of knowledge transfer aspect in the creation of a framework for education and training of digital manufacturing technologies
Authors: Piili H , Huusko A , Kurvinen A
Published: December 2023

Digitalization is changing the industry. As this change accelerates its speed, it also requires a transformation process where knowledge transfer between industry and research institutes play a significant role. There is a need to be more fluent, flexible, and efficient in order to get the latest research results into industrial implementation as quickly as possible. The challenge in knowledge transfer is that its speed in the current stage is too slow compared to the speed of development and changes required by digitalization of traditional manufacturing industries. The motivation for this study is the gap in knowledge transfer. One emerging digital transformation is the establishment of modern digital manufacturing technologies, e.g., additive manufacturing (AM). There are different approaches to supporting the industry in this transformation. Knowledge transfer can happen, for example, through education (e.g., master students) and industrial training, but also the fluent transfer of the latest research results from research institutes to companies is needed. University education needs to support the requirements of the manufacturing industry by providing future experts with skills to smooth the transformation process and bring novel technology applications, such as AM, to industrial-scale use. The article discusses how university education can support future competence-building in the industry. Similar needs are also present in industrial training, which universities often provide. Both education and training need to be improved from fundamental approaches to explain how this new knowledge should be created, i.e., how knowledge transfer happens most efficiently. The outcome of this article is the basis of the framework for education and training of digital manufacturing technologies by using modern learning methods and tools. More detailed pedagogical and knowledge transfer models can be developed and applied when this framework is created.
Virtual Reality-Based Training in Additive Manufacturing: Developing a Service Concept that Adapts to Company-Specific Requirements
Authors: Huusko A , Susi J , Parchegani S , Hosseini H , Tuomisto A , Helin A , Piili H , Salminen A
Published: December 2023

Additive manufacturing (AM), commonly known as 3D printing, has vast amount of technological opportunities, but it also necessitates specialized expertise among its specialists, adopters, users etc. As AM continues to demonstrate its potential and has high growth rates in fields of its use, applications, systems etc., the importance of AM education and training becomes increasingly evident. This paper serves as a preliminary study outlining a novel training concept for industrial AM training including microlearning units and conducted in virtual reality, focusing on the accessibility and flexibility of users. The concept has been developed as part of the ongoing industrial training project. Microlearning and virtual tool-assisted training methods offer effective and agile approaches to enhance the continuous learning of new industrial skills, enabling companies to keep pace with evolving technologies. These tools facilitate extensive customization of training, making company-specific training even more crucial for effective skill development and knowledge transfer. The design of this training concept leverages the user story mapping (USM) method, enabling a deeper understanding of company-specific requirements and needs concerning additive manufacturing training. Moreover, through questionnaires and interviews conducted during the USM process helps identify technology readiness levels (TRLs) of companies in relation to their AM adoption. Measuring TRLs provides valuable insights into the technical maturity of companies regarding additive manufacturing, as readiness levels tend to vary significantly among different organizations. The preliminary framework provided serves as a foundation for designing a modern training concept that cater to the unique requirements of different companies, fostering their successful adoption of AM technologies.
Industrial IoT system for laser-wire direct energy deposition: data collection and visualization of manufacturing process signals
Authors: Martikkala Antti , Wiikinkoski Olli , Asadi Reza , Queguineur Antoine , Ylä-Autio Aapo , Flores Ituarte Iñigo
Published: December 2023

Industry 4.0, also known as the Fourth Industrial Revolution, is a term used to describe the current trend of automation and data exchange in manufacturing and other industries. The Internet of Things (IoT) plays a crucial role in Industry 4.0 by connecting devices, machines, and products to the Internet and enabling real-time data exchange. Moreover, additive manufacturing is a key developing manufacturing technology in Industry 4.0. New technologies such as data analysis with Artificial Intelligence and machine vision are widely used in optimization. However, in a lab environment, these technologies depend on the data collected from the process. For such work, the researchers should be able to focus on their core research rather than on the development of infrastructure to collect and analyse the data. This research presents an open software and hardware IoT solution to monitor a laser wire direct energy deposition system installed in a cartesian type 3-axis machine tool. The IoT solution adopts three open-source tools for core issues, such as 1) interoperability, flexibility, and availability; 2) data storage; and 3) data visualization of sensor data and manufacturing process signals. The system architecture is based on one or more edge devices connected to sensors and forwarding their data toward a local API endpoint. The endpoint is created with Node-RED, an open-source visual flow-based development tool for IoT data. Node-RED forwards the data to an open-source InfluxDB database. Finally, the data is visualized with an open-source Grafana application. The system is prototyped, designed, implemented, and tested in a lab environment to monitor a laser-wire direct energy deposition process. The significance of such a flexible IoT data collection system for research and development projects can be integral. Thus, providing savings in time and money can substantially speed up the development of new technologies where the value arises from the sensor data and its analysis.
In-situ monitoring for PBF-LB/M processes: Does multispectral optical tomography add value in recognizing process deviations?
Authors: Becker Tina , Breese Philipp P , Metz Christian , Altenburg Simon J
Published: December 2023

Laser powder bed fusion of metallic components (PBF-LB/M) is gaining acceptance in industry. However, the high costs and lengthy qualification processes required for printed components create the need for more effective in-situ monitoring and testing methods. This article proposes multispectral Optical Tomography (OT) as a new approach for monitoring the PBF-LB/M process. Compared to other methods, OT is a low-cost process monitoring method that uses long-time exposure imaging to observe the build process. However, it lacks time resolution compared to expensive thermographic sensor systems. Monochromatic OT (1C-OT) is already commercially available and observes the building process layer-wise using a single wavelength window in the NIR range. Multispectral OT (nC-OT) utilizes a similar setup but can measure multiple wavelength ranges per location simultaneously. By comparing the classical 1C-OT and nC-OT approaches, this article examines the advantages of nC-OT (two channel OT and RGB-OT) in reducing the false positive rate for process deviations and approximating maximum temperatures for a better comparison between different build processes and materials. This could ultimately reduce costs and time for part qualification. The main goal of this contribution is to assess the advantages of nC-OT compared to 1C-OT for in-situ process monitoring of PBF-LB/M.
Towards data driven quality monitoring: alignment and correlation of photodiode-based co-axial melt pool monitoring signals to part quality in laser powder bed fusion
Authors: Reijonen Joni , Revuelta Alejandro , Nagarajan Hari P.N.
Published: December 2023

Online quality control of advanced manufacturing processes often utilize process monitoring as a qualification method to reduce or eliminate time consuming and costly destructive and non-destructive tests. The need for process monitoring based qualification becomes more apparent with the advent of laser based additive manufacturing for complex geometries and lot-size-one production. However, the usability of the process monitoring solution heavily relies on the accuracy of the established alignment and assignment of process signals to specific part and defects herein. This research proposes a data fusion strategy for data pre-processing to structure and align multi-source sensor data for improving correlation accuracy in process monitoring. A laser powder bed fusion system equipped with a photodiode-based co-axial melt pool monitoring is used for the study. First, the monitoring system collects photon emission data from the melt pool using photodiodes with high frequency (>100 kHz) which are aligned spatially and temporally using position data (xy-coordinates) of the galvanometer scanner and the laser ON/OFF signals. Next, a clustering approach is used to assign each photodiode signal with the individual parts on the build platform. Finally, correlation between melt pool monitoring signals and part level porosity is studied using micro-computed X-ray tomography (μCT) from a build job containing parts produced under varying process conditions.