bluuebunny/crossref_metadata_2025 huggingface dataset:
Proposed maintenance policy using reliability centered maintenance (RCM) method with FMECA analysis: A case study of automotive industry
Authors: Dzulyadain Harits , Budiasih Endang , Dwi Atmaji Fransiskus Tatas
Published: March 2021

PT XYZ is one of the companies engaged in the automotive industry, especially in the motorcycle industry that produces spare parts on motorcycles. One component made by PT XYZ is Guide Comp Level K1AA. The problem in the company is one of the machines to produce the Guide Comp Level K1AA component, which is a Press machine that has a high frequency of failure. The Press machine itself consists of electrical and mechanical systems that each system consists of sequential subsystems as many as 6 subsystems and 10 subsystems. By using risk matrix, obtained two critical subsystems namely brake and trigger. Then the analysis of failure mode, effects and criticality analysis (FMECA) was carried out with output in the form of risk priority number (RPN), obtained that the selected critical subsystem is the brake. Using the reliability centered maintenance (RCM) method, then obtained the maintenance policy for the brake critical subsystem are 2 scheduled on condition task with interval time is 2.55 months and 2 scheduled restoration task with 5,394 months. The proposed maintenance policy also decreases the total maintenance cost for the critical subsystem brake up to 25% from existing maintenance costs.
Measurement and analysis of productivity in the process of raw material shearing sheet by using matrix objective
Authors: Sayuti Muhamad , Pratiwi Annisa Indah , Neni Triana N.
Published: March 2021

One improvement that can be done is to increase the productivity of the company. Important productivity measurement and analysis was conducted to determine the level of efficiency and effectiveness of resource use. These measurements were done on the Raw Materials Inventory at Raw Materials Shearing process. By measuring the productivity of companies can see achievements that have been achieved and as a basis for planning and improvement of section Raw Materials Inventory. Productivity measurement is done using methods Objective Matrix (OMAX) and Cause and Effect Analysis. January to December 2019 fluctuated productivity. The increase in productivity index in the period from February, April, June, September, and November 2018. While the decline in productivity index occurred in January, March, May, July, August, October, and December 2019. Increased productivity is the highest in the period of November 2019, by performance indicator value of 1.49 and the lowest productivity decline in the period of August 2019, with a value of 0.60. And performance indicator criteria that need to be improved to achieve better productivity is the criteria one, three and four, the criteria Raw material shearing, shearing time, and the result of shearing.
Determination of risk level, remaining life prediction, and risk based inspection planning based on API 581
Authors: Agistina Alia , Budiasih Endang , Pramoso Aji
Published: March 2021

Electricity can be produced through several types of plants, one of which is Geothermal Power Plant (PLTP). One company that manages Geothermal Power Plants in Indonesia is PT Indonesia Power. In processing geothermal into electricity, companies need machines that work well in any condition, one of which is a separator machine that functions as a separator of geothermal steam with impurities. To keep the separator machine working properly, proper inspection is needed. Inspections can be done by a variety of methods, but inspections of separators should use a risk-based inspection method. Therefore, the study was conducted by applying a risk based inspection method based on API 581 Second Edition to determine the level of risk, the remaining life of the machine, and the planning of inspections (intervals and inspection techniques) on the machine. The level of risk for all separator units is medium high with a risk category of 1E, which has a low probability of failure and high failure consequences. The estimated age of the remaining machines working according to their functions based on research for unit I is 25 years, for unit II 13 years, and for unit III 18 years. This affects the inspection intervals in each unit, unit I should be inspected every 6 years, unit II is inspected every 3 years, and unit III is inspected every 4 years with a thorough inspection and thickness measurement as an inspection technique.
Differences in braking time in symmetric and asymmetric tire tread pattern type
Authors: Partono  , Kusuma Fuad Indra , Sumarli  , Ismail Hasan
Published: March 2021

Identification of tire tread type characteristics needs to be taken into consideration when choosing a tire. The accuracy of choosing a tire will help ensure the safety of the rider. The identification procedure is by comparing symmetrical and asymmetrical 1-way direction tires. The parameter is the braking time needed for the vehicle to stop. The braking time required by asymmetric type 1-way direction tires is shorter than symmetrical type. So, motorists are advised to choose asymmetric type 1-way direction tires to get a shorter braking time.
Pile defect quality control analysis on construction company in East Java
Authors: Widiyawati Sri , Lukodono Rio Prasetyo , Lustyana Astuteryanti Tri , Juliawati Luciana
Published: March 2021

A production process has a possibility of product defects; the types of defects commonly found in pile products are porous concrete defects, dented joint plate defects, pile dimensions deviation defects, etc. The defect of the product needs to be controlled because it can cause losses to the company. Therefore, in this study, data processing was conducted on pile defect products using statistical process control. An analysis was then performed using the Pareto Chart to determine the types of defects that occur most often. After that, identifying the problems causes that occur in terms of man, machine, method, materials, money, and environment by using fishbone diagrams; so that recommendations for improvement can be given to the company. The results showed that, based on the Pareto principle, 80% of the defects types that occur include the type of porous concrete defects, the type of dented sheath plate defects, and types of joint plate dimension defects. The type of defect with the highest frequency is a porous concrete defects type. Recommendations for improvement that can be given include providing training to workers, maintaining machinery, improving product quality, and providing alternative electrical energy sources.
Evaluation of the standard deviation of droplet speed on grey-scale technique of DoD inkjet printer
Authors: Oktavianty Oke , Haruyama Shigeyuki , Ishii Yoshie , Kyoutani Tadayuki , Darmawan Zefry , Novareza Oyong , Sirait Marudut
Published: March 2021

The print quality of an inkjet printer is determined by the quality of the droplets. The droplet quality of a DoD inkjet printer is affected by speed variation between the droplets that generated from different nozzles. The effectiveness of a preliminary vibration using the W waveform design to generate spherical droplet without satellite and ligament has been denoted from previous studies. The waveform design considered to influence the speed variations of droplet. The standard deviation of droplet speed from different waveform design was investigate and evaluated. In this study, it is evidenced that by performing rear-wave adjustment on the W wave design can effectively reduce the standard deviation of droplet speed and produce the highest average speed.
Automation of occupational safety and health (K3) electricity based on internet of things (IoT)
Authors: Sholihah Qomariyatus , Hardiningtyas Dewi , Hulukati Stephan Adriansyah , Kuncoro Wahyudi
Published: March 2021

The use of computers in the future can to dominate human work and defeat human computing capabilities such as controlling electronic equipment remotely using internet media, IOT (Internet of Things) allows users to manage and optimize electronics and electrical equipment that uses the internet for Automation of Work Safety and Health (K3) Internet Based Electricity of Things (IoT). Design of Automation Occupational Safety and Health (K3) Electricity Based on the Internet of Things (IoT). which is used to test the installation of research instrument equipment. This needs to be done to ensure that the installation and research instruments function properly at the actual time of the experiment. Devices that have been made by researchers can work well as expected, where the automation of the protection of Occupational Health and Safety (K3) Internet-Based Electricity of Things (IoT) so that it can provide initial assistance in the event of work accidents caused by gas leakage and fire monitored online by panel space operators.
Design of experiment of material level settings on the factors affecting the quality of calcium silicate board by using the Taguchi method
Authors: Hendra Franka , Margaretha  , Supriyono  , Vidhia Clara , Rosalinda
Published: March 2021

The main purpose of this paper is to identify and determine the level of regulation on factors that influence the type and characteristics of the pulp so that it can produce optimal quality Calcium Silicate Boards. The experiments were carried out using the Taguchi method and using quality characteristics: strength, deflection, density, and water absorption. Then, the factors that influence product quality are the use of pulp percentage, pulp type, and pulp composition. Data processing uses two analyzes to determine the optimal level setting, which consists of mean analysis and signal to noise ratio analysis, then an experiment is carried out to confirm the predictive value of the level setting factor under optimal conditions. The results showed that the type and composition of the pulp affected the strength and density of the product, the use of the percentage of the pulp affected the deflection of the product, and all factors did not affect the absorption of product water, with an optimal level of regulation: 9.8% percentage of pulp, Y type of pulp, and 100% pulp composition. Confirmation results obtained an average value of the strength test was 154.5 kg / cm2, 13 mm for the deflection test, 1.3275 g / cm3 for the density test and 36.35% for the water absorption test.
The effect of pouring temperatures to tensile strength and porosity of aluminium processed with vacuum casting
Authors: Nurhidayah Ichwan , Aminnudin  , Afifah Nurul
Published: March 2021

Pouring temperature also affects the mechanical properties of aluminium. High pouring temperature will make aluminium grains become large and a lot of gas will be trapped into the liquid metal when the metal is poured into the mould. The right temperature will prevent metal porosity and the metal does not freeze before filling the entire moulds cavity. The casting process used permanent mould. Temperature of the moulds was 150 °C and the pressure 0.35 atm (absolute pressure). Pouring temperature were 750, 800 and 850 °C. The increasing pouring temperature reduce the tensile strength and specific density of aluminium. Pouring temperature aluminium in vacuum casting system at 750 °C produce the highest tensile strength (130.26 MPa). The specific density of the aluminium is 2.65 g/cm3
Low pressure casting effect to tensile strength of aluminium
Authors: Aminnudin  , Anwar Muhammad Said
Published: March 2021

The air in the mould cavity is pushed out by liquid metal when the liquid metal entered mould cavity. In green sand-casting process, the air passes through the pores in the mould. Permanent mould doesn’t have pores and the air released from the mould cavity only through air outlet. Low pressure on mould cavity make liquid metal easier and faster filling the mould cavity, and make casting process can be done at lower temperature, the main focus of this research is about effect of pouring temperature on the low-pressure casting process to tensile strength and porosity of the aluminium. The casting process carried out at 750, 800 and 850°C. Aluminium smelting uses electric furnace and the mould used is a metal mould with a pressure of 0.33 atm. The casting process on aluminium at low pressure (-0.33 atm) and at a temperature of 750 °C produces the highest tensile strength compared to aluminium casting at 800 and 850 °C. The increasing pouring temperature increasing porosity of aluminium is from 1.86% at 750 °C to 4.03% at 850 °C.
Improved mechanical properties with the soaking time of NaOH in composites made from sugarcane bagasse fibers for future windmill blades material
Authors: Laksono Andromeda Dwi , Faisyal Muhammad , Kurniawati Diniar Mungil , Awali Jatmoko , Ramadhan Gilang , Rozikin Muhammad Nurhidayatur
Published: March 2021

The purpose of this study was to determine the effect of 5% NaOH alkalization and soaking time for 1 hour, 2 hours and 3 hours on mechanical properties by tensile and impact testing and scanning electron microscope (SEM) on composites with sugarcane bagasse fiber reinforcement and epoxy matrix which have the potential as future wind turbine blades material. The method used in the manufacture of composites was a hand lay-up method with a volume fraction ratio of 60% epoxy matrix and 40% waste sugarcane bagasse fiber. The optimum results of this composite study showed the impact strength value on the composite with 5% NaOH soaking for 2 hours was 0.120 Jmm-2, the tensile strength value was on the composite with 5% NaOH soaking for 2 hours at 10.80 MPa. SEM analysis results on the tensile test fracture pattern showed that composites have failed in the form of fiber pull out and debonding which can reduce mechanical properties, especially in strength. In this study, it was concluded that the alkalization process of 5% NaOH for 2 hours had a significant influence on improving the mechanical properties of sugarcane-epoxy fiber composites.
Conduction mechanism of Co-doped ZnO transparent memristive devices
Authors: Simanjuntak Firman Mangasa , Chandrasekaran Sridhar , Prasad Om Kumar , Gapsari Femiana , Prodromakis Themis , Tseng Tseung-Yuen
Published: March 2021

The Co dopant substitutes the Zn atomic position in the hexagonal crystal lattice and generates acceptor defects. These defects play significant role in modulating the conduction mechanism of the memristive device. The devices without Co dopant have high concentration of donor defects so that the electron can flow easily through hopping these donor defects; henceforth, only weak filaments can be formed during the set process. Meanwhile, the increase of the acceptor defects in the films enhances the film resistivity. This acceptor defects also contribute to an increase of barrier height at the electrode/dielectric interface where the electrons require higher energy to overcome this barrier and, eventually, induce the formation of strong filaments during the set process.
Voids analysis on polyester matrix composites reinforced with a combination of Bambusa bluemena fiber and fiber glass from tensile test results
Authors: Syarief Akhmad , Raliannoor  , Isworo Hajar , Sabitah A’yan
Published: March 2021

Composites with BQTN 157-EX polyester matrix Yukalac reinforced with bambusablumeanafiber and glass fiber are used to find the right reinforcement composition. For natural fibers that are used to get special treatment, namely the separation of fibers by alkaline immersion process. The mixing process of the 2%, 2.5% and 3% reinforcement volume fraction was used for ASTM D638M-84 tensile testing variations. The maximum tensile strength is obtained in the bamboo powder and glass fiber fraction with a length of 5 mm with a value of 53.581 MPa. Void observations in the form of bubbles were carried out by quantitative metallographic analysis of ASTM E112-10 standards. The result of macroscopic enlargement, most voids in the volume fraction of reinforcement 3% of bamboo fiberhaur and glass 5 mm long an average of 9 point grid. The greater the volume volume fraction of the mixed bamboo and fiberglass, increasing the likelihood of voids occurring.
FTIR analysis of alkali treatment on bacterial cellulose films obtained from pineapple peel juice
Authors: Suryanto Heru , Aminnudin  , Mahsuli  , Wijaya Husni Wahyu , Yanuhar Uun
Published: March 2021

This study aimed to identify the functional group of bacterial cellulose films (BCF) treated by alkali (NaOH) solution. The research methods were BCF production using medium culture based on pineapple peel juice. The resulted pellicle was immersed in the alkali of 0%, 1%, 5%, and 10%. Pellicle was dried in the oven to obtain BCF. Functional group of the sample was recorded by an FTIR instrument. BCF surface was observed by scanning electron microscopy. The result shows that structure of BCF contains cellulose I and cellulose II. The functional group of BCF before and after the treatment were at wave number 3400 cm−1, 2900 cm−1, 2133 cm−1, 1635 cm−1, 1373 cm−1, 1067 cm−1. Alkali treatment caused the peak band at 2135 cm−1to be reduced due to the breaking of the triple bond of alkynes.
Mechanical properties of starch-based biocomposite: The effect of acidic atmosphere treatment
Authors: Setyamarsa Y A , Suryanto H , Kustono D , Aminnudin A. , Suyetno A , Edy D L , Pradana Y R A , Lubis D Z , Bintara R D
Published: March 2021

The objective of this study was to obtain the mechanical properties of starch-based biocomposites after treated in an acidic atmosphere. The research applies the tapioca starch, glycerol, distillate water, and nanoclay as biocomposite raw materials. Starch-based biocomposite was made by casting method. Acid sources for acidic atmosphere treatment were acetic acid with various pH of 1, 3, and 5 with exposure time for 4 hours. Characterization of biocomposite was conducted using tensile test, SEM and FTIR analysis. The acidic atmosphere treatment results decreasing both in the tensile strength and modulus in higher acidic atmosphere. The tensile test of biocomposite treated by the acidic atmosphere with acidic source pH 5 has an optimum modulus of 36.9 MPa and tensile strength of 9.1 MPa. The functional group of biocomposite changed after treatment in wavenumber of 2358 cm−1.
Hidden bioactive of caryophyllene inside Keruing wood
Authors: Malik Jamaludin , Santoso Adi
Published: March 2021

In the utilization of natural resources, there is often something problematic on one side, but there are benefits on the other side. Utilization of natural resources in the form of wood should be directed at a variety of efforts that are more diverse, not focused on wood only. Bearing in mind that trees contain not only lignocellulosic components, but other high-value materials. Research was conducted on one species of wood that is considered problematic in wood processing, namely Keruing (Dipterocarous hasseltii). The results showed that the Keruing wood contained extractive substances with the main compound of bioactive caryophyllene which is widely used by the pharmaceutical, food and cosmetics industries. The total caryophyllene content in extractive wood reached 47.68%.
Core sandwich material development based on vinyl ester bioresin for ship structure application
Authors: Tuswan Tuswan , Zubaydi Achmad , Piscesa Bambang , Sari Eli Novita , Ismail Abdi
Published: March 2021

Development of lightweight core sandwich based bioresin for ship structure application needs more attention. Bioresin from vegetable oils constitutes single, easily available, low cost, and biodegradable materials. In this research, the vinyl ester bioresin based Vinyl Ester-Coconut Oil (VE-CO) and Vinyl Esters-Soybean Oil (VE-SbO) containing 4 wt% vegetable oils are developed. The influence of vegetable oil addition in bioresin is characterized by visual observation and physical testing, including FTIR, density, hardness, and tensile test based on Lloyds Register standard. Visual testing shows that VE without vegetable oil is more transparent compared with VE with vegetable oil. The density test shows that adding vegetable oil decrease the apparent density. Vibration pattern indicates the presence of O-H, C-H, C=O, C=C, and C-O-C, which demonstrate the ability to bind, which leads to the potential formation of a polymer blend and elongation increase. Moreover, hardness decreases due to the absence of chemical bonds that occur between vinyl esters and vegetable oils. The addition of vegetable oil to vinyl ester bioresin reduces tensile strength and increases the elongation at break. So, density and tensile strength criteria meet Lloyd’s Register Standard while the other criteria are not fulfilled.
Technical analysis of biocomposite reinforced with sugar palm (Arenga Pinnata) fiber for jukung materials
Authors: Samlawi Achmad Kusairi , Ansyah Pathur Razi , Cahyono Gunawan Rudi
Published: March 2021

This study aimed to determine the effect of composition between sugar palm fiber (Arenga Pinnata) and polyester resin as composite materials. The parameters are focused on impact strength, tensile strength, and modulus of elasticity and are compared to Badan Klasifikasi Indonesia (BKI) standard which is Regulations for the Classification and Construction of Ship in Indonesia. The composition of fiber and resins is 30:70%, 40:60%, and 50:50% using mass fraction. The angle orientation of fiber is 0,90,0,90 and manufacturing process uses the hand lay up method. Impact testing is carried out with the ASTM D5942-96 standard and Tensile Testing is carried out with the ASTM D638-03 standard. The results showed that the composition of 50:50% is the highest test value compared to other compositions, with average impact strength of 1.703 x 1016 kg mm−2, tensile strength of 27.13 N mm-2 and modulus of elasticity of 790.01 N mm−2. Although the results of the value of the impact test, tensile test and modulus of elasticity of the composition of the mass fraction of sugar palm fiber (Arenga Pinnata) material are still below the BKI standard, it still has the potential to continue to be developed as an alternative raw material for making Jukung (traditional boat in Banjarmasin).
Failure analysis of a gas turbine blade: A review
Authors: Puspitasari Poppy , Andoko Andoko , Kurniawan Pradhana
Published: March 2021

Blade is an essential component of a gas turbine that functions to convert thermal gas energy at a high temperature and pressure into mechanical energy. Gas in the turbine blade works at a high temperature and pressure. High temperatures and pressures cause turbine blades to be one part of turbine components that often fails. Failure of the blade results in performance and turbine efficiency. The cause of failure on the blade is influenced by several factors, including fatigue, creep, oxidation, degradation of the coating on the turbine blade, corrosion, erosion, and surface degradation due to working at high temperatures. The hot temperature on the blades work on turbines around 1927 F to 3500 F and is one of the main factors in the failure rate. Individual blade failure rates differ due to operating temperature, rotation speed, operating mode, total service time, and differences in fabrication. This article discusses several case studies of failure in turbine hot section components such as blades to support the failure investigation is the key to improving turbine efficiency.
The effect of pin probe length on the characteristic of dissimilar metal Al-CuZn lap joint using friction stir welding (FSW)
Authors: Setiawan Widia , Thoha Muhammad Badarudin , Surojo  , Santoso Nugroho
Published: March 2021

Dissimilar lap joint between aluminum 6061 and brass is performed by using friction stir welding (FSW) method where universal milling machine is used to implement this method. The parameters that use in welding are probe design with a varied length of pin probe 11.0 mm, 11.5 mm and 12.0 mm at 2000 rpm rotation of machine and feedrate 10 mm min−1. The macrostructure result of pin probe length 11.0 mm better than of pin probe 11.5 mm and 12.0 mm. The mechanical properties results with a pin probe length 11.5 mm a higher mean hardness value of 104.26 VHN than a pin probe length 11.0 mm and 12.0 mm with hardness values of 98.93 VHN and 70.43 VHN. Shear stress result of 67.32 MPa with a pin probe length 12 mm, better than of pin probe length 11.0 mm and 11.5 mm shear values of 40.2 MPa and 42.14 MPa.
Effect of thermal cycling on the cold rolled AISI 316L with varying degree of reduction toward their microstructure and hardness
Authors: Mubarok Fahmi , Rosalina Amanda
Published: March 2021

Orthopedic implants had been widely used to treat bone fractures. One of the selected materials for an implant is austenitic stainless steel AISI 316L following the ASTM F138 standard. These implants had been produced locally in Indonesia using investment casting method. Even though the mechanical properties of local implant had met ASTM standards requirements, it was found to be lower in their properties as compared to the imported implant from developed countries. In order to compete with these imported products, local implant 316L was modified by reducing their grain size microstructures of about 83.17 µm on average to become finer grain through recrystallization mechanism. The mechanism can be triggered by thermal cycling treatment after 316L was subjected to cold rolling process. The cold rolling process will induce stored strain energy that affects the dislocation density. Different degrees of cold rolling reduction of 52%, 60%, 69%, 80%, and 90% will give different amounts of dislocation density that will affect the recrystallization stage during thermal cycling. It was found that after thermal cycling treatment at 900 C for 35 seconds with 4 cycles, homogenous full recrystallization was confirmed on 80% and 90% reduction degree samples. The average grain size of 80 and 90% reduction degree samples were decreased from 83.17 µm on average detected in the investment casting product to 3.26 µm and 2.87 µm, respectively. This had resulted also in increased average hardness from 159 HV2 to 257 HV2 and 267 HV2 respectively. Conversely, only partial recrystallization was observed in the other degree of reduction samples. The obtained hardness provides lower value than 80% and 90% reduction degree with larger average grain size being detected on these samples.
Mathematical model of wear volumes due to sliding speed using Buckingham Pi Model
Authors: Kaelani Yusuf , Syaifudin Achmad
Published: March 2021

The objective of this research is to determine a mathematical model of wear volumes due to sliding speed. Some researchers have studied the influence of sliding speed, roughness and coefficient of friction. However, mathematical model dealing with sliding speed has never been explicitly reported. Wear analysis due to various speed is offenly expressed experimently through charts concerning both wear volume and sliding speed instead of mathematics. This research conducts variables affecting wear. The study is started by modeling mathematical representation within Buckingham Pi Theory. The mathematical model includes wear volume, hardness,normal loads, sliding speed, sliding distance, and density of materials. Since Buckingham set requires constant of equality, the equation is solved by rectifications. The model, in turn, is verified by data gathering to determine the constant. This value is called Wear-Speed Coefficient. Experiment using pin-on-disk tribometer is conducted by varying sliding speed and normal loads. Further more, those parameters are applied to estimate wear volumes. Furthermore, It is compared with those measured data. Moreover, the mathematical model is verified by comparing graphically to results of previous researchers having evaluated wear volumes due to sliding speed. The materials included are 2014 Aluminum Alloy, NBR Rubber Nitril, Ultra High Moleculair Weight Poly Ethylene (UHMWPE), and Poly Tetra Fluoro Ethylene (PTFE). The results of discussion shows that the mathematical approach modelled using Bucking Pi Theory is mostly similar to patterns. This study yields several constants of wear-speed coefficient relating to the materials.
Influence of chamber pressure variations of plasma nitriding on surface hardness and micro structure of Al 6061
Authors: Oerbandono Tjuk
Published: March 2021

Aluminium 6061 is a material that is widely applied in industrial and automotive parts. The corrosion resistance and surface hardness of Al 6061 can be improved by using plasma nitriding. Plasma nitriding is the process of treating the surface of a material by inserting nitrogen in the material through the plasma, i.e. nitrogen gas was converted in the form of plasma before being inserted into the material. This research was conducted using experimental research methods by directly observing the plasma nitriding process. This research used aluminium alloy 6061 as a specimen, variations in chamber pressure of plasma nitriding 100 mTorr, 200 mTorr, and 300 mTorr, constant temperature of 150 °C, constant power input of 40 watts, and holding time for 2 hours. Hardness testing was carried out using a micro-Vickers hardness tester, whereas microstructure testing used SEM (Scanning Electron Microscope) and EDAX. Experimental results showed the highest surface hardness value of Al 6061 was 276.5 VHN. This condition occurred at a chamber pressure of 200 mTorr, temperature of 150 °C, the input power of 40 watts and a holding time of 2 hours. Based on composition and microstructure analysis using EDAX and Scanning Electron Microscope shown that the lowest surface hardness 179.4 VHN had a nitrogen content of 1.225% and this occurred at a chamber pressure of 300 mTorr.
ASTM A36 steel corrosion rate control in 1M HCl using Electrophoretic Deposition (EPD) with chitosan coating
Authors: Gapsari Femiana , Setyarini Putu Hadi , Hidayatullah Syarif , Puraditya Yohanes D. , Wijaya Hastono , Abidin Zainul
Published: March 2021

This study aims to investigate the effective coating time for ASTM A36 steel using chitosan in 1M HCl. In this study, ASTM A36 steel was used as a test specimen and the EPD technique was employed with coating time of 10, 20, 30, 40, and 50 minutes. The electrochemical technique was conducted using Autolab PGSTAT128N. In addition, this study also employed potentiodynamic polarization and Electrochemical Impedance Spectroscopy (EIS). It was found that longer chitosan coating using EPD will produce better coating results.
The effect of the welding methods on the corrosion rate and impact strength of AA5083 material
Authors: Suryo Dhanang , Sugiarto  , Setyarini Putu Hadi
Published: March 2021

The 5xx series aluminum alloy is currently widely used in marine construction applications for the fabrication of chemical tankers, offshore and others because it has good corrosion resistance. This study aims to determine the effect of the welding method on the corrosion rate and impact strength of 5083 aluminum. Four specimens of AA 5083 in this observation were preheated until reaching temperature 50 °C, 150 °C, 250°C and 300 oC as the selected variations. Then, welding result were tested by Charpy impact test with different load for determining amount of energy absorbed during the fracture process. After comparing the the impact toughness, the best specimen was conducting the corrosion rate test by using Corrosion Tester 3-Electrode system. The study result show that specimen with 250oC preheat was the highest impact toughness with 0.1593 mmPY corrosion rate result.
Failure analysis of pipeline elbow connecting high pressure heater to deaerator in a steam power plant
Authors: Yudanto Fajar Dwi , Ariyanto Dwi , Arfi Abdul Aziz , Suwarno
Published: March 2021

The coal-based steam power plant accounts for the largest electricity generation in Indonesia. Disruption in operation mostly caused by a failure of a component of the system and considered a serious problem and must be prevented. Failure can be originated from operations as well as the design. In the present work, a root cause study was performed on failure elbow in the steam line from the high-pressure heater (HPH) to the deaerator. The failure occurred only after 5 years of operation. The analysis was started with a visual examination, material verification, microstructural investigation, thickness measurement, and computational modelling. The analysis and simulation study showed that the failure of the elbow caused by two-phase flow where steam quality was compromised. The recommendation was to examine the HPH and to find possible leaks of the waterside to the steam side in the HPH system.
Dynamic Multi-agent Real Time Scheduling Framework for Production Management
Authors: Talmale Girish , Shrawankar Urmila
Published: March 2021

Production management is a complex problem. The problem becomes more complex in open, uncertain, dynamic environments and distributed productions. The existing static scheduling methods are not efficient to deal with this problem efficiently. This paper proposed multi-agent approach for real time scheduling in production management to efficiently manage production. The proposed scheduling optimizes the performance of production management in dynamic uncertain environment. Dynamic multi-agent approach in real time scheduling consist of the agent collect and analysis the production data in real time and ensure real time response to emergency events. Real time scheduling agents increase the resource utilization and success rate in production management by using real time feedback.
One Hop Neighbor based Broadcast Method for Reactive Routing in Mobile Ad-hoc Network
Authors: Mittal Nimit , Pahadiya Pallavi , Agrawal Amit
Published: March 2021

To overcome redundant issues of routing messages for the reactive routing protocol is become research challenge. In general, to discover route or path reactive routing protocols broadcast routing messages which may leads congestions and degrades battery power unnecessary. Though, to resolve the challenges several efficient broadcast methods have been suggested. Each method has its own procedure and results sort of advantage and disadvantages. The motive of the paper is to presents a method which is proposed to minimize redundant issue of routing messages resulted by broadcasting. Proposed method uses one hop neighbor’s knowledge to broadcast routing messages for the purpose of route discovery. Proposed method experimented through simulation software that named as NS-2. An experimental accomplish certain factors like number of nodes, routing protocol, MAC protocol etc. Proposed method evaluated on the basis of different criteria such as throughput, control overhead, routing efficiency and node remaining battery power.
Linear Regression based Power Optimization of Wireless Sensor Network in Smart City
Authors: Sahu Manish Kumar , Patil Sunil
Published: March 2021

The modern smart cities are highly dependent on the performance of the Internet of Things (IoT) based energy-efficient sensor networks. Energy efficiency is a critical and indispensable issue for wireless sensor networks (WSNs). In the collection of sensor nodes, one node is selected to collect data and forward it to the base station. The modern base stations in smart cities are unmanned aerial vehicle (UAV) based. This paper presents a linear regression based model, where the initial residual energy and its corresponding transmission power are submitted to the proposed system, then it generates a prediction model since transmission power depends on the residual energy of the sensor node. Based on this model the transmission power of the sensor node can be calculated for data transmission as a higher residual node is best suitable for data transmission to the base station. As presented in the simulation result, the regression based model gives better performance for energy efficiency in WSN.
Analysis of image inpainting and object removal methodologies
Authors: Thomas Shiney , Mathew Juby
Published: March 2021

Image inpainting is a process that tries to fill in missing parts of a degraded image or remove objects from an image, but maintain the realistic content in the image. Various methods can be employed to perform inpainting. Here three benchmark methods of which two are conventional and other GAN based are evaluated to check the effectives of the inpainting process, for different class of images. The visual quality evaluation as well as quantification parameter namely the SSIM score was computed. Based on the test score it was seen that the GAN based method was capable of providing visually good restored images with an average SSIM score of 0.9516, which is an indicator on the quality of the image. The GAN based methods can be further enhanced to provide more realistic images by incorporating functions to extract both local and global contextual content.
Robust Segmentation and Classification of Moving Objects from Surveillance Video
Authors: Chandrajit M , Shobha Rani N , Manohar N
Published: March 2021

Object segmentation and classification in the video sequence is a classical and critical problem that is constantly addressed due to vast real-time applications such as autonomous vehicles, smart surveillance, etc. Segmentation and classification of moving objects in video sequences captured from real-time non-constraint sequences is a challenging task. This paper presents a moving object segmentation and classification method for video sequences captured in a real-time environment. The key contributions of the paper include a method to detect and segment motion regions by applying the non-parametric Kolmogorov–Smirnov statistical test in the Spatio-temporal domain and a probabilistic neural network-based classification method to classify the moving objects into various classes. Promising results are obtained by experimentation using challenging PETS and Change Detection datasets. To corroborate the efficacy, a comparative analysis with contemporary method is also performed.
A recurrent neural network forecasting technique for daily PM2.5 concentration level in Southern Kerala
Authors: Babu Sherin , Thomas Binu
Published: March 2021

The natural environment and public health are seriously impacted by air pollution. One of the most dominant contributors to air pollution around the world is particulate matter PM2.5. Predicting air pollution in advance has considerable importance for the regulation of people’s health and to implement pollution control strategies for air quality management. The study was conducted for Thiruvananthapuram district, the southernmost region of Kerala. The data for the period from 1st July 2017 to 31st December 2019 were collected from the Central Pollution Control Board (CPCB) website. To predict the daily PM2.5 concentration, Recurrent Neural Network (RNN) based Long Short-Term Memory (LSTM) was used here. LSTM was built on the inputs of four meteorological parameters, namely average temperature, wind speed, wind direction and relative humidity and air pollutant parameter PM2.5 values. Performance evaluation of the prediction model has conducted, and the results showed that the model attained considerable prediction accuracy.
Segmentational color map analysis to identify retinal detachment
Authors: Poongothai L. , Sharmila K.
Published: March 2021

The recent perilous times entails the importance of good health for humans. This can be pertaining the maintenance of good health in various organs of the human body. With the increase of digital platforms, and the necessity to stay longer hours with gadgets and electronic devices, the human eye takes a toll in terms of absorbing radiations that maybe harmful. An imperative check of the eye is essential from time to time, as the luminous membrane that aids in vision needs to hold firm to the various components within itself. Although there are various treatments associated with the detection of eye detriments, several gremlins tend to loom at large. These eye diseases can arise from numerous reasons ranging from genetic disorders to accidents and vision loss due to stimulated injuries, infections and dysfunctional development of tissues/cells/nerves within the eye. Retinal detachment (RD) is one of the profound problems that persist amongst many individuals scaling over a diverse range of ages. The risk in relevance to untreated detachment of the eye leads to purblind and sometimes complete loss of vision. The previous paper concerning retinal detachment of human eye has focused on various algorithmic and post-processing approaches, but failed to identify the origination and symptoms that could aid in meticulous diagnosis. The indagation in this paper pivots on the unsheathing of attributes that explicates the disassociation of the retina from the underlying layers of the eye using the fundus image with cost-effectiveness and swifter analysis. An important characteristic that is emphasized in this study is the segmentation of eye floaters in the vitreous fluid of the eye. These eye floaters are color mapped to identify the presence of detached tissues in the eye. The histogram analysis using the grayscale thresholding value further aids in providing a detailed distinction of the normal eye from the detached eye. The simulations are carried out in MATLAB, and the results have been obtained successfully.
ECG based Decision Support System for Clinical Management using Machine Learning Techniques
Authors: Moturi Sireesha , Vemuru Srikanth , Tirumala Rao S. N.
Published: March 2021

Heart disease prediction system using ECG is to predict heart disease using ECG signals. Heart is the next major organ comparing to brain, which has more priority in human body. Heart disease diagnosis is a complex task which requires much experience and knowledge. The huge amount of data generated for prediction of heart disease is too complex and voluminous to be processed by traditional methods. By using traditional methods doctors took lot of time to diagnosis the disease. So, an entropy based feature selection technique is used with classification algorithms in order to reduce the search space. The proposed model was tested on the real time dataset of NRI Hospital medical data. Using this system it is easier to predict the disease. It will also helpful for the doctors to take quick decisions.
An evaluation of deep learning approaches for detection of voice disorders.
Authors: Chinchu M S , Kirubagari B.
Published: March 2021

The human voice manufacturing system is a complicated natural device capable of modulating pitch and loudness Human sound frequency particularly. The part in which the folded is the primary source underlying internal and/or external factors often destroys vocal folds justification. Some changes consequences are reflected in functioning emotional state soul. Therefore it essential to identify variations at an early stage gives the patient an endangerment overcome any impact modernize their quality of life will-less detection disorders using depth study methods plays an important role as has been proven to facilitate the process. Many researchers have explored technologies for streamlined that can help clinics diagnose noise paper we present the conducted research activities.
Answer Book Valuation Using Semantic Similarity
Authors: Sunilkumar P. , Sunil K.S.
Published: March 2021

Conventional examination systems are a tedious task for the universities and the faculties. It takes a lot of time and human effort for the valuation of the answer books, updation of the marks and the declaration of the results. Automation of descriptive answer book assessment would be useful for universities and academic institutions to simplify the valuation system to a large extend. It ensures a uniform valuation and also helps to publish the results without much delay after the examination. We design a system for automatic assessment of descriptive answer books of technical subjects. Semantic similarity is a metric used to assess the similarity between documents and it gives the degree of similarity as a numeric value. It can be used to value the students’ answer books by checking the similarity with original answers given in the answer key and then award appropriate marks.
Analysis of distance measures in spatial trajectory data clustering
Authors: Sharmila S , Sabarish B A
Published: March 2021

Tremendous growth of Location-based technologies resulted in the generation of a huge volume of spatial data, which needs to be analyzed to get potentially important patterns. The spatial patterns extracted can be used to design a better infrastructure ensuring reliable service coverage. Trajectory data is one variant of spatial data that are generated by moving objects travelling across. It is represented as a sequence of spatial coordinates (latitude, longitude) of a location. Trajectory clustering tries to group similar spatial data points to extract the most common movement behaviors. Trajectory data poses major challenges including uncertainty, sampling rate, representation, relationships, spatial autocorrelation, serialization, redundancy, and triviality, which makes it hard to apply traditional clustering algorithms over trajectory data. In this paper, K-Means and DBSCAN (Density-based spatial clustering of applications with noise) clustering algorithms are analyzed using different similarity measures like Euclidean, Hausdorff and Haversine distances with the help of index measures say Adjusted Rand Index (ARI) and Fowlkes-Mallows scores (FMS). Experiment is carried out over two different trajectory datasets and it is proved that usage of Haversine distance for clustering is efficient than Euclidean and Hausdorff distances in terms of spatial trajectory data.
An Early Disease Prediction and Risk Analysis of Diabetic Mellitus using Electronic Medical Records
Authors: Gulhane Rutuja A , Gupta Sunil R
Published: March 2021

In the world today, the fourth leading disease is Diabetes that could lead to other serious complicating diseases. Diabetes is one of the most common chronic disease which can also be the cause of death in many cases. An efficient system for early disease prediction and risk analysis of diabetic mellitus is very much needed as it has the major adverse effects. The large amount of medical data is collected by healthcare industry in the form of Electronic Medical Records. The Electronic Medical Records is communal database for clinical disease and risk prediction that are useful in accurately predicting multiple medical events using machine learning approach. Therefore, this research presents an efficient technique for early prediction and risk analysis of diabetic mellitus disease to improve accuracy and precision using Electronic Medical Records.