Advanced in Creative Technology- added Value Innovations in Engineering, Materials and Manufacturing

In this research, the compressive strength of interlocking concrete blocks made using 80% glass instead of sand will be compared to the TIS 58-2533 standard. The blocks have dimensions of 10 cm in width × 25 cm in length and 12.5 cm in thickness. Additionally, there are two circular holes beneath the block that measure 5 cm in diameter and 1 cm deep. These holes were placed at different distances based on the thickness of the interlocking concrete block. This was achieved by using concrete with a 1:1.17:1.59 ratio and a water/cement value of 0.40 (w/c) for each block. Thirty samples of each kind, totalling 60 samples, were air-cured and moist-cured for 3, 7, 14, 21, and 28 days using a glass mixture instead of sand. The findings demonstrate that when 80% glass is used as a substitute for sand in a 1:1.17:1.59 ratio with a water/cement ratio of 0.40 (w/c), the interlocking concrete blocks exhibit a consistent interlock and curing for the entire 28-day duration. The average ultimate strength was 133.65 kg/cm2, which is 81.29% higher than the TIS 58-2533 standard for moist curing throughout the 28-day period. The average ultimate strength was 148.20 kg/cm2, which is higher than the TIS 58-2533 standard by 83.13%, and the moisture curing experiment exceeded 9.82%.

This paper aims to present the improvement of nozzle blade C-9015A of wet-steam turbines in modern power plants by reducing blade erosion. This may be done with the help of changing the blade's geometry. There are different ways to reduce the erosion of the blade's surface, the most important of which is using special alloys for the blade and coating the nozzle blade. In addition, a new initiative to reduce moisture erosion after moisture hits the blade surface is the use of another function for the geometry of the blade, and the purpose of this paper is to show that under another surface geometry, this surface should have less erosion than itself surface of the geometry of the blade. The impact results of different droplet diameter range on the blade's new geometry have been accounted for and compared with the moisture impact results on the nozzle blade's initial surface. Furthermore, in both cases, the erosion energy on the blade surface has been accounted for and compared.

The objective of this research is to determine the appropriate parameters for achieving the desired surface roughness (Ra), cutting tools is used a hard series carbide ball-nose end mills (model 5R × 10 × 60L), equipment consists of a Chevalier automatic milling machine (model QP 2026-L) for the machining process and a calibrated Mitutoyo surface roughness tester (model SJ-310) for measuring the surface roughness. The surface roughness tester was calibrated using a 2.94 µm Mitutoyo calibration plate. The SKT4 steel sample is prepared with a size of 100 × 100 × 50 mm, hardness range of HRC 40-48. The research are focused on investigating the influence of the feed rate and depth of cut on surface roughness. The spindle speed was maintained at 1,500 RPM, and air cooling was utilized during the milling process. Surface roughness was evaluated using the Ra parameter, representing the average roughness of the surface. The measured Ra values were compared to a standard range of 12.5–3.2 µm. The results indicated that variations in the feed rate and depth of cut had a significant impact on surface roughness. Optimal surface roughness was observed at feed rates of 300, 500, 600, and 800 mm/min. Furthermore, a difference in the depth of cut of 4 conditions had a notable effect on surface roughness.

An A microchannel heat sink, which includes a heat exchange cavity, are a variation of fin and tube heat exchangers. Fluid, in the form of a coolant, flows through tubes or enclosed channels, the hydraulic diameter of the channels is less than 1 mm. The fluid used in the simulation is MXene based nanofluids, MXenes are two dimensional inorganic compounds which combine the metallic conductivity of transition metal carbides with a hydrophilic nature because of their hydroxyl- or oxygen-terminated surfaces. They tend to have good thermal conductivity and the aim of the study is to prove the difference in heat transfer between MXene fluid and water. The nanofluids are passed through the Micro Channel Heat Sink using a pulsating flow driven by square wave are to improve the thermal performance. ANSYS is used to numerically simulate the environment of the microchannel and to predict the outcome of the study. A mesh sensitivity study has been conducted to determine the mesh which is the most accurate to conduct the further study. The results obtained were mainly discussed using few fundamental concepts like the Velocity, Pressure and Temperature Contour together with the Nusselt Number Analysis to determine the trends between fluid with various pulsating frequency.

The research optimizes vehicle wheel rims to create sustainable power and reduce weight. The study employs aluminum alloy AZ80 to lighten wheel rims while retaining safety. The project aims to improve vehicle agility and power generation while reducing pollution and energy use. The research method focuses on improving the efficiency of a vehicle's tire rim to generate renewable energy. The study employs aluminum alloy AZ80 to reduce wheel rim weight. Topological optimization and structural research utilizing the finite element approach show a 15% mass decrease while retaining a safety factor 3. The study’s findings indicate that reducing the weight of the wheel rim using the aluminum alloy AZ80 can result in energy savings and pollution reduction. The research provides insights into boosting wheel stiffness, rigidity, mechanical strength, and fatigue life and suggests a viable route for improving sustainable transportation. This research proves that power may be generated most efficiently from a vehicle's wheel rim. More study is required to realize this method's potential and create superior variants entirely. The research has massive consequences for optimizing automobiles, particularly in Bangladesh, and provides insights for improving wheel stiffness, rigidity, mechanical strength, and fatigue life. The study focuses on generating sustainable electricity utilizing an inverter mechanism and a belt-pulley system within the wheel hub, which provides a viable route for the growth of sustainable transportation. Using the aluminum alloy AZ80 to reduce the weight of the wheel rim can also result in energy savings and pollution reduction.The research's topological optimization methods and usage of AZ80 aluminum alloy to reduce wheel rim weight are unique. Structural analysis utilizing the finite element approach and mass optimization shows a 15% mass reduction while keeping a safety factor of 3. The research can improve wheel stiffness, rigidity, mechanical strength, and fatigue life, which could lead to sustainable transportation.

In this paper, a study of the properties of S50C steel used for mold structure is presented, and plastic injection molds are prepared to be hardened by giving it a low surface hardness. There is a risk of warping and cracking when heat treatment causes the surface to be hardened for milling, turning, and hardening processes. By receiving heat from two sources: the heat from the heater and induction heating. When heating from a heater that can reach a temperature of 600–800 ℃ with induction heating, using an inverter circuit to adjust the power and control the temperature for heat, studying the internal structure of steel when heated, and hardening test results of the S50C steel structure by using a laser confocal microscope to see the comparison results of unheated steel, heated steel with a heater, and steel that has been heated by induction heating.

Energy is a must the belonging to human beings in everyday life the day. Nowadays, the value of energy is higher. Renewable energy this to play a greater role. Purpose research is to design and build mixers automatic charcoal briquette press. Charcoal production from waste materials, coconut shell charcoal powder. Study property the problem of charcoal powder, design and construction of mixing machines, automatic charcoal briquettes. Study the performance mixer and efficiency of Automatic charcoal compress and studying the properties of charcoal briquettes. Trial this Coconut shell charcoal powder, tapioca starch the cassava as a binder and water. It is an ingredient. Charcoal powder 3 kg. Tapioca starch the 50 g and water empty 450 ml. Mixed with a mixer leading residents into the machine a Charcoal briquettes. Study the properties charcoal powder. The evaluation the efficiency of mixing machine, charcoal briquette press and the study of the properties of charcoal briquettes. The results showed that initial charcoal with moisture 26%wb. Charcoal density 552.18 kg/m3 the performance of the mixer is compatible with at 5 min. Mixing 300 kg/kWh Charcoal compressor capacity 7 s per briquette. Power consumption the Charcoal briquette machine 293.33 briquettes/kWh. Moisture content of charcoal 7.23%wb. Density of charcoal 747.53 kg/m3 as mixing index 0.97 the calorific value of charcoal 6588 kcal/kg is within the range. Product charcoal briquette standard constraints the Bite/implication of research: Residual material (charcoal powder) the Can be used to benefit. But must go through the process briquette to increase the calorific value of the fuel. Practical effects: can be used the Charcoal powder can be compressed into bars to create value. The study focused on the mixing process. And charcoal briquettes from waste materials (charcoal powder) these energy to replace some fuels used in the combustion process because it is a by-product and creates value from waste materials.

This study examines the structural characteristics of porous materials derived from scanning electron microscopy (SEM) images of bamboo biochar. The goal is to design a metal-porous structure using biomimicry. The stress distribution in the porous structure during the cooling process after heating up to a high temperature was analyzed using the finite element method (FEM). The FEM model consists of a hexagonal body with circular pores arranged in an organized pattern and has consistent pore distances. Three pore sizes were examined to observe the stress distribution while cooling from 800 to 25 ℃. The study revealed that stress is caused by material expansion at high temperatures and rapid shrinkage at lower temperatures, leading to stress concentration. Additionally, the research shows that porous materials with smaller pores have a higher stress distribution compared to those with larger pores.

There is an ever growing demand for better materials in the aerospace and automobile industries. Conventional materials like steel and other ferrous alloys possess great strength, however they are heavy and energy inefficient. Aluminium and aluminium composites are light weight and a corrosion resistant material, it has lower specific weight and higher strength to weight ratio. The objective of this work is to propose an alternative material that will replace the traditional materials without compromising on the strength and durability. LM6 is used as the base and Al2O3 is chosen as the reinforcement. Samples were fabricated using powder metallurgy; compacted at the load of 15 ton and sintered at 550 ℃ for 60 min. The surface was also modified by gas nitriding at 450 ℃ up to 7 h. Tests for density, hardness, mechanical and wear characteristics are performed to study and evaluate structure and properties. The density of the composite was found to be lower than that of LM6. Values of hardness, tensile, compressive and shear strength showed a significant increase and further improvements were observed upon nitriding. Optimum nitriding time was found to be 4 h. The wear rate of nitrided samples was found to be lesser than LM6.

In today’s manufacturing industry, there is a growing demand for high-quality, precision-machined parts. However, one of the biggest challenges facing manufacturers is tool wear. As tools wear progress, they become less effective at cutting which can lead to poor surface finish, dimensional accuracy, and even tool failure. Vibration analysis is a non-destructive method that can be used to detect tool wear in real-time. Signal monitoring and analysis of the vibration characteristics on the cutting tool during the cutting process, it is possible to identify changes in the cutting conditions that are indicative of tool wear. Thus, the corrective action before the tool failure leads to preventing costly production delays and ensuring that high-quality parts are produced. This paper presents tool wear detection in real-time using the vibration analysis method. A vibration sensor is installed on the CNC turning center for detecting vibration data. A set of cutting experiments was conducted and vibration signals were then collected. The tool wear analysis was employed on observing changes in Power Spectral Density (PSD) of the vibration signals obtained by the Fast Fourier Transform (FFT) method. The remarkable results presented that the amplitude of the PSD increases as the tool wear increases. This study demonstrates that vibration analysis is a reliable and effective method for detecting tool wear in turning processes. This method can be used to improve the quality and efficiency of manufacturing processes, leading to significant cost savings for manufacturers.

This work aims to qualify the cans produced by WAFO Industry for the packaging of consumer oils in order to respond to the recurring concerns of consumers about the quality and food safety of the consumable products contained. This is an aspect of the support of this company towards the certification of their cans. The basic polymer raw material being high density polyethylene (HDPE), matrix in the formulation for the production of cans, a physico-mechanical characterization study is necessary, while having a look at the elements of contribution which are the calcium carbonate and the dye used. The cans being obtained by the extrusion blow molding process, the study seeks to see the influence of the transformation process on the raw material during extrusion. The methodology used is based on the determination of the mechanical characteristics by compression tests on 25-L capacity cans differentiated by their empty mass. We note that the compression tests carried out on cans produced with masses between 1.235 and 1.276 kg have a breaking strength which varies between 0.78 MPa and 0.90 MPa with a strain at break estimated at ε = 4, 6%. The raised elastic limit is equal to σe = 0.523 MPa for a modulus of rigidity E = 33.2 MPa. These results show that Wafo Industry’s edible oil container canisters meet the packaging requirements, from an environmental, mechanical and resistance point of view, at least for its primary role of protection against energy transfers and protection against material transfers. Thus for the improvement of the quality of the cans, some more tests are essential such as the perforation tests, the tests of control of thickness and the control of humidity of HDPE are the next lines of investigation.

This paper presents experimental performance of a polyethylene covered large-scale solar tunnel dryer type of Hoheinheim. Studies were conducted to investigate the performance of Hohenheim-type solar tunnel dryer for drying agricultural products under Togo climatic condition. However, in the sub-Saharan crop producers rely on open-air drying under the sun, this means that this method depends on good dry weather conditions. Tests of drying have been undertaken in experimental research station at Gapé Kpodji (latitude 6°25N, longitude 1°12E) in Togo on the two devices the more used: the traditional sun drying device and the Hohenheim tunnel drier.There is neither electric network nor regular provision in gas butane or other shape of energy besides the biomass. The trade of materials and equipment use for dryers’ construction are non-existent and the technical level of the population is low. The great majority of the population uses the traditional techniques of drying.The obtained the results revealed that the temperature available inside the Hohenheim solar drier produce a 15,5 °C increase in the inside air temperature versus the outside temperature (33,70 °C) to considerable reduction of drying time compare to the traditional device. Besides, the products are protected against rain, the bugs and the dust. It permits to get dry products of good quality. However, its capacity is very low considering to the quantities of cereal produced. Also the cost of maintenance and of its renewal is over the financial capacity of the users. The Hoheinheim drier certainly introduces some improvements compare to traditional sun drying but doesn't answer fully to the specifications of the users.

The Ti6Al4V alloys are used in many industries because it has excellent thermos-mechanical properties such as relatively lightweight, high strength, and corrosion resistance. However, grinding of titanium alloys is a challenge because it has low thermal conductivity and high chemical reactivity with most abrasives, and it is gummy and clogs the wheel pores rapidly, which leads to deterioration of the quality of the ground surfaces and increased wear of the grinding wheel. The microgeometry of the grinding wheel depends on the conditions of the dressing process and the type of the dressing tool and directly affects the quality of the resulting ground surfaces. The use of vibration in grinding is a trend in modern machining. This research paper aimed at optimizing the conditions of dressing and grinding of titanium alloy Ti6Al4V with the application of vibrations and a mist of vegetable oil. The obtained process performance shows the effect of the application of vibration on the grinding and dressing processes. The resulting roughness parameters of the ground surfaces and the alumina grinding wheel wear are presented.

This paper proposes for the design of food container packaging using the leaf sheet of the tree as a natural material. The objective of this project is to develop a design for the press and container molding machine, along with a pulling machine specially designed for the processing of leaf sheaf banana. It can control a temperature of 50–150 ºC to test the forming from natural fiber. The temperature used for forming is 100 ºC, and the temperature used to roll the leaf sheaf banana is 120 ºC. The biological material was developed with the aim of adding value and reducing damage. The packaging design complies with the safety and mechanical properties specified in TIS 170 standard. This parameter covers various factors including weight, moisture content, water absorption, radiation resistance, resistivity to scratches, resilience to cracks, elasticity, stretching and mechanic properties. The product case has been thoroughly tested and developed for the production of foodstuffs.

Modification is one of the ways used to actualize oneself in mass products. Motorcycle radiator covers are an interesting component to combine with Batik, which is part of Indonesian culture. This cover has a specific shape. In this study, this process will be carried out by reverse engineering techniques which include 3D scanning, Re-drawing, modification, and production processes. The 3D scanning process was performed by using a handled 3D scanner tool which had a specification of 0.2 m × 0.2 m × 0.2 m to 2 m × 2 m × 2 m scanning volume with 0.45 m to 1.6 m of operation range. The process was optimized by object coloring. The CAD object was re-drawn and evaluated by using a combination of CAD/CAE and their features. Surface generating and editing were among the most useful features used in this work. The result showed that this technique could accommodate the objective of this work.

The trend of online food delivery was famous during the Covid 19 due to the pandemic that forced everybody to stay only in accommodations. Social distancing was a policy that was used in many parts of the world. However, even though the pandemic was spreading everywhere people still needed food to survive. Therefore, ordering the food online and using online food delivery was the way to receive food once the consumer could stay safely at home. Even nowadays, Covid19 is almost gone but the trend of using online food delivery is still famous among many people. This research aimed to investigate the continuous intentional behavior of Thai customers to continue using online food delivery after the Covid-19 crisis. Structured equation modeling (SEM) was used to evaluate data and there are in total of 548 sample respondents by having females 54.2% and males 45.8%, which is a big enough number for SEM analysis. The sample group is Thai customers who have answered the online and offline questionnaire about their behavior to use online food delivery. Results showed that most Thai people still would like to continuously use the online food delivery service because it is convenient and safe while some customers prefer to use it because it can save their time from travel. However, some customers still prefer to go to the restaurant because they can change the atmosphere of their house.

This research aims to develop modeling and prediction for the electrical discharge machining (EDM) process of Ti6Al4V with a graphite electrode. The three models have been developed for the prediction of material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (SR) using two artificial neural network models (ANN_sigmoid and ANN_Relu) and a deep neural network model (DNN). Herein, the four inputs of the network were the discharge current, duty factor, pulse on time, and voltage. Taguchi’s L27 (34) orthogonal array was used to designed and conducted the experiments. Comparing the values predicted with the experimental data indicated that all neural network models provided accurate results. Moreover, this study showed that the DNN model gave the best performance and can successfully predict the MRR, EWR, and SR of the stochastic and complex EDM process.

Slippage problem is one of the most concern problems in a Wheel-Mobile Robot when it is operated under the dynamic situation. This paper proposes the causes of slippage problems occurring by AMR’s operation in various conditions and predicts the slippage distances using ANFIS methodology. Four main factors are concerned and defined as the membership function; speed of motion, directions and conditions of movement, friction and pay loads. ANFIS method is adopted to fit with slippage of the AMR working in the environment such as the shop floor factory. The model was performed by MATLAB with several rules of thumb which were captured from the robotic experts together with documented texts. The system was trained and carried out the fuzzy inference reasoning. The case study was tested in various conditions. It was found that the slippage will be less when the load is less whereas the slippage is high when the play load is heavy. The further study is to simulate the dynamic control using Simulink and compared to the real experiment in the laboratory.

This paper presents a numerical and experimental study of a storage system composed of spherical capsules filled with water placed inside a horizontal cylindrical tank and a working fluid circulation system to charge and dis-charge the storage tank. The simplified one-dimensional model is based on pure conduction in the water subject to boundary conditions of constant temperature or force convection heat transfer on the external surface of the spherical capsules. The mathematical model of spherical capsules with ice thermal energy storage system has been developed for the computer simulation of the energy storage system. The model was then used to predict the optimal capacity of the storage tank and the effect of the spherical capsule diameter, the spherical capsule wall thickness, the spherical capsule material, the inlet or initial temperature, the ice mass fraction, and the time on the charging and discharging processes. The results indicated that the optimal cool energy can be fully stored when the 60 mm of the spherical capsule diameter and 70% of spherical capsule porosity in storage tank. And test performed to note Reynold number, the diameter of the spherical capsules, and the number of the spherical capsules dependencies of two phase and energy storage.

This study investigates the wear patterns of hot forging dies in relation to work-piece temperature, die temperature, and the coefficient of friction. The materials used in the forging process were tool steel grade SKD61 for the dies and general-purpose high-tensile steel with medium strength, grade SCM435, for the work-pieces. The initial sizing of workpieces is 13 mm in diameter and 155 mm in length. The simulation of the forging process was carried out using commercially available software based on the finite volume method. Characteristic values of the parameters in the simulation started with die temperatures of 120 ℃ and 180 ℃, and workpiece temperatures of 850 ℃, 950 ℃, 1050 ℃, and 1150 ℃, respectively. The friction coefficient values used were 0.2, 0.3, and 0.4. The experimental results indicated that at a workpiece temperature of 1150 ℃ and die temperature of 180 ℃, a minimum forging force of 132 KN was required to achieve the desired complete shape in close die forging while minimizing flash. Therefore, the contact pressure distribution stress on the workpiece remained within the fracture threshold curve region due to the minimum operation force during the process. The simulation of the forging process indicated that appropriate parameter adjustments contributed to the reduction of wear mechanisms. By way of comparing the numerical results with the measurements taken from the worn die, the damage coefficient has been evaluated for one of a kind points at the die floor, and a very last value of wear is usually recommended.

This paper proposes the mathematical modelling using Neuro-fuzzy (ANFIS) system for prediction temperature occurring on Al 6061 turning together with experimental study using temperature measurement. The comparison is discussed. Neuro fuzzy system is developed based on the machinist expert opinion rules for a particular material of Al6061on turning process. The experiment study is also created using DOE and tested by thermal image camera modelled IC125LV. The comparison is discussed by the both methodologies. It is found that the cutting parameters of cutting Al6061 related mainly on feed rate. When the feed rate increases, the temperature will increase simultaneously. Therefore, the control temperature of the turning Al6061 can be controlled by the feed rate. The paper presents only on the single cut turning process. It may extend the study on multiple cutting processes to investigate the cumulative heat of temperature and compare to the ANFIS training data. The research study benefits to academic and practitioners to use for setting and control temperature on turning of the Al6061 which is widely used in the auto part industry. The ANFIS system is developed to fit with the cutting conditions on Al6061 and obtain data prediction of the temperature that occurs on the various different conditions. It is found that the cutting temperature of the Al6061 is mainly depended on the feed rate.

Hazardous materials transport company by road. It is necessary to develop a safe road transport system. And have more international standards. Therefore, the Company's risk management planning is the primary mission that must be carried out. Prioritizing risk factors is a crucial component of risk management plan preparation, which considers the importance and prioritizes each factor. Make judgments based on in-built criteria that make it easy to make mistakes. The Analytic Network Process (ANP) is a theory that can solve complex problems. Which decisions influence each other and the feedback process. There is a delay and non-linearity. ANP has a significant scale, which 1 is less critical and chasing down to 9 is very important, respectively. However, there is still ambiguity in rating this importance because we want a score between 1 and 1.5 Will it change the result? Therefore, The Fuzzy Analytic Network Process (FANP) was applied to eliminate the uncertainty of such scoring criteria problems. This research uses a case study of factors affecting hazardous substance transport companies using the FANP to analyze two models, namely 1. Triangular membership function, and 2. Trapezoidal membership function. To compare the results in prioritizing each format.

Aircraft heavy maintenance (AHM) is frequently delayed due to the large number of maintenance tasks involved. This can lead to significant costs for airlines, as maintenance is the third highest annual operating cost. This paper presents a task-based DSM model for solving the complexity of AHM planning. The model uses DSM partitioning analysis to sequence AHM tasks. If coupled blocks are present after the sequencing analysis, the aggregation, decomposition, and tearing methods are used to resolve them. The task-based DSM model also uses heuristic priority rules to determine the priority of tasks and to allocate limited resources. The results of the study show that the developed task-based DSM model performs efficiently compared to the current method in terms of planning lead time and maintenance expected time.

The blended wing body Aircraft (BWB) model is an unconventional aircraft that combines the conventional fuselage and flying wing aircraft design. This BWB model aircraft has an aerofoil-shaped body which contributes to the overall lift during the flight. This unique design of the BWB offers high fuel efficiency, low noise, and a large payload volume for the size of the aircraft. The high fuel efficiency is attained due to its Lift-to-Drag (L/D) ratio which is an important parameter to describe aircraft efficiency. The higher L/D ratio reflects better flying performance which includes flight duration, endurance, and better fuel consumption. The main objective of this work is to analyze the aerodynamic characteristics of our developed BWB model to evaluate its performance at steady flight conditions and at variable pitch angles using CFD analysis. The aerofoil used was NACA 2412. The scope of this study was limited to evaluating only lift, drag, and pressure coefficient values at a speed of 70 m/s at sea level conditions. The results obtained illustrate a higher lift-to-drag ratio following the trend of other studies and research on the Blended-Wing-Body aircraft (BWB) model. The maximum lift-to-drag ratio obtained was 13.5 at 5° angle of attack (AOA). And then starts to decrease with a further increase in angle of attack. The L/D ratio is also supported by the pressure contour graphs of the lower and upper surfaces obtained. Overall, the result obtained correlates with other previous studies done on BWB model aircraft.

Purpose: This paper proposes the novel study by using Case-based reasoning with fuzzy logic knowledge-based acquisition for adaptable die design on cold forging fastener for bi-material. New knowledge and parameters are validated by DEFORM simulation which is widely used for practitioners.Design/methodology/approach: Case-based reasoning is applied to collect data, classify and store in the case library before retrieving them to be a pattern, modify and adapt the most similar case to fit a new case. In addition, the cases are also created by Fuzzy logic which assists to create new knowledge and parameters for new bi-material that never applied to industry. DEFORM simulation is used to verify the feasible new process.Findings: It was found that CBR is effective to combine previous experience and modify to solve current problem that have not occur. The solution is used, tested, modified and store in the library can retrieve for the future use. Light-weight with bi-material data for forging is developed for academic and practitioner references.Research limitations/implications: The limitation is that the new case of knowledge should be verify by experience before using effectively.Practical implications: The CBR concept has implemented by the case study to verify the library knowledge workable in practical routine process design with new material that have not design and production before.Originality/value: The new concept for new material for cold forging design is developed to deal with design problem without data and knowledge availability. Analogy solution by CBR approach is the best alternative and adopted to this work. In addition, knowledge was created and generated by fuzzy logic and verification by DEFORM.

Advanced Air Mobility (AAM) is an air transportation system that moves people and cargo in areas that have not previously been or are still little served by using new and revolutionary aircraft, such as electric aircraft, urban air mobility, and cargo drone. AAM can be a solution for several of Indonesia’s problems such as emissions and congestion. However, how AAM can be developed according to the needs of Indonesia and be integrated into existing and possible future air transportation in Indonesia still need to be further explored. This paper is to discuss the preliminary effort of Advanced Air Mobility (AAM) development using ModelBased Systems Engineering (MBSE) development framework carried out in Indonesia, especially related to pre-conceptual study. This includes the development of initial MBSE framework, followed by the initial implementation of the framework to AAM case studies. Two pre-conceptual studies are discussed, which are cargo drone and Urban Air Mobility (UAM). In this paper, several pre-conceptual aspects, such as stakeholder, needs, and concept of operations, has been discussed. Scope of AAM has been identified and proposed in this paper. By using System Modelling Language (SysML) and MBSE, each case of AAM can be categorized more structurally. This paper only discusses Urban Air Mobility and Cargo Drone. Conceptual aspects of AAM may also need to be explored. However, to fulfil this, a complete and comprehensive database of AAM is needed to be developed. Is mainly associated with identifying the potential of Advance Air Mobility and its associated pre-conceptual aspect such as stakeholders and concept of operations, in the case of Indonesia. A categorization of Advance Air Mobility is made so that in the future, each categorization can be connected to a specific set of stakeholders, needs, and requirements, which in turn will drive objectives, constraints, and design solution spaces.

Cosmetics are crucial for daily of life everywhere in the world for the main propose of body’s protection from heat and sunlight. Presently, people use cosmetics for personal hygiene, attractiveness, self-esteem and promote tranquility. In addition, cosmetics are produced locally with domestic materials for eco-products and environment protection. Varieties of cosmetic’s Thai brands are promoted in the local and global marketplace whereas customers choose them by appreciation. This paper proposes the principle component analysis (PCA) strategy to present the emotional perception of the local cosmetic product. The data collected is analyzed by using statbox and concluded by the remarks for the future conceptual product design and development to meet the customer requirement and perception. The local cosmetics in Thailand were found to be in the perception of safety, beauty, quality and eco-natural products.

The maintenance, archiving and usage of the design drawings is cumbersome in physical form in different industries for longer period. It is hard to extract information by simple scanning of drawing sheets. Converting them to their digital formats such as Computer-Aided Design (CAD), with needed knowledge extraction can solve this problem. The conversion of these machine drawings to its digital form is a crucial challenge which requires advanced techniques. This research proposes an innovative methodology utilizing Deep Learning methods. The approach employs object detection model, such as Yolov7, Faster R-CNN, to detect physical drawing objects present in the images followed by, edge detection algorithms such as canny filter to extract and refine the identified lines from the drawing region and curve detection techniques to detect circle. Also ornaments (complex shapes) within the drawings are extracted. To ensure comprehensive conversion, an Optical Character Recognition (OCR) tool is integrated to identify and extract the text elements from the drawings. The extracted data which includes the lines, shapes and text is consolidated and stored in a structured comma separated values (csv) file format. The accuracy and the efficiency of conversion is evaluated. Through this, conversion can be automated to help organizations enhance their productivity, facilitate seamless collaborations and preserve valuable design information in a digital format easily accessible. Overall, this study contributes to the advancement of CAD conversions, providing accurate results from the translating process. Future research can focus on handling diverse drawing types, enhanced accuracy in shape and line detection and extraction.

The Industrial Internet of Things (IIoT) has emerged as a breakthrough technology in the industrial industry, providing new prospects for improving production processes, increasing operational efficiency, and enabling data-driven decision-making. This paper aims to explore the existing body of knowledge on IIoT in manufacturing, examining its applications, benefits, challenges, and future prospects. This research provides insights into the current state of IIoT implementation, its potential implications in food packing production line control and monitoring. Data analytics and visualization are used to convey in-line monitoring and management of the production line's productivity for food packaging. It entails employing automated tools, sensors, and statistical techniques to look for patterns, anomalies, and potential opportunities for process optimization. Graphical interfaces and dashboards are used to present the studied data for easy comprehension during real-time production line control and monitoring.

This research aims to assess suitable axes for model assembly in a cyber-physical factory by employing a virtual reality platform in collaboration with the studio program. This research involves the assembly of cyber-physical model libraries. The model libraries are factory and application, which consist of a high-bay warehouse, module drill, camera inspection, robot assembly station, module back cover, module muscle press, and module turn. In this experiment, a gyroscope sensor uses to record wrist movements and assess the experiment's satisfaction. The 30 participants had less experience using the virtual reality platform. From the results of this experiment, the participants accept that the use of the virtual reality platform is satisfactory and highly effective for virtualization. Working in a sitting position has obstacles and is inconvenient to experiment with; using a virtual reality platform can prevent damage to equipment and ensure operators’ safety before actual operations.

Recommender systems are widely used users’ lives easier by assisting them in narrowing down their product of choice from the various alternatives. Recommender systems (RSs) are information search and filtering technologies that propose items that may be useful to a user. Several companies use them to advertise their products. This work focuses on comparing deep learning algorithms which are used to develop recommendation systems. Four major algorithms are compared - Restricted Boltzmann Machine, Auto-encoder, Convolutional, Attention, and Recurrent Neural Networks. Our results show when a dataset is used which majorly consists of images, CNN (0.85 accuracy) works perfectly. Among RNN (0.81 accuracy), ABRS (0.59 accuracy), and RBM (0.94 accuracy) - RBM performs the best for the given dataset.

The emergence of cyber-physical systems (CPS) has revolutionized the development of smart systems. These systems are progressively adopting data-driven intelligent operations. The cyber part combines a set of data with embedded computing to monitor and control the physical components of the system. Through feedback loops, it enables the system to adapt its operational modes based on varying usage and operational scenarios, while striving to achieve the desired system performance. A system operation mode characterizes the behavior of a system at a specific point in time, based on the actual system configurations. With a specific focus on a conventional rice milling machine used in the local community, this paper aims to fulfill three primary objectives. Firstly, it seeks to identify a comprehensive set of parameters for operating a CPS-based milling machine. Secondly, it aims to define the system operation modes during the control setting stage of the machine across various operational scenarios. The potential system operation modes are determined by the diverse levels of multiple measured parameters, which are carefully selected by the rice milling process. Additionally, two external factors, namely rice moisture content and paddy seed variety, are taken into consideration. The variations in system operation modes can be aligned with the quality aspects of the final rice products. Finally, to delve deeper into the investigation, the study utilizes a design of experiment approach to examine the factors of the state of operation that significantly influence the quality of the rice grains. The analysis revealed that three factors including the area of the hopper feed, the rice adjuster, and the gap adjuster, exert a substantial impact on the number of broken grains.

During the COVID-19 pandemic, the harshness of home confinement was alleviated by transferring a range of activities online, including education. This paper investigates how teachers and students perceived themselves within this online learning environment, their interactions, self-efficacy and satisfaction. This was achieved via a study surveying 200 students and teachers in countries worldwide (with a reliability coefficient of 0.93). SPSS correlation analysis, ANOVA and factor analysis were conducted. Herzberg’s two-factor theory of job satisfaction was tested, and it was found that there were two key drivers, intrinsic and extrinsic factors. Additionally, the study revealed that the key indicating factors for student satisfaction were online course content and structure and teacher-student interaction. For teachers, self-efficacy was found to be the most influential factor in satisfaction, along with other indicators, including teacher perception of online teaching platforms and students’ performance.