Micropropagation and In Vitro Inflorescence of Pentas lanceolata

In this study, different concentrations of 6-benzyladenine (BA) on in vitro shoot and inflorescence inductions of P. lanceolata were investigated. The in vivo and in vitro floral characteristics of this plant were also compared. Nodal explants of P. lanceolata were cultured vertically with the cut ends inserted into semi-solid Murashige and Skoog (MS) medium supplemented with 0, 0.5, 1, 2, 4, and 8 mg L–1 BA. The results showed that the explants formed the highest numbers of shoots even when cultured in MS basal medium without any addition of BA, while the shoots formed in the explants cultured in MS medium supplemented with 1 mg L–1 BA were the longest. No inflorescence was found in the shoots cultured in MS medium supplemented with 8 mg L–1 BA, while the highest percentage of inflorescence induction was found in the shoots cultured in the medium supplemented with 0.5 mg L–1 BA. The apperances of in vivo and in vitro flowers of P. lanceolata were the same in many aspects except that the number of flower/inflorescence formed was different. In addition, water accumulation was observed only inside the in vitro flowers. Water deposit in the long tubular structure of P. lanceolata flower could cause anther injury, suggesting that flowers developed in vitro may not always produce pollen.

Optimization of Design for Air Gap Sensor Using the Response Surface Methodology

In Hard Disk Drive (HDD) manufacturing, there is always a concern about the cutting defects that are caused by residual cutting chips. Only a small amount of 10 μm chips (act as the air gap) can cause the workpiece to tilt and shift from the correct position, and thus affect the dimension of the workpiece (mainly the Base HDD). For this reason, researchers adapted the adjustable micrometer as a simulation device that resembles the air gap for the design of the Air Gap Sensor Module. The design of experiments using response surface methodology will be studied to confirm the appropriate factors of the prototype. This study reports the optimization of the main factors that affect Air Gap Sensor Module condition: Air Nozzle Diameter 2.303 mm, Air Pressure 0.1 MPa, and Sampling Time 645 ms, which has a high square of the coefficient correlation (R-squared = 99.0%) with a close relationship between gap distance and air pressure. The relationship between these variables is mostly linear. The R-squared error percentage of actual value is less than 0.93% compared to predicted value. The mathematical model results and experimental values were consistent and able to predict response variables. The Air Gap Sensor Module can provide the measurement results in micron ccuracy and displays light and beep to confirm as acceptable or reject gap conditions with the uncertainty of measurement ± 0.001 mm.

Triacetin as Lubricant Additive: Slipping Friction between Metal Pairs under Boundary Lubrication

Friction between rubbing pairs plays a key role in operating machines in an efficient approach. In some intended works or occasional circumstances, slipping friction may occur during dry or boundary lubrication. Lubricating mechanical equipment using proper and efficient lubricant agents is tremendously necessary. This work explores the synthesized triacetin as an additive for lubricant under slipping friction between steel rollers and aluminum, brass, copper, and stainless-steel rods under boundary lubrication. The metal surface morphology under the lubricant with 10% triacetin additive covering roughness periphery is investigated by Field Emission Scanning Electron Microscope imaging. In the dry slipping condition, the friction coefficient is lower for the copper-steel pair compared to the aluminum-steel combination. Compared to the absence of triacetin additive, the steel roller combinations with the rod metal specimens undergoing boundary lubrication with 10% triacetin additive in the lubricant can reduce the slipping friction coefficient by up to 49.2% in the case of steel roller and brass rod pair. The quantitative influences of triacetin additive on metal rubbing pair friction coefficients under boundary lubrication are inversely exponential correlated to triacetin additive, varying in the range of 0 to 10% v/v.

Continuous Encapsulation of Vitamin E Using Polycaprolactone and Tween 20 in a Micro-Channel

Encapsulation of vitamin E is the preservation of the biological activities of vitamin E for various applications. In the first part of this research, factors affecting the batch encapsulation of vitamin E, including PCL concentration, the concentration of Tween 20, and the volumetric ratio of aqueous phase to organic phase were experimentally investigated. The Box-Behnken experimental design and response surface methodology were implemented to determine the optimal operating conditions of the batch encapsulation. At the optimal conditions, the percentage of vitamin E encapsulation (%EC) was 98.69%, using the PCL concentration, the Tween 20 concentration, and the volumetric ratio of aqueous phase to organic phase of 3.6 g/L, 0.6 g/L, and 0.9 mL: 1 mL, respectively. The second part is to enhance the productivity by applying the optimized formulation of vitamin E encapsulation in a continuous process using a micro-channel encapsulator. The effect of residence time was investigated. At the residence time of 1 s, the percentage of vitamin E encapsulation of 97.28% and the productivity of 153.61 mg/(mL∙min) were achieved.

Watermelon Sorting Process by Frequency Identification and Artificial Neural Network

This research aims to enhance the watermelon’s quality selection process, which was traditionally conducted by knocking the watermelon fruit and sort out by the sound’s character. The proposed method in this research is generating the sound spectrum through the watermelon and then analyzes the response signal’s frequency and the amplitude by Fast Fourier Transform (FFT). Then the obtained data were used to train and verify the neural network processor. The result shows that, the frequencies of 129 and 172 Hz were suit to be used in the comparison. Thirty watermelons, which were randomly selected from the orchard, were used to create a data set, and then were cut to manually check and match to the fruits’ quality. The 129 Hz frequency gave the response ranging from 13.57 and above in 3 groups of watermelons quality, including, not fully ripened, fully ripened, and close to rotten watermelons. When the 172 Hz gave the response between 11.11–12.72 in not fully ripened watermelons and those of 13.00 or more in the group of close to rotten and hollow watermelons. The response was then used as a training condition for the artificial neural network processor of the sorting machine prototype. The verification results provided a reasonable prediction of the ripeness level of watermelon and can be used as a pilot prototype to improve the efficiency of the tools to obtain a modern-watermelon quality selection tool, which could enhance the competitiveness of the local farmers on the product quality control.

GRNN Prediction Model for Temperature-Induced Deformation of CRTS II Unballasted Slab Track

The General Regression Neural Network (GRNN) is one of the algorithms of artificial neural networks (ANN) that receives much attention in prediction applications. This research used the GRNN to predict the temperatureinduced deformation of unballasted track structures based on experimental data considering external weather conditions, such as sunshine duration, rain conditions, daily maximum temperature, daily minimum temperature, and daily average wind speed. The GRNN network predicts the average absolute error of the prediction results (0.0318 ℃), the maximum absolute error (1.7729 ℃), and the GRNN prediction sample mean squared error (0.070701). The average relative error is 0.32%. The finding of this study shows that the GRNN prediction method has good accuracy and robustness. Furthermore, it can promote the research of unballasted track temperature fields that are related to concrete structures.

Confidence Intervals for the Ratio of the Coefficients of Variation of Inverse-Gamma Distributions

Herein, we present four methods for constructing confidence intervals for the ratio of the coefficients of variation of inverse-gamma distributions using the percentile bootstrap, fiducial quantities, and Bayesian methods based on the Jeffreys and uniform priors. We compared their performances using coverage probabilities and expected lengths via simulation studies. The results show that the confidence intervals constructed with the Bayesian method based on the uniform prior and fiducial quantities performed better than those constructed with the Bayesian method based on the Jeffreys prior and the percentile bootstrap. Rainfall data from Thailand was used to illustrate the efficacies of the proposed methods.

Injury Risks of Rear Occupant in Typical Four-door Type of Pick-up Truck under Vehicle Collision

This research explores the injury risks of occupants in four-door type of pick-up truck using experimental based collision with Hybrid III dummy for occupant injury indicators. The full-sized crash laboratory was developed to conduct full frontal impact based on standard regulation. To verify performance of full-sized crash laboratory and vehicle deceleration, low and high speed tests were conducted at the same vehicle. The Hybrid III dummy with head and chest sensors was used at the rear outboard seat during high speed test. Consequently, the deflection and thoracic viscous criteria, which represent the chest injuries, are up to 93 mm and 3.96 m/s, respectively, high beyond the standard requirement. Moreover, the most important finding of this research is that the four-door pickup truck is subjected to the 2nd impact up to 116.51 G at dummy head with higher resultant acceleration than the 1st impact (65.62 G) due to the limited space behind the rear headrest and thinner backrest of rear seat. This research also investigates the post-crash results to illustrate the suggestive idea for improving crashworthiness of future design resulting in mitigation of occupant injuries.

Avoiding Covid-19 Using a 3D Digital Mock Up and Augmented Reality with Cobot in Digital Factory

The Fourth Industrial Revolution or Industry 4.0 is extremely relevant and important in manufacturing for several reasons. Failing to adopt the technology of the Fourth Industrial Revolution can cause organizations to fall behind, as their operations are not digitized enough in benchmarking competitors. A major industry as bicycle manufacturing needs to be transformed into a digital factory in order to keep up with the evolving technology. The objectives of this research are in designing a 3D digital mock up and Augmented Reality (AR) for bicycle frame production in the form of digital factory for increasing production capability by decreasing the break-even point whilst avoiding Covid-19 contraction using Tecnomatix Plant Simulation and Unity 3D programs. This research constructed three alternative digital factory layouts that are designed by using a 3D simulation program. The risk of Covid-19 contraction points and the three layouts of cost per unit are analyzed. The results show that the break-even point of the first to the third layouts with Automated Guided Vehicle (AGV) are 26,580, 26,322 and 25,354 units respectively. The result of the risk about Covid-19 contraction points from the first to the third layout with AGV are 21,272, 2,872 and 0 points respectively. This means the most appropriate layout for bicycle frame production is the third layout due to the best break-even point that can significantly avoid Covid-19 contraction. The benefit of this research is to integrate a 3D digital mock up, AR and Cobot including AGV to assist the resilience of operations with a dynamic industrial environment.

Lubricant Evaluation Technique for Single Point Incremental Forming Process

Single-point Incremental Forming (SPIF) is highly flexible dieless forming process suitable for a small batch production. The higher the feed rate and tool rotational speed, the higher the production rate will be. Therefore, the selection of the suitable lubricant is a key important factor to maintain the formability of the material when increasing the feed rate and tool rotational speed. This paper proposes the technique to evaluate and later on select the proper lubricant for these conditions. This technique was divided into two phases; 1) screening, and 2) stabilization. The screening phase is a quick method for preliminary selection of the lubricants. The stabilizing phase is a step to evaluate reliability as well as ensure efficiency of the lubricant throughout the process, because of the significant increase of the forming temperature which affects directly to the performance of the lubricant. Two types of lubricants, namely solid (Graphite) and liquid (Callington Calform NF-206) lubricants mixed with the base oil (coconut oil) at different ratios were tested. The cold rolled hot-dipped zinc-coated steel sheet with thickness of 0.176 mm. and wall angles of 45, 50, 55 and 60 degrees with the depth of each wall angle of 5 mm were used. During the screening phase, the fifteen mixtures firstly were tested by using the achieved maximum wall angles without fracture as a criterion. Later on, the lubricant mixtures which could successfully form at the wall angle of 60 degrees with the forming depth of 20 mm would be tested in the stabilization phase to evaluate the formability and the forming temperature. The results showed that during the screening phase 11 lubricants could perform successfully, while the stabilization phase with the wall angle of 60 degrees only 3 lubricants could successfully form the workpiece. Therefore, this evaluation technique could help to evaluate and, for later on, be a criterion to select the select lubricant.