Research on the Impact of Digital Technology and Servitization on the Performance of Manufacturing Enterprises

This article mainly discusses the impact of digital technology and service-oriented on the performance of manufacturing enterprises.It first elaborates on the background of the trend of service-oriented manufacturing and the significance of its enterprises.Then,based on the impact of digital technology on the performance of manufacturing enterprises,several practical and feasible measures are proposed,mainly focusing on the long-term layout of service-oriented,shortening the low period,enhancing the competitive awareness of state-owned manufacturing enterprises,improving the driving force transformation,achieving simultaneous progress digitally,configuring digital and service-oriented elements,and eliminating the monopoly of digital resources.Followed by lowering the threshold for private enterprise resource acquisition,promoting financial digital development,breaking the financial dilemma of service-oriented manufacturing,continuously improving the performance level of manufacturing enterprises,and promoting the development of manufacturing enterprises.

Research on the Impact of Digital Transformation on the Performance of Manufacturing Enterprises

To address the challenges faced by manufacturing enterprises in digital transformation,this paper analyzes the relationship between digital transformation and enterprise performance.Using panel data from domestic A-share-listed manufacturing enterprises from 2012 to 2022,two hypotheses were proposed.The analysis and verification revealed that digital transformation in manufacturing enterprises can enhance performance and reduce costs.Based on the impact of digital transformation on manufacturing enterprise performance,optimization suggestions are proposed to guide future digital transformation and performance improvement efforts in these enterprises.

The Impact of E-Commerce Live Broadcasts on Consumers’Purchase Intention

E-commerce live broadcast has an important influence on consumers’purchase intention.The three dimensions of live broadcast content in the broadcast room are the number of comments,product quality,and live content as independent variables.A theoretical model is constructed with perceived value and risk as intermediaries and the consumers’purchase intention as the dependent variable,and corresponding hypotheses are put forward.We designed the scale,collected relevant data,and tested the model hypothesis using Statistical Package for Social Sciences(SPSS)and Analysis of Moment Structure(AMOS)software.The study found that the number of comments and product quality had a significant impact on perceived value,perceived risk,and consumers’purchase intention.From this conclusion,it is suggested that businesses should control the number of comments,strengthen the product quality of comments,and distinguish the repetition degree of the content of live broadcasts.

Marketing Strategy Analysis of Migu Video App Based on 4I Theory

With the increasing maturity of 5G technology and the comprehensive development of video apps on the Internet,the landscape of video app downloads shows that Migu Video lags behind giants like iQiyi,Tencent Video,Youku,and Mango TV.However,during the Tokyo Olympics and the Beijing Winter Olympics,Migu Video’s focus on sports coverage and commentary led to increased public use and app downloads.This study analyzes the marketing status and strategy of the Migu Video App.It conducts a detailed analysis using the 4I theory-interest,interaction,individuality,and initiative-and proposes a brand marketing strategy tailored for Migu Video.This aims to provide insights into the marketing strategies of other mobile Internet companies.

Potential of Thai Bast Fibers for Injection Molded PLA Composites

Thailand has a huge variability of bast fiber plants,some of which have been little researched regarding their applicability in composites.Bast fiber(bundle)s from different species were investigated and incorporated into a polylactide(PLA)matrix by injection molding.Hemp and kenaf were used as well-studied fibers,while roselle,Fryxell and paper mulberry are less extensively characterized.Tensile strength,tensile modulus and interfacial shear strength(IFSS)of single fiber(bundle)s were highest for hemp,followed by kenaf,roselle,Fryxell and paper mulberry.Despite the lower tensile strength and IFSS of paper mulberry,the highest tensile strength was achieved for the paper mulberry/PLA composite followed by hemp/PLA.Scanning electron microscope(SEM)analyses showed that the single cells in paper mulberry fiber bundles,in contrast to the other fiber types investigated,were only partially bonded to each other,which explains the lower strength of the fiber bundles.The higher aspect ratio of fiber(bundle)s of paper mulberry in the PLA composite can explain the good composite characteristics.Apart from hemp,paper mulberry shows the best reinforcing effect in the PLA matrix and offers interesting potential for composite applications.Compared to neat PLA,the tensile strength could be increased by 24%and the tensile modulus by 54%.

Stochastic Framework for Solving the Prey-Predator Delay Differential Model of Holling Type-Ⅲ

The current research aims to implement the numerical resultsfor the Holling third kind of functional response delay differential modelutilizing a stochastic framework based on Levenberg-Marquardt backpropagationneural networks (LVMBPNNs). The nonlinear model depends uponthree dynamics, prey, predator, and the impact of the recent past. Threedifferent cases based on the delay differential system with the Holling 3^(rd) type of the functional response have been used to solve through the proposedLVMBPNNs solver. The statistic computing framework is provided byselecting 12%, 11%, and 77% for training, testing, and verification. Thirteennumbers of neurons have been used based on the input, hidden, and outputlayers structure for solving the delay differential model with the Holling 3rdtype of functional response. The correctness of the proposed stochastic schemeis observed by using the comparison performances of the proposed and referencedata-based Adam numerical results. The authentication and precision ofthe proposed solver are approved by analyzing the state transitions, regressionperformances, correlation actions, mean square error, and error histograms.

Modified DS np Chart Using Generalized Multiple Dependent State Sampling under Time Truncated Life Test

This study presents the design of a modified attributed control chart based on a double sampling(DS)np chart applied in combination with generalized multiple dependent state(GMDS)sampling to monitor the mean life of the product based on the time truncated life test employing theWeibull distribution.The control chart developed supports the examination of the mean lifespan variation for a particular product in the process of manufacturing.Three control limit levels are used:the warning control limit,inner control limit,and outer control limit.Together,they enhance the capability for variation detection.A genetic algorithm can be used for optimization during the in-control process,whereby the optimal parameters can be established for the proposed control chart.The control chart performance is assessed using the average run length,while the influence of the model parameters upon the control chart solution is assessed via sensitivity analysis based on an orthogonal experimental design withmultiple linear regression.A comparative study was conducted based on the out-of-control average run length,in which the developed control chart offered greater sensitivity in the detection of process shifts while making use of smaller samples on average than is the case for existing control charts.Finally,to exhibit the utility of the developed control chart,this paper presents its application using simulated data with parameters drawn from the real set of data.

Blood Pressure Estimation with Phonocardiogram on CNN-Based Approach

Monitoring blood pressure is a critical aspect of safeguarding an individual’s health,as early detection of abnormal blood pressure levels facilitates timely medical intervention,ultimately leading to a reduction in mortality rates associated with cardiovascular diseases.Consequently,the development of a robust and continuous blood pressure monitoring system holds paramount significance.In the context of this research paper,we introduce an innovative deep learning regression model that harnesses phonocardiogram(PCG)data to achieve precise blood pressure estimation.Our novel approach incorporates a convolutional neural network(CNN)-based regression model,which not only enhances its adaptability to spatial variations but also empowers it to capture intricate patterns within the PCG signals.These advancements contribute significantly to the overall accuracy of blood pressure estimation.To substantiate the effectiveness of our proposed method,we meticulously gathered PCG signal data from 78 volunteers,adhering to the ethical guidelines of Suranaree University of Technology(Human Research Ethics number EC-65-78).Subsequently,we rigorously preprocessed the dataset to ensure its integrity.We further employed a K-fold cross-validation procedure for data division and alignment,combining the resulting datasets with a CNNfor blood pressure estimation.The experimental results are highly promising,yielding aMeanAbsolute Error(MAE)and standard deviation(STD)of approximately 10.69±7.23 mmHg for systolic pressure and 6.89±5.22 mmHg for diastolic pressure.Our study underscores the potential for precise blood pressure estimation,particularly using PCG signals,paving the way for a practical,non-invasive method with broad applicability in the healthcare domain.Early detection of abnormal blood pressure levels can facilitate timely medical interventions,ultimately reducing cardiovascular disease-related mortality rates.

Antioxidant activity,total phenolic,and resveratrol content in five cultivars of peanut sprouts

Objective: To investigate the change in total phenolic compounds, antioxidant activity,and resveratrol content of five different germinated peanut cultivars.Methods: The germinated sprouts of five peanut cultivars(Kalasin1, Kalasin2, Konkaen,Konkaen4, and Tainan9) were extracted with 80% ethanol and collected as crude extract.The antioxidant capacities were determined with 2,2-diphenyl-1-picrylhydrazyl and ferric ion reducing antioxidant power method.The total phenolic compound was measured using the Folin–Ciocalteau assay.The qualification and quantification of resveratrol was performed by high performance liquid chromatography method.Results: Among the five cultivars, a three-day germination of Kalasin1 showed the highest phenolic content [(40.67 ± 2.62) mg gallic acid/g dry weight], expressed the highest 2,2-diphenyl-1-picrylhydrazyl antioxidant value [(80.51 ± 1.47) mmol/L Trolox/g dry weight], and ferric ion reducing antioxidant power antioxidant value [(171.33 ± 8.59)mmol/L ascorbic acid/g dry weight].However, the high performance liquid chromatography result of Kalasin2 significantly increased to the highest resveratrol content of(6.44 ± 1.26) mg/g dry weight on the second day of germination.Conclusions: The variation of phytochemical content in the peanut sprout is due to the effect of the peanut cultivar and the germination period.

Optimization of gas tungsten arc welding parameters for the dissimilar welding between AISI 304 and AISI 201 stainless steels

This present study applied gas tungsten arc welding in order to join AISI 304 and AISI 201 stainless steels.The objective was to find the optimum welding condition that gave a weld bead in accordance with DIN EN ISO 25817 quality level B, pitting corrosion potential of the weld metal of not less than that of the AISI304 base metal and a ratio of delta-ferrite in austenite matrix of the weld metal of not lower than 3%.Such a ratio is a criterion widely accepted to protect the weld metal from solidification cracking. At the welding current of 75 A and by using pure argon as a shielding gas 0 to 8 vol.% and applying a welding speed in the range of 2-3.5 mm·s^(-1) was found to give a complete weld bead with an increased depthper-width ratio(promote weldability). For welding speed in the range of 3 and 3.5 mm·s^(-1)(promote corrosion resistance). Increasing the welding speed in such a range decreased the amount of delta-ferrite in the austenite matrix, and increased the pitting corrosion potential of the weld metal to be 302 mV_(SCE).This value was still lower than the pitting corrosion potential of the AISI 304 base metal. Mixing nitrogen in argon shielding gas increased the nitrogen content in the weld. The optimum condition was found when using a welding speed of 3 mm· s^(-1) and mixing 1 vol.% of nitrogen in the argon shielding gas(promote weldability and corrosion resistance). Pitted areas after potentiodynamic test were observed in the austenite in which its Cr content was relatively low.

Field testing of stiffened deep cement mixing piles under lateral cyclic loading

Construction of seaside and underground wall bracing often uses stiffened deep cement mixed columns （SDCM）. This research investigates methods used to improve the level of bearing capacity of these SDCM when subjected to cyclic lateral loading via various types of stiffer cores. Eight piles, two deep cement mixed piles and six stiffened deep cement mixing piles with three different types of cores, H shape cross section prestressed concrete, steel pipe, and H-beam steel, were embedded though soft clay into medium-hard clay on site in Thailand. Cyclic horizontal loading was gradually applied until pile failure and the hysteresis loops of lateral load vs. lateral deformation were recorded. The lateral carrying capacities of the SDCM piles with an H-beam steel core increased by 3-4 times that of the DCM piles. This field research clearly shows that using H-beam steel as a stiffer core for SDCM piles is the best method to improve its lateral carrying capacity, ductility and energy dissipation capacity.

Research and development of gas induced semi-solid process for industrial applications

Several rheocasting processes are developed or applied worldwide in the metal forming industry.One of the new rheocasting processes is the gas induced semi-solid(GISS) process.The GISS process utilizes the principle of rapid heat extraction and vigorous local extraction using the injection of fine gas bubbles through a graphite diffuser.Several forming processes such as die casting,squeeze casting,gravity casting,and rheo-extrusion of the semi-solid slurries prepared by the GISS process have also been conducted.The GISS process is capable of processing various alloys including cast aluminum alloys,die casting aluminum alloys,wrought aluminum alloys,and zinc alloys.The GISS process is currently developed to be used commercially in the industry with the focus on forming semi-solid slurries containing low fractions solid(< 0.25) into parts.The research and development activities of the GISS process were discussed and the status of the industrial developments of this process was reported.

Industrial development of gas induced semi-solid process

The gas induced semi-solid(GISS) is a rheocasting process that produces semi-solid slurry by applying fine gas bubble injection through a graphite diffuser.The process is developed to be used in the die casting industry.To apply the GISS process with a die casting process,a GISS maker unit is designed and attached to a conventional die casting machine with little modifications.The commercial parts are developed and produced by the GISS die casting process.The GISS die casting shows the feasibility to produce industrial parts with aluminum 7075 and A356 with lower porosity than liquid die casting.

Feasibility of semi-solid die casting of ADC12 aluminum alloy

The feasibility of semi-solid die casting of ADC12 aluminum alloy was studied. The effects of plunger speed, gate thickness, and solid fraction of the slurry on the defects were determined. The defects investigated are gas and shrinkage porosity. In the experiments, semi-solid slurry was prepared by the gas-induced semi-solid （GISS） technique. Then, the slurry was transferred to the shot sleeve and injected into the die. The die and shot sleeve temperatures were kept at 180 ℃ and 250 ℃, respectively. The results show that the samples produced by the GISS die casting give little porosity, no blister and uniform microstructure. From all the results, it can be concluded that the GISS process is feasible to apply in the ADC12 aluminum die casting process. In addition, the GISS process can give improved properties such as decreased porosity and increased microstructure uniformity.

Effect of grinding on chemical and physical properties of rice husk ash

The effect of grinding on the chemical and physical properties of rice husk ash was studied. Four rice husk ashes with different finenesses, i.e. coarse original rice husk ash （RHA0）, RHA1, RHA2, and RHA3 were used for the study. Ordinary Portland cement （OPC） was partially replaced with rice husk ash at 20% by weight of binder. The water to binder ratio （W/B） of the mortar was maintained at 110%±5% with flow table test. Specific gravity, fineness, chemical properties, compressive strength, and porosity test of mortars were determined. The differences in chemical composition of the rice husk ashes with different finenesses from the same batch are small. The use of RHA3 produces the mortars with good strength and low porosity. The strength of the mortar improves with partial replacement of RHA3 in comparison with normal coarse rice husk ash. The use of RHA3 results in a strong and dense mortar, which is due to the better dispersion and filling effect, as well as an increase in the pozzolanic reaction.

Influence of bismuth on microstructure,thermal properties,mechanical performance,and interfacial behavior of SAC305−xBiCu solder joints

This research sought to improve the properties of SAC305 solder joints by the addition of 1 and 2 wt.%Bi.The effects of bismuth doping on the microstructure,thermal properties,and mechanical performance of the SAC305−xBiCu solder joints were investigated.Bi-doping modified the microstructure of the solder joints by refining the primaryβ-Sn and eutectic phases.Bi-doping below 2 wt.%dissolved in theβ-Sn matrix and formed a solid solution,whereas Bi additions equal to or greater than 2 wt.%formed Bi precipitates in theβ-Sn matrix.Solid solution strengthening and precipitation strengthening mechanisms in theβ-Sn matrix increased the ultimate tensile strength and microhardness of the alloy from 35.7 MPa and 12.6 HV to 55.3 MPa and 20.8 HV,respectively,but elongation decreased from 24.6%to 16.1%.The fracture surface of a solder joint containing 2 wt.%Bi was typical of a brittle failure rather than a ductile failure.The interfacial layer of all solder joints comprised two parallel IMC layers:a layer of Cu6Sn5 and a layer of Cu3Sn.The interfacial layer was thinner and the shear strength was greater in SAC305−xBiCu joints than in SAC305Cu solder joints.Therefore,small addition of Bi refined microstructure,reduced melting temperature and improved the mechanical performance of SAC305Cu solder joints.

Algorithmic Scheme for Concurrent Detection and Classification of Printed Circuit Board Defects

An ideal printed circuit board(PCB)defect inspection system can detect defects and classify PCB defect types.Existing defect inspection technologies can identify defects but fail to classify all PCB defect types.This research thus proposes an algorithmic scheme that can detect and categorize all 14-known PCB defect types.In the proposed algorithmic scheme,fuzzy cmeans clustering is used for image segmentation via image subtraction prior to defect detection.Arithmetic and logic operations,the circle hough transform(CHT),morphological reconstruction(MR),and connected component labeling(CCL)are used in defect classification.The algorithmic scheme achieves 100%defect detection and 99.05%defect classification accuracies.The novelty of this research lies in the concurrent use of CHT,MR,and CCL algorithms to accurately detect and classify all 14-known PCB defect types and determine the defect characteristics such as the location,area,and nature of defects.This information is helpful in electronic parts manufacturing for finding the root causes of PCB defects and appropriately adjusting the manufacturing process.Moreover,the algorithmic scheme can be integrated into machine vision to streamline the manufacturing process,improve the PCB quality,and lower the production cost.

Kriging Surrogate-Based Genetic Algorithm Optimization for Blade Design of a Horizontal Axis Wind Turbine

Horizontal axis wind turbines are some of the most widely used clean energy generators in the world.Horizontal axis wind turbine blades need to be designed for optimization in order to maximize efficiency and simultaneously minimize the cost of energy.This work presents the optimization of new MEXICO blades for a horizontal axis wind turbine at the wind speed of 10 m/s.The optimization problem is posed to maximize the power coefficient while the design variables are twist angles on the blade radius and rotating axis positions on a chord length of the airfoils.Computational fluid dynamics was used for the aerodynamic simulation.Surrogate-assisted optimization was applied to reduce computational time.A surrogate model called a Kriging model,using a Gaussian correlation function along with various regression models,was applied while a genetic algorithm was used as an optimizer.The results obtained in this study are discussed and compared with those obtained from the original model.It was found that the Kriging model with linear regression gives better results than the Kriging model with second-order polynomial regression.The optimum blade obtained in this study showed better performance than the original blade at a low wind speed of 10 m/s.

Strength and chloride resistance of blended Portland cement mortar containing palm oil fuel ash and fly ash

This paper presented a study on the strength and chloride resistance of mortars made with ternary blends of ordinary Portland cement （OPC）, ground palm oil fuel ash （POA）, and classified fly ash （FA）. The mortar mixtures were made with Portland cement type I containing 0-40wt% FA and POA. FA and POA with 1wt%-3wt% retained on a sieve No.325 were used. The compressive strength and rapid chloride penetration depth of mortars were determined. The results reveal that the use of ternary blended cements produces good strength mortars. The use of the blend of FA and POA also produces high strength mortars and excellent resistance to chloride penetration owing to the synergic effect of FA and POA. A mathematical analysis and two-parameter polynomial model were presented to predict the compressive strength. The mathematical model correlated well with the experimental results. The computer 3-D graphics of strength of the ternary blended mortars were also constructed and could be used to aid the understanding and the proportioning of the blended system.

Stability characteristics of shallow landslide triggered by rainfall

Rainfall induced shallow landslides are known to be extremely dangerous since the sliding mass can propagate quickly and travel far from the source. Although the sliding mechanism in sloping ground is simple to understand, the problem may be complicated by unsaturated transient water flow. The flow behavior of rainwater in unsaturated sloping ground and the consequent factor of safety must be clearly understood to assess slope stability under rainfall conditions. A series of laboratory experiments was conducted to examine the critical hydrological states so that assessment of slope stability under rainfall condition can be performed. Based on the test results, a unique relationship between critical hydrological states, rainfall intensity, and soil properties was formulated. Sequential stability analysis provided insights into the stability of slopes subjected to variations in soil properties, slope angles and rainfall intensities, and the consequent variation in the depth of the failure plane, vital in landslide risk assessment, was determined through this analysis.The variation of rainfall intensity was found to strongly affect the depth of the failure plane in cohesionless sloping ground. Furthermore, the influence of rainfall intensity on the depth of the failure plane may be alleviated by a small magnitude of cohesive strength. The results of this study will reinforce knowledge of landslide behavior and help to improve mitigation measures in susceptible areas.