Search

This article presents a process improvement study applied at a local paper manufacturing company based on customized Lean Six Sigma methodologies. More specifically, the DMAIC (Define, Measure, Analyze, Improve, and Control) project management methodology and various lean tools are utilized to streamline processes and enhance productivity. Two performance measures namely production rate and Overall Equipment Effectiveness (OEE) are employed to evaluate the performance of the cutting and the printing machines before and after the DMAIC cycle. Obtained results indicate that the production rate increment for printing machines by 5% and for the cutting machines by 10%. Moreover, the OEE for the printing and cutting machines has increased by 21.6% and 48.45% respectively [ABSTRACT FROM AUTHOR]

The powder and crude extracts from five plant species, namely garlic (Allium sativum), manjack or drum tree (Cordia millenii), African or calabash nutmeg (Monodora myristica), negro-pepper (Xylopia aethiopica), and ginger (Zingiber officinale) were tested for their repellent activity against Callosobruchus maculatus (F.) adults through the cup bioassay technique and filter paper repellency method in the laboratory. C. millenii was the most superior repellent against C. maculatus. Results indicated that the repellent efficacy of the botanical materials followed this trend: C. millenii > Z. officinale > A. sativum > X. aethiopica > M. myristica. The former two plants generated a repellency of 66.0% and 65.4%, respectively; Class IV repellency (60.1-80.0%). Whereas, A. sativum, X. aethiopica and M. myristica caused a repellency of 50.3, 49.9 and 45.5%, respectively; Class III repellency (40.1-60.0%). The repellent effect on C. maculatus at the application doses of the powders of the selected plant species were statistically significant. There was also a significant difference in repellency due to various concentrations of the extracts of selected plant species with high correlation coefficients and positive significance compared to the powder treatment. Thus, % repellency increased according to doses and concentrations of the tested botanical products and due to the increase in the exposure period. [ABSTRACT FROM AUTHOR]

Information about the journal is presented, including rules on plagiarism, forced joint authorship and article sale.

This paper presents a detailed methodology to optimally synthesize links' lengths of planar Crank-Rocker (C-R) mechanism to achieve a targeted design with definite transmission angle deviation. Analytical and graphical proposed methodologies are applied to three different case studies; each satisfies a definite case (task). The analytical methodology is based on deducing six design equations with equality constraints, which represent relations between the desired case conditions and the mechanism's lengths. Meanwhile, deflection and transmission angles; the time ratio limits or output angular stroke can be easily obtained. Furthermore, optimal synthesized results can fulfil any definite case requirements which can be represented using the corresponding six deduced equations. The optimal charts are presented to quickly obtain the optimal (C-R) mechanism's lengths, which are achieving the targeted transmission angles deviations. Consequently, the designers can easily select optimal synthesized crank-rocker mechanisms' lengths, instead of time consuming of optimization calculations. Also, this paper presented a fast-graphical methodology to directly obtain an optimal synthesized (C-R) mechanism's lengths. This methodology requires only identifying the design case related to the chosen mechanism class and the desired transmission angle deviations through giving the minimum and maximum transmission angles (γmin and γmax). Moreover, a direct relation between the mini-max transmission angle deviations, the (C-R) mechanisms classes and the performance parameters can be presented. Hence, this facilitates the specialists' mission in designing (C-R) mechanisms for special uses as driving conveying, screening and shaking mechanisms. [ABSTRACT FROM AUTHOR]

Mechanical systems are mainly considered in heavy transmissions, and helix-angled gears are being mostly used in such fields of interest. As these mechanical components operate, they are heavily subjected to potential faults of operation. To avoid experimental faults, simulation-based analysis and test apparatus are now used for diagnosing purposes and hence, improving the dependability while enhancing their performance. For that, this paper presents an integrated approach of simulation analysis and the fabrication of a test rig specifically designed for fault inducing and seeding in helical gear transmissions. Computer-aided design and engineering techniques are both used to conduct vibration-based analysis. Six mode shapes are called out for in the modal simulation workbench where they were discussed accordingly. Bearing-mounted accelerometers were used to capture vibration signals of three operating axis in order to study the potentiality of utilizing them for condition monitoring. The current approach has demonstrated advancements in fault diagnosis methodologies and provided valuable insights in enhancing reliability and dependability of such applications. [ABSTRACT FROM AUTHOR]

Stone and Marble sector in Palestine has a significant contribution to the GDP. There are some modern factories that use computerized and numerical controls for stone cutting employing modern tools and processes, but most of the marble cutting factories depend on manual and small machinery production lines. This paper examines integrating modern technologies; artificial intelligence (AI) and mechatronic systems like sensors, actuators and control systems, in these cutting factories in order to increase their efficiency, improve the added value and contribute in the occupational safety for human labor and cutting processes. In particular artificial intelligence, machine learning and image processing tools will be investigated as examples of modern technologies that can be implemented in marble and stone cutting processes in Palestine. Four Convolutional Natural Network (CNN) types were employed to classify marble slabs, comparing colored and gray-level databases. Gray-level yielded superior recognition rates due to marble's prevalent gray color. Texture, not color, drove classification; ResNet-152 achieved 100% Recognition Rate (RR) for gray-level and 98.6% for colored. In terms of efficiency, Inception CNN excelled. Ultimately, gray-level images best served marble classification, rendering color irrelevant. [ABSTRACT FROM AUTHOR]

This paper collects and sorts out a large amount of fault data of a series of CNC lathes, and analyzes the fault data to classify fault levels. The values of a and b are obtained by Gutenberg--Richter (G-R) curve fitting, and then the relationship between a and b is used. The b value under each division criterion is obtained. By analyzing and comparing these b values, the rationality of classifying the fault levels according to these three methods is verified. The b-value is towards 1.0 when the reliability level of CNC lathes was promoted through ten years' reliability promotion. [ABSTRACT FROM AUTHOR]

Aiming at the problems of low monitoring accuracy and large memory consumption of traditional monitoring software, a visual monitoring software for MEMS micro-drive debugging is designed in this paper. According to the characteristics of MEMS system and the driving principle of micro actuator, the functional module of visual monitoring software for micro actuator debugging is designed. It includes monitoring pause button module program, visual display module program, monitoring quadrature signal module program and monitoring signal communication module program. Improve the monitoring accuracy through the connection between various modules. Select the material of the micro-drive and set its structural parameters, connect and debug the hardware of the drive, and test the performance of the designed software. The experimental results show that the software designed in this paper has high accuracy and low memory loss, the average accuracy is more than 90%, and the memory consumption is only 156 kb. It shows that this method can effectively monitor MEMS micro actuator, and the monitoring results are reliable. [ABSTRACT FROM AUTHOR]

The purpose of this literature review is to compare the difference between the concept of green supply chain management (GSCM) and sustainable supply chain management (SSCM) in relation to the factors of sustainable development and supply chain management in the literature. In order to achieve this objective, we proposed three factors of sustainable development and five factors of supply chain management. Based on these factors, the analysis of 20 definitions of GSCM and SSCM identified is performed. The results showed that the differences between the two concepts are that GSCM definitions are generally based on environmental factors. While the SSCM definitions are based on the three levers of Sustainable Development (SD) (environmental, economic and social) at the same time. However, the flow and the stakeholder factors present the similarities between the two approaches. Consequently, studying two approaches mutually can provide the companies the possibility to choose the implementation of GSCM or SSCM approach, which can help manufacturing practitioners in their decisions to increase their sustainable development goals. [ABSTRACT FROM AUTHOR]

The issue of energy security is becoming very important due to higher standards of living and being the engine for economic development. Hence, recently solar PV systems witnessed high popularity worldwide since it has facilitated the utilization of the untapped potential of solar energy. On-grid PV schemes have become the first option for power generation, among other renewable energy sources, due to low cost of generated power as compared with other systems and short construction time. This paper presents the real performance data of the first large size solar PV project, in Jordan, connected to the medium voltage grid on wheeling basis. The PV station was designed to be installed on south-north axis with an eastwest solar tracking system to enhance electrical energy production. The technical specification and calculated design parameters, such as different losses and energy yield, using the commercial software, PVsyst, were reported and compared with real data from the field. The annual electricity yield, in 2019, was about 3954 MWh with an overall performance ratio of 95%, exceeding all expectations. Unfortunately, little attention has been paid by governmental institutions and/or distribution companies, to the general performance of such plants and variation in rates of production. It is deemed that this paper will answer some of critique questions and fill the gap of information related to the performance of PV power stations, connected to the medium voltage network, under local conditions. More work should be aimed to check influencing factors on the performance of other large PV and wind plants in the country. [ABSTRACT FROM AUTHOR]

This paper deals with machines, tool transporter (TT) and tools simultaneous scheduling in multi machine flexible manufacturing system (FMS) with the lowest possible number of copies of every tool type without tool delay taking into account tool transfer times to minimize makespan (MSN). The tools are stored in a central tool magazine (CTM) that shares with and serves for several machines. The problem is to determine the lowest possible number of copies of every tool variety, allocation of copies of tools to job-operations, job-operations' sequencing on machines and corresponding trip operations of TT, including the dead heading trip and loaded trip times of TT without tool delay for MSN minimization. This paper proposes nonlinear mixed integer programming (MIP) formulation to model this simultaneous scheduling problem and crow search algorithm (CSA) built on the crows' intelligent behavior to solve this problem. The results have been tabulated, analyzed and compared. [ABSTRACT FROM AUTHOR]

The optimization process is applied to the machining operations in order to provide continual improvement in accuracy and quality of produced parts. The effects of machining parameters in milling operations, such as spindle speed, depth of cut and feed rate are investigated in order to minimize the surface roughness as well as the time of machining process. The effective machining parameters, such as depth of cut, feed rate and spindle speed in turning operations are investigated to minimize the surface roughness as well as the time of machining process. Also, machining parameters, such as peak current, gap voltage, duty cycle and pulse on time in Electro Discharge Machining (EDM) operations can be optimized in order to obtain the optimized material removal rate, tool wear, and surface roughness in part production process. To improve material removal rate, surface roughness, and spark gap in part production process using the wire EDM operations, machining parameters, such as spark on time, spark off time, input current are studied and optimized. To calculate optimized machining parameters, different optimization methods, such as Taguchi method, fuzzy logic algorithm, artificial intelligence, genetic algorithm, artificial neural networks, artificial bee colony algorithm, ant colony optimization and harmony search algorithm are used. As a result, time and cost of accurate production can be reduced to increase productivity in part production process using machining operations. In this paper, a review of machining parameter optimization is presented and future research works are also suggested. The main aim of the study is to review the challenges and limitations of the optimization techniques used in optimizing machining parameters. It has been observed that the research field can be moved forward by reviewing and analyzing recent achievements in the published papers. [ABSTRACT FROM AUTHOR]

Conventional sports posture positioning method, using convolution neural network, only uses Fast RCNN algorithm to locate sports posture, which leads to low accuracy of sports posture positioning. This paper proposes the application of multibody system dynamic direction vector model in sports posture positioning. In this paper, the direction vector model of multibody system dynamics is used to design the constraint of direction vector property and hinge between objects, calculate the activity of objects, and establish the motion posture model; The four coordinate systems of image, pixel, camera and world are established, and the spatial relationship of the four coordinate systems is calculated to complete the spatial transformation of each coordinate system; The gray transformation is carried out for the image to obtain an image. Gray human body image is used to obtain the target image and extract the contour of human body region; Similar to Fast RCNN algorithm and multi-scale context information are used to form a multi scale convolution neural network to locate the sports posture. The experimental results show that positioning sports posture has better positioning effect, higher positioning accuracy and faster positioning efficiency. [ABSTRACT FROM AUTHOR]

Orientation of corn is an essential step in the corn product processing. Corn processing mainly includes cutting root, tip, segment, and grain, and the whole ear packaging, etc., and at each step, the ear needs to be operated in a straight direction. In this paper, the physical parameters of three kinds of corn have been measured, and combined with the characteristics of corn shape geometry, the corn orientation solutions have been put forward. The corn orientation device has been designed, and its working principle has been introduced. When the primary belt speed was 1.426 m/s, all of corn can come off the belt. In order to ensure the requirements of corn processing technology, the orientation device can solve the following problems. When the corn was transmitted in the front of corn small diameter, corn orientation device could make the corn flip in the former of corn big diameter. The corn was transmitted in the front of corn big diameter; corn orientation device keeps its original direction remains the same. [ABSTRACT FROM AUTHOR]

All joints of the non-driving robot have driving devices, but they can not be controlled effectively, which increases the difficulty of the robot control. In order to solve this problem, a multi joint integrated control system for non-actuated robot is designed in this paper. The research object is a two-degree of freedom non-actuated robot. After designing the basic structure of the robot, the dynamic characteristics of the robot are analyzed, and the integrated control system is designed from two aspects of current and position. The experimental results show that the design method can realize the accurate motion control of multi-joints of non-driven robot, which provides a reference for practical application. [ABSTRACT FROM AUTHOR]

Since the beginning of the 21st century, it has been noted that the rate of energy consumption has increased globally due to the technological progress that has taken place. The industrial sector occupies one of the first sectors in the consumption of electrical energy. Therefore, this paper aims to use the method of artificial neural networks (ANN) to model, analyze, and forecast electricity consumption in Jordan's industrial sector. In the present analysis, several factors affecting energy consumption in this sector are studied and verified, namely: the number of the industrial establishments (ES), the number of employees (EM), the electricity price (E$), the price of fuel (F$), gross output (G), structural effect (GI/GN) and the capacity utilization (CU). Several networks are executed and tested in terms of the root mean square error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R2). The results of this study implicated that the electricity consumption levels in the Jordanian industrial segment are highly driven by the number of industrial establishments and employees followed by the gross output, among others. Additionally, the present ANN-predicted electricity consumption results are compared with literature and showed superior accuracy. Finally, this ANN model is combined with the time series analysis approach to forecast the electricity needs of the Jordanian industrial sector for the next decade. [ABSTRACT FROM AUTHOR]

Recent years have seen an increase in the importance of assessing the environmental and social impacts of industrial product supply chains, leading to the introduction of the concept of supplier sustainability, which entails meeting all suppliers' economic, environmental, and social needs. Typically, supplier selection decisions are based on expert opinions presented as supplier scores. Experts may not be equally familiar with all aspects of suppliers' economic, social, and environmental attributes when evaluating sustainability metrics. The purpose of this paper is to present a new approach for selecting a sustainable supplier using the COPRAS (Complex Proportional Assessment) multicriteria group decision-making process. Suppliers' scores and the weights of each criterion are expressed verbally by experts, by using linguistic variables. Then the linguistic terms are transformed into equivalent type 2 fuzzy numbers. Using fuzzy type 2 numbers facilitates aggregating experts' opinions during group decision-making. The proposed approach assumes that the problem analyst, in addition to collecting the suppliers' scores given by the experts, also determines a degree of expertise for each expert in each criterion and aggregates the data by the COPRAS method to determine the optimal decision. The analyst's verbal variables to represent his view on the validity of each expert are then converted into intuitionistic fuzzy numbers. Intuitionistic fuzzy numbers provide the possibility of presenting uncertainty and doubt from the analysts' point of view. This paper illustrates the application of the model by presenting an example and discussing its results. [ABSTRACT FROM AUTHOR]

In automotive industries, the belt grinding (BG) is a mechanical manufacturing process by removing material using a tool called an abrasive belt. This technique enables high surface quality and reproducibility of high-precision mechanical parts to be achieved. The main objective of this paper is to provide a detailed account of the effect of superfinishing on the surface texture of 16MC5 casehardened steel by the belt grinding process under the alumina abrasive grains (Al2O3) with average sizes (60, 40, 30, 20 and 9 µm), respectively. The surface quality was characterized by one surface roughness parameter (Ra) and three parameters of the Abbott-Firestone curve (Rpk, Rk and Rvk) in order to determine the relationship between the grains size reduction and the surface texture. As all mechanical machining processes with undefined tool geometry (e.g. grinding, polishing, lapping,...etc.), experimental results obtained during measurements suggest a clear relationship between the reduction in abrasive grains size and the surface texture. The minimum quantity lubrication (MQL) also decreases the surface roughness; the lubrication addition helps to achieve better surface quality than the dry belt grinding. [ABSTRACT FROM AUTHOR]

This paper aims to analyse the healthy-smart concept as a standard design of kitchen waste biogas for urban people. The anaerobic digester (AD) is designed for family size. The planned vertical digester is a one-stage- semi-continuous type because this AD type is easy to operate in urban areas. Kitchen waste or food waste can be generalized as all bio-materials produced from kitchen activities (including vegetables, fruits, bread, rice, coffee ground, tea leaves, etc). The biggest problem with household waste is the non-uniformity of feedstock entering the digester biogas. Five steps will be carried out: to establish technical standards in designing kitchen waste; to calculate the biogas potential from kitchen waste; to simulate the methane demand and generation profile; to calculate the geometry of the biogas digester; and to analyse the operation parameter for gas production into the healthy-smart concept. With a simple simulation of two people in the household for 1 d, the results show that biogas produced from kitchen waste is sufficient for cooking purposes. For the healthy-smart concept of biogas production, some operation parameters must be considered, such as; pH, alkalinity, temperature, volatile fatty acid concentration, volatile solids, and C/N ratio. The results can be used in overcoming the urban household waste and also as a reference in sustainable urban planning. [ABSTRACT FROM AUTHOR]

Maintenance of medical devices has become a top priority around the world, this is due to the vital role of these devices in contributing to saving human lives. Maintenance engineering makes use of data analytics using statistical techniques to expose patterns to capture relationships among the different variables that affect the performance of medical devices. This research presents an attempt to discuss an efficient approach of data analytics for maintaining medical devices to enhance their reliability in terms of the mean time between failure and availability. Data analytics methodology is applied based on supervised machine learning techniques by training the classification models to improve reliability, availability. Raw data were collected from the cooling system of the Magnetic Resonance Imaging MRI magnet as a case study, then organized and cleaned to make it suitable to build and train classification models. A new representation of the data has been resampled using the Synthetic Minority Oversampling Technique (SMOTE). Six different classification models were trained and tested using Weka software, these are Logistic regression, K-nearest neighbors, J48 and Random Forest decision trees models, Support-vector machine SVM, and Naive Bayes. Based on the F-measure, K-nearest neighbor, Random Forest, and SVM were chosen to be the most significant classifiers, a comparison between these three classifiers was done based on evaluation metrics, the metrics are: Correctly classified instances, Incorrectly classified instances, Root mean squared error (RMSE), Recall, Precision, F-Measure, Area under ROC curve, and Accuracy, it was found that the random forest classifier has the best performance, highest accuracy, and the least error. Maintenance performance in terms of MTBF and availability are estimated after applying the random forest model and compared with their values before to determine the efficiency of the classifier. It was found that the random forest model has caused an improvement in MTBF by 879%, and an improvement in the device availability by 11%. Data analytics plays a critical role in improving efficiency and generating understandings from the data generated by devices. Through this paper, data analytics was followed for maintenance planning to improve the mean time between failure and availability of the cooling system of the magnetic resonance imaging device, the results were positive and encouraging. The same methodology can be generalized to benefit from it in maintenance planning for other medical purposes. [ABSTRACT FROM AUTHOR]

Cancer diseases and microbial infections are the subject of several ongoing recent researches. In this paper, aqueous extract of red and yellow Astragalus sarcocolla gum was used as safe and green agent, for the synthesis of novel biologically active silver-nanoparticles. Six silver nanoparticles (AgNPs) with different characters were obtained using sarcocolla gum at (5, 10 and 20 mg/ml (w/v)) concentrations. All biosynthesized AgNPs were characterized using UV–visible spectroscopy, Transmission Electron Microscopy (TEM), and Dynamic light scattering (DLS). Cytotoxic effect of sarcocolla gum-AgNPs against five human cancer cells and one normal cells was determined using the MTT (3-(4, 5-dimethylthiazol-2-yl)-2, 5- diphenyltetrazolium bromide) assay. The semi rounded particles formed from 5mg/ml red gum (AgNPs-RG1) and having 9.23±3.66 nm size range were the most active and possessed high cytotoxic effect against, A549 lung, pc3 prostate, Mcf-7 breast and paca2 pancreatic cancers, with IC50 values (88.4,75.6, 72.2& 55.0 ug/ml, respectively), but showed low cytotoxic effect (20 % at 100ug/ml) against human normal cells (BJ-1). On the other hand, the spherical to cubic shaped nanoparticles obtained from 5mg/ml yellow gum (AgNPs-YG1) with 10.92 ± 5.48 nm size range, showed good cytotoxic effect against three cancer cells (PC3 prostate, MCF-7 breast and paca2 pancreatic) with IC50 values (75.0, 82.8 and 81,6ug/ml respectively), and normal cells(BJ-1) with IC50 value (81.8ug/ml). Antibacterial and antifungal activities of the synthesized red and yellow gum-mediated AgNPs with different sizes and shapes were also investigated. Particles biosynthesized from 5 and 10 mg/ml red gum (AgNPs-RG1, RG2) and 5mg/ml yellow gum (AgNPs-YG1) exhibited broad spectrum antimicrobial effects against all tested pathogenic gram-positive, gram-negative bacterial strains, unicellular yeast and filamentous fungi. Based on these results, it can be concluded that the synthesized silver nanoparticles from low concentrations of sarcocolla gum have significant biomedical applications. [ABSTRACT FROM AUTHOR]

This paper investigates the linkage between TQM two dimensions, namely Soft (ST) and Hard (HT). Few empirical studies examined the interrelatedness between these dimensions especially in the developing economy of Malaysia. Thus, the paper proposed a theoretical multidimensional integrated framework in order to examine the link between TQM dimensions. Seven variables were used to measure ST and Eight variables used for HT. the hypothesis of the study is that the there is a significant and positive relationship between the two dimensions. To show the validity of the proposed model, it was tested in 40 ISO 9000 certified Malaysian manufacturing industries. To test the hypothesis, a structured self-administrated questionnaire was developed. It is based on the common five point likert scale for quality management for all the items included in the survey. The multiple regression analysis was used in order to test the corollary hypotheses, utilized from the statistical package for social science. Data analysis indicated: [1] the instrument was valid and reliable; [2] the results supported the proposed theoretical framework; [3] there is a significant and positive link between ST and HT such that they could be linked and integrated together in the same framework if they are implemented and practiced correctly by the quality and production managers; and [4] Malaysian managers have awareness to ST and HT. Results showed that All seven variables of ST were significantly associated with some HT variables. This paper contributes to quality management by: [1] theoretically proposing and empirically investigating the theoretical framework; [2] examining the integration between TQM two dimensions; [3] using the multidimensionality of ST and HT; and [4] the application of this study in the developing economy of Malaysia. It is concluded that ST and HT can be integrated together, the relationship was supported and that Malaysian quality managers can utilize these dimensions if implemented and practiced correctly. This paper provides essential guidelines for Malaysian managers dealing with quality management inside organizations. [ABSTRACT FROM AUTHOR]

Lean production has been industrialized in manufacturing industry in the Global North on account of delivering quality products. The industry in the Global South on the other hand is facing problems that could easily be minimized using the production principle. This paper is organized to adapt lean production for improving productivity of garment industry in Ethiopia. The target is to alleviate variety between company's productivity and customer demand. Shop floor visit, questionnaire survey, and focus group discussion-based data mining approaches have been used for this purpose. The qualitative part was used to map out baseline data of existing manufacturing process whereas the quantitative part was aimed to construct empirical findings obtained from qualitative organization. Aggregate results accordingly show that there are substantial lean wastes such as longer lead time, high WIP inventory, longer routes, and unutilized resources. It has been meanwhile renown that if appropriate lean production tools have framed and implemented, the impact of these wastes could meaningfully be minimized and a smooth process flow can be ensured. For instance, a lead time for a single round neck t-shirt in the case study has shown an improvement of 18.3% and a 3.9% improvement of resource utilization. [ABSTRACT FROM AUTHOR]

The paper has a dual purpose: firstly, to examine the influence of various cutting conditions (cutting speed Vc, feed f, depth of cut ap, tool nose radius rɛ, and cutting edge angle Xr) on the quality of machined parts (Ra), tangential force (FZ) and cutting power (Pc) during the turning process of polyoxymethylene POM-C. Two carbide inserts, SPMR 120304 and SPMR 120308, were used for the three-dimensional cutting operations. Secondly, the goal is to identify optimal cutting conditions that maximize material removal rate (MRR) while minimizing three output parameters (Ra, FZ, and Pc). The study employed analysis of variance (ANOVA) to assess the significance of the input parameters on the desired outcomes and utilized an artificial neural network (ANN) to create mathematical models. The K-fold Cross-Validation approach was deemed suitable due to its efficiency in requiring fewer experiments. To optimize the cutting conditions, a new metaheuristic optimization algorithm called Multi-Objective Artificial Hummingbird Algorithm (MOAHA) was selected. ANOVA analysis reveals that factors f and rɛ contribute 58.05% and 32.25%, respectively, to the response Ra. Classical parameters (Vc,f, and ap) also impact mechanical cutting actions (FZ and Pc). The MOAHA algorithm, coupled with four ANN models, optimized the five cutting conditions, resulting in optimal values Vc = 250 m/min, f = 0.08 mm/rev, ap = 1.3 mm, rɛ = 0.8 mm, and Xr = 75°. Under these conditions, responses are: Ra = 0.6 μm, FZ = 21.51 N,Pc = 60.24 W, and MRR = 26.38 cm3/min. The ANN-MOAHA coupling provides an excellent, simple, and fast computer tool for multi-objective optimization. [ABSTRACT FROM AUTHOR]

Bolted joints are used extensively in mechanical engineering due to their reusability, appearance, and strength advantages. In different industrial applications, the separated mechanical components are clamped together during the assembly using a tightening process. Estimating precisely the initially achieved clamping force is a persistent problem for providing a secure and reliable connection for a particular design. However, the nut coefficient is one of the exploratory methods used for this purpose. This paper aims to investigate how the nut coefficient of a bolted joint is influenced by factors such as bolt/nut surface treatment and the presence of lubrication at joint contact surfaces throughout the cyclic joint assembly/disassembly process, serving as a simulation for real-life maintenance operations where the same bolt/nut are reused. Torquing cycles were introduced to bolted joints with two surface finishes and four lubrication conditions. The experiments were conducted on bolts at room temperature according to ISO16047. The nut coefficient was calculated for bolt sizes M6*1, M8*1.5, and M10*1.5. The results were analyzed using the analysis of variance and Taguchi method L32 for estimating the contribution of the different factors on the nut coefficient. It was found that the lubrication was the most significant parameter affecting the nut factor regardless of the bolt size. Also, a case study was conducted to investigate the underlying reasons behind the significance of lubrication in influencing the nut coefficient across different bolt sizes. [ABSTRACT FROM AUTHOR]

After the establishment of any facility, it is quite necessary to determine the profitability of the unit. The present research provides a detailed analysis of the case unit along with the necessary costs and returns on investment. This research paper also includes the cost and benefits analysis of a newly installed digital printing department at Sapphire Diamond Company. Since the relationship between fabric printing and most of the costs is non-linear, this is the reason the system dynamics modelling technique was used in the present research; it was used to model the requirement of material, electricity, and human resources. The model was developed by using the stocks, flows, variables, and parameters in the Anylogic PLE version and the simulated results were validated from the real-time scenario. The data regarding the labour cost, electricity cost, and material cost were collected from the case department. Furthermore, the scenario analysis was conducted and simulated results were downloaded in Microsoft Excel. Several line charts were plotted in Microsoft Excel and Origin software. It was indicated from the scenario analysis that the cost per meter decreased by increasing the production rate. It was also indicated that if the digital printing machine was operated at its maximum capacity, the ROI would be maximum. Incurred overheads were also the subject of concern in the present scenario. After the overall analysis, it was concluded that the digital printing facility was still in profit even if its production rate per day was 150+50. Since the present research encompasses the detailed cost and benefit analysis of a newly installed digital printing facility, therefore, it can be beneficial for investors as analytical support to decide on installing digital textile printing machines. [ABSTRACT FROM AUTHOR]

Cancer tissue engineering using three-dimensional (3D) cell culture scaffolds has been reported to handle the limitations of two-dimensional (2D) cell culture in vitro and in vivo cancer models. In this paper, the scaffolds were produced via the freeze-drying technique and chemical cross-linking. 1-ethyl-3(3-dimethylamino propyl) carbodiimide hydrochloride (EDC) has been used as a crosslinker for conjugation between gelatin and silk fibroin (SF). The gelatin-fibroin (GF) scaffold evaluated the physicochemical characteristics such as microstructure, functional groups, swelling rate, degradability as well as some biological characteristics including in vitro cytotoxicity, for physicochemical characteristics such as microstructure, functional groups, swelling rate, degradability, and some biological characteristics including in vitro cytotoxicity and cell adhesion, cell proliferation and the spheroid forming capacity of MCF-7 cells on this scaffold. The results showed that the GF scaffold with the uniform pore size demonstrated suitable physicochemical properties that controlled swelling and degradation characteristics. The GF scaffold had no toxicity on human fibroblast cells (hF), and supported MCF-7 cells' adhesion, proliferation, and spheroid formation. In conclusion, this study successfully considered the potential of the GF scaffold as an in vitro 3D cell-culture scaffold in cancer tissue engineering in particular and tissue engineering in general. [ABSTRACT FROM AUTHOR]

Given that corrosion is not considered in calculating the stiffness of reinforced concrete structures under existing cord, this paper improves the calculation formula in cord, and proposes a method to calculate the stiffness of the corroded beam strengthened by steel plate, then the formula for calculating the deflection is proposed. Nine corroded beams are strengthened by steel plates, the static test results of which are used to verify the correctness of calculation method. The influence of corrosion rate and thickness of steel plate on the stiffness are analyzed through the deflection change. Both experimental and theoretical analysis results show that the corrosion rate has a limited impact on the reduction of stiffness. When the thickness of steel plate reaches 6 mm and the corrosion rate reaches 30%, the change in deflection will decrease. At the same time, the influence of corrosion rate on the stiffness is greater than that of steel plate thickness. [ABSTRACT FROM AUTHOR]

With the further increase of domestic oil demand, the diversification strategy of energy supply represented by alternative energy sources, such as alcohol fuel which has become a direction of China's energy policy. Alcohol fuel can reduce conventional engine emissions by replacing conventional gasoline and diesel, but their unconventional emissions -- formaldehyde -- tend to have higher concentrations than conventional engines. Based on this, this paper analyzed the physical and chemical properties of mixture of methanol and gasoline and its feasibility as an energy fuel, and conducted experiments on formaldehyde emission of gasoline and methanol gasoline respectively, and then obtained a large number of experimental data that studied and analyzed the experimental results and methods, and drew relevant research conclusions. The results show that the high ratio of alcohol fuel can replace the use of chemical fuel and has good energy saving and environmental protection characteristics. When the same fuel is tested, the formaldehyde emission increases first and then decreases with the increase of power. In this paper, a large amount of formaldehyde emission data from alcohol fuel engines are obtained through bench experiments, which provides a scientific basis for the future development of alcohol fuel vehicle combustion system and the formulation of environmental emission standards. [ABSTRACT FROM AUTHOR]

The present paper presents a Computer-Aided Design (CAD) system that detects lung cancer. Lung cancer detection uses Multi-Layer (ML), Neural Networks (NNs) and Independent Component Analysis (ICA). ICA aims to speed the detection by decreasing the number of features. The ML NNs classifier is trained by Gradient descent algorithm (traingd), Gradient descent with momentum (traingdm), Gradient descent with variable learning rate and momentum (traingdx), Resilient back propagation (trainrp), Fletcher-Reeves Update (traincgf), Polak and Ribiere (traincgp), Powell and Beale Restarts (traincgb), Scaled Conjugate Gradient Algorithm (trainscg), Quasi Newton BFGS (trainbfg), One step secant algorithm (trainoss) and Levenberg-Marquardt (trainlm). The detection algorithm is tuned to determine the existence of cancer in real Computerized Tomography (CT) images and it is validated, trained & tested using 460 CT images, 350 of them belong to lung cancer patients in Jordanian hospitals. The presence of cancer in these images is labeled by experts. The present paper investigates the performance of the ML NN classifier trained by these training algorithms with ICA feature extraction. Results reveal the robustness of the detection algorithm for real CT images. Among the 11 training algorithms, Levenberg-Marquardt achieves a classification accuracy of 100% with least number of ICA features. [ABSTRACT FROM AUTHOR]

In this study, a moving track tracking method of multi degree of freedom manipulator based on particle filter algorithm is proposed. By constructing the transformation matrix and the Jacobian matrix, the kinematics of the multi degree of freedom manipulator is analyzed. According to the three coordinates of the end of the multi degree of freedom manipulator, the forward kinematics model is solved and the inverse kinematics model is obtained. Particle filter algorithm is adopted to track the moving trajectory of multi degree of freedom manipulator, and the trajectory tracking error is corrected. Experiments show that this method has the advantages of small difference between the trajectory of the multi degree of freedom manipulator and the actual target trajectory, such as high trajectory tracking accuracy and short tracking time, and can meet the requirements of people for the trajectory control accuracy of the joint manipulator. It is expected that this paper can provide valuable references and help for the application field of robots as well as the actual life and production activities. [ABSTRACT FROM AUTHOR]

In most industrial environments, vibration analysis is widely used for fault diagnosis of rolling bearings. The vibration signal measured from a bearing represents a mixture of motor vibration, rolling vibration, noise, and other sources. Due to the high cost of devices and limited space, only one sensor can be installed to measure this signal. In this paper, a feature extraction method based on Single Channel Blind Source Separation (SCBSS) and Normal Distribution (ND) is proposed for vibration monitoring of rolling element bearings. To decompose the bearing signal, SCBSS is applied for separating the different sources. Because ND is sensitive to the type of fault, it is used as criterion to find an output that contains the maximum information about the fault by removing the other sources. In fact, the obtained signal contains other vibrations which affect the correct source of fault. A second SCBSS filter is, therefore, proposed to decompose the selected source and thus improves the performance of fault diagnosis. The application of the proposed method is carried out on a deep groove ball bearing with outer race fault, ball fault, and inner race fault in order to better validate the diagnosis results. [ABSTRACT FROM AUTHOR]

The global fossil fuel crisis has generated the need to find alternative solutions through renewable energy sources. Since Jordan has a distinctive location, the potential for using renewable energy such as solar, wind, or other available sources has been studied extensively by researchers. The main objective of this study is to investigate the awareness level about the renewable energy in the Jordanian society. The research study group of people consisted of six hundred and sixty six surveys. The data showed that Jordanians have a high awareness and knowledge about renewable energy and its sources. More than 90% of the surveyed know about renewable energy's merits, and the environmental effect of fossil fuels. This paper also provides a comprehensive overview of the renewable energy technologies and projects established in Jordan, including their distribution, advantages and disadvantages and the challenges encountered by each project. [ABSTRACT FROM AUTHOR]

The key advantages of 3D printing technology include design freedom, customization, pollution prevention, the capacity to construct advanced systems, and rapid prototyping. In this paper, a concise overview of the fundamental 3D printing techniques, materials, and their advancement in emerging fields is presented. Besides, the significant potential of additive manufacturing in medical, aeronautical, architecture, and defensive structures are discussed in detail. The latest developments in materials, comprising alloys, polymer composites, ceramics, and concrete are also discussed. Finally, the key processing issues and computer design limitations of 3D printing technology is described. In short, this study presents a survey of the advantages and disadvantages of 3D printing as a baseline for possible future research work. [ABSTRACT FROM AUTHOR]

Brake lining performance is influenced by configuration of friction material, functional speeds, load, and temperature. Asbestos friction materials are injurious to human health and, therefore, replacement is needed, hence an alternate material with desired tribo-mechanical properties is to be investigated. In this paper, the wear characterestics of two asbestos-free friction materials sliding against grey cast iron disc were investigated. A metallic based (viz:AF-22) and fine brass based (viz:CL-3003) were prepared by compression moulding process that required pin samples. Wear experiments were performed using a Pin-on-disc tribo-tester. The wear rates were compared under various temperature, sliding speed, and pressure conditions using Taguchi's L9 orthogonal array. The wear rate of AF-22 was observed between 2.01 to 2.17 mm³/N.m., and for CL-3003 (1.49 to 1.66 mm³/N.m). Ranking of the parameters based on the experimental findings and the S/N ratio analysis was done. Temperature is the most influencing parameter, i.e. 82.96% for AF-22 and 87.95% for CL-3003 material. The EDS technique was used to understand material composition. At various magnifications, SEM images of brake pad materials were investigated. Further investigation under in-situ condition is recommended for these materials. [ABSTRACT FROM AUTHOR]

Nowadays, to survive in the highly competitive industries, organizations require adapting to the rapid changes in the industrial environment to deliver the products or services with high quality in accordance with the consumer's expectation. In order to achieve maximum efficiency, organizations endeavour to enhance their asset integrity, reliability, availability, productivity, maintenance practice, and concentration on safety and product quality. It is also vital to ensure the highest maintenance efficiency practice in organizations to achieve the best efficiency practice. Therefore, this paper aims to identify the most influential factors that impact workforce productivity's Wrench Time (WT). Understanding the impacts of these factors on the WT and identifying their causes will provide a clear vision of how the management can allocate the necessary resources to eliminate these impacts. As a methodology, random sampling is used to determine the sample of observations from a given population. This sample is then used in the pilot test that is conducted to test the reliability of the data collection method. The Day In Life Of (DILO) approach is used to collect data as an observation method that involves the supervisor's participation with the technicians throughout the whole working day. A case study based on one of the largest LNG plants in the Middle East is conducted to verify the achieved maintenance efficiency. As a result, workforce productivity has increased to 38.1% by changing the monthly workforce plan, leading to a future roadmap to enhance maintenance efficiency by considering more related factors. [ABSTRACT FROM AUTHOR]

This paper presents a detailed methodology to optimally synthesize links' lengths of planar Crank-Rocker (C-R) mechanism to achieve a targeted design with definite transmission angle deviation. Analytical and graphical proposed methodologies are applied to three different case studies; each satisfies a definite case (task). The analytical methodology is based on deducing six design equations with equality constraints, which represent relations between the desired case conditions and the mechanism's lengths. Meanwhile, deflection and transmission angles; the time ratio limits or output angular stroke can be easily obtained. Furthermore, optimal synthesized results can fulfil any definite case requirements which can be represented using the corresponding six deduced equations. The optimal charts are presented to quickly obtain the optimal (C-R) mechanism's lengths, which are achieving the targeted transmission angles deviations. Consequently, the designers can easily select optimal synthesized crank-rocker mechanisms' lengths, instead of time consuming of optimization calculations. Also, this paper presented a fast-graphical methodology to directly obtain an optimal synthesized (C-R) mechanism's lengths. This methodology requires only identifying the design case related to the chosen mechanism class and the desired transmission angle deviations through giving the minimum and maximum transmission angles (min and max). Moreover, a direct relation between the mini-max transmission angle deviations, the (C-R) mechanisms classes and the performance parameters can be presented. Hence, this facilitates the specialists' mission in designing (C-R) mechanisms for special uses as driving conveying, screening and shaking mechanisms. [ABSTRACT FROM AUTHOR]

When using the current method to schedule the resources in parts recycling, the resource scheduling delay is relatively long, which reduces the efficiency of parts resource scheduling, resulting in a low resource utilization rate. This paper proposes an adaptive scheduling method for parts recycling resources based on improved reverse particle swarm optimization. The current situation of waste vehicle recycling resource scheduling is analyzed, and the mathematical model of component recycling resource scheduling is constructed to consider time and cost. The reverse particle group is used to dispatch component recovery resources, and the inertia weight parameters are adjusted. The adaptation mechanism regards the degree of change of the particle function as the update factor of the inertia weight, avoiding the value according to the number of iterations; introducing the inverse learning operator, strengthening the ability of resource scheduling global search, and completing the recycling of used automobile parts and components Adaptive scheduling. The experimental results show that the proposed method has the highest recovery resource utilization rate, and the task time is about 200-400s, and the energy consumption is small. The proposed method can effectively schedule resources and improve the utilization of resources. [ABSTRACT FROM AUTHOR]

Global primary energy demand will most likely increase in the coming decades as a result of a growing world population and generally increasing prosperity. Historically, increasing energy demand has usually been associated with increases in greenhouse gas (GHG) emissions as the additional energy needs are met by the utilization of fossil fuels. However, in order to meet the efforts to curb climate change, both existing and emerging energy demands (and therefore energy supply systems) must be sustainably covered using renewable energy resources. In this context, two different development scenarios are presented in this paper: First, based on historical developments in recent years, the given expansion pathway of renewable energies is extrapolated until the year 2050 (bottom-up perspective). However, as this expansion does not meet the climate goals set to meet the 1.5 °C target, additionally a development pathway, which meets the GHG reduction goals in 2050 is developed (top-down perspective). Given the very high levels of energy delivered from (fluctuating) renewable energy sources needed for such a sustainable development path, comprehensive decarbonization (concerning fossil carbon) requires a much better interconnection of the different energy sectors (electricity, heat, mobility) compared to today; some of these necessities are also presented because they influence the further development of the energy system and thus the role of renewables considerably. All over, the paper shows that the already ongoing efforts to achieve the 1.5 °C target must be intensified dramatically; the already significant developments related to the installation of new systems to use renewable sources of energy are not enough to achieve the defined targets. [ABSTRACT FROM AUTHOR]

This research paper introduces a comprehensive approach for evaluating material alternatives in the design of low cost robotic wheelchair chassis, incorporating a combined CRITIC (Criteria Importance through Intercriteria Correlation), EDAS (Evaluation based on Distance from Average Solution), and COPRAS (Complex Proportional Assessment) framework. Material selection has a significant impact on robotic wheelchair performance and longevity, offering issues due to many criteria and sophisticated decision-making in engineering design. The proposed framework solves these issues by combining three well-known multi-criteria decision-making (MCDM) techniques by considering 7 criteria and 12 potential alternate materials. CRITIC assesses the relevance of criteria, EDAS rates material alternatives, and COPRAS computes comprehensive performance ratings while taking interdependencies into account. Wheelchair Chassis Materials are assessed based on SOLIDWORKS analysis for mechanical qualities and online B2B market data for cost, weight, and other relevant factors. Gray cast iron emerges as the most favorable choice for the robotic wheelchair chassis, showcasing its exceptional balance of attributes. This study adds important insights to material selection for complex engineering systems and assistive technology design, resulting in better wheelchair design and user experience. [ABSTRACT FROM AUTHOR]

This paper highlights a study for examining the viability and performance of a solar-assisted ground-coupled heat pump (SAGCHP) to meet domestic hot water and heating needs of a typical low-energy residential building covering a total floor area of 100 m2 under Batna, Algeria, weather conditions. In this study, four different solar-assisted ground source heat pump combinations have been developed and will be simulated numerically using the simulation program TRNSYS. It turned out that a geothermal heat pump system of 7.7 kW, combined with flat solar thermal collectors, is an alternative promoter to achieve the objective of this study. The extreme annual average values of the heat pump coefficient of performance (COP) obtained are 3.48 and 4.55. In the system, with recharging the borehole, the net energy extracted from the ground is decreased by 30.4% compared to the reference case (GSHP). This can reduce the ground thermal imbalance problem. [ABSTRACT FROM AUTHOR]

Electric vehicle systems are growing in popularity as a promising solution to the problems associated with traditional transportation systems, such as environmental pollution. Nonetheless, the task of devising control algorithms that effectively control electric vehicle systems continues to persist as a complex realm of research. This is due to the ongoing pursuit of refining the dynamic attributes of the system, a task that is riddled with challenges. The inherent instability exhibited by the system and the presence of undesirable behaviors further compound the intricacy of this endeavor, demanding careful attention and comprehensive analysis of the system's unstable roots. In this paper, an advanced control algorithm is proposed for controlling the speed of the electric vehicle system based on the lead compensation. In addition, the control algorithm is designed to include the utilization of model reference control to improve the time response properties of the closed-loop system. Then, the Zebra Optimization Algorithm (ZOA) is used to optimally define the compensator parameters such that the reference model and system outputs be asymptotically identical with desirable steady-state error. Eventually, the simulation results show that the proposed optimal model reference lead compensator ensures stable and high-performance control of the electric vehicle system while maintaining simplicity and acceptable control action compared to other control approaches. This is substantiated by the noteworthy reductions it brings about: a staggering 90% decrease in rise time, a substantial 51% decrease in overshoot, and an impressive 99% reduction in cost value. In addition, the intervention of the proposed method completely eradicates steady-state errors, thus addressing a critical aspect of control system performance. [ABSTRACT FROM AUTHOR]

Metal defects detection has always been an essential task for the majority of various industries, moreover, it is the core element in the metal inspection too. This research paper explores the effectiveness of different deep learning algorithms for surface-defect detection in investment casting using the Inspection 4.0 approach. The study compared the performance of four popular deep learning algorithms, Fast R-CNN, Faster R-CNN, ResNet, and YOLO, using the accuracy metric as a performance evaluation measure. The results show that ResNet achieved the highest accuracy rate of 95.89%, followed by Faster R-CNN with 90.23%, Fast R-CNN with 89.21%, and YOLO with 86.43%. The findings of this research demonstrate that ResNet and Faster R-CNN are effective deep-learning algorithms for automated surface-defect detection in investment casting. On the other hand, Fast R-CNN and YOLO exhibited lower accuracy rates. The outcomes of this study provide valuable insights into the effectiveness of deep learning algorithms for surface-defect detection in investment casting. The high accuracy rate achieved by ResNet and Faster R-CNN can guide the development of automated inspection systems for investment casting in various industries such as aerospace, automotive, and medical. [ABSTRACT FROM AUTHOR]

This paper focuses on life prediction models considering the variability of loads. It describes the fatigue strength and crack growth behavior of AISI 304L austenitic stainless steel at room temperature. The deformation behavior of the austenitic stainless steel was investigated via tensile and fatigue tests. Crack tests were performed on CT50 specimens for constant ΔP and ΔK under different cyclic loads before the specimen was severely cracked by a monotonically increasing load. The impact of loading sequence and the evolution of the dissipated energy ΔJ were investigated using constant charge ΔP and stress intensity ΔK. The dissipated energy per cycle is used to predict fatigue crack growth. Experimental results proved that the various parameters considered in terms of cyclic loading and the results obtained under monotonic loading up to unstable failure show that cracking at constant ΔP is significantly more damaging than at constant ΔK. Therefore, cyclic loading with a constant pressure drop will result in faster crack growth or shorter fatigue life than loading with a constant stress intensity factor ΔK. [ABSTRACT FROM AUTHOR]

Rapid development has occurred recently in the use of thermoelectric generators (TEGs), as they have been applied in numerous fields. Although TEGs can harvest the body's energy, the output voltages they yield are extremely small (a few hundred mV). Accordingly, the objective of this paper is to study the possibility of enlarging a voltage generated by the TEG to a level where it can be used. In this paper, we provide a comprehensive simulation of the performance of TEGs system that harvests human energy by using one topology of the conversion circuit, the DC/DC step-up converter, that raises the external voltage so that portable mobile devices can be charged. In the proposed system ten pieces of the TEGs have been used, every system contains 35 TEG couples connected serially by legs. The methodology of the current study focuses on using the finite element method (FEM) to simulate the TEG system, where we used ANSYS Workbench software platform (Professional Version 18.1). Moreover, MATLAB and PSPICE Simulink have been used to simulate the energy conversion circuit. The outcomes of this study can be summarized in the following points: 1) the total voltage obtained from the ten pieces of the TEG system is about (2.165V). 2) Using the boost DC/DC converter system help to enlarge the total voltage of TEG to 5 Volt. 3) There is no signifying effect for the different shapes of TEG legs, where a comparison was made between two different shapes of TEG legs, one is rectangular and the other is equivalent cylindrical. 4) The results of TEG were also compared with the results of previous work, and a good agreement has been attained. 5) MATLAB - PSPICE simulation programs were used to design and implement the DC-to-DC boost converter circuit, and the results showed the output response of the overall system being in line with the study objectives. [ABSTRACT FROM AUTHOR]

Hybrid ventilation systems present many advantages compared to the natural or mechanical ventilation systems. In the case of buildings with significant heat gains, they seem to be the proper solution, if correctly analyzed and designed. The paper presents the calculations and study of the natural ventilation parameters with the possibility of including roof fans in the model glasswork in Kielce, Poland. The calculations for the optimization process were conducted using Ventos software. The limitations of the method include maximal values of air temperature at the top of the building, air velocity at the inlets and outlets, and negative pressure. Conclusions for the summer season arise that the most optimal solution ensuring the minimum internal temperature and air velocity conditions for the glassworks building is the use of wall inlets located on two levels. On the other hand, in winter conditions not all wall intakes should be open. Further analyses and simulations were performed for hybrid ventilation. Assessments confirm the accuracy and efficiency of using natural ventilation in facilities with significant heat gains, including glassworks. [ABSTRACT FROM AUTHOR]

In the most industrial process and air conditioning systems, huge amount of heat are generated for better performance. The shower cooling tower (SCT) is used for heat transfer to the environment. In this study, mathematical modeling and tower behavior simulate based on the laws of heat and mass transfer. This is done after reviewing papers and rewriting governing differential equations using a computer program to solve numerical solution and then analyzing tower behavior. Also, the effect of physical parameters (the velocity of water droplet, inlet air velocity and water to air mass flow ratio) on reducing the outlet temperature of the water has been checked and compared with the results of the experiment, which has a great accuracy. Simulated data shows that, as the inlet air velocity increases, the corresponding heat and mass transfer coefficients increase, outlet temperature from tower decreases. Also due to the excessive increase in the droplet velocity, it does not have much effect on reducing the temperature of the outlet. By increasing the water to air mass flow ratio, decreasing of temperature is reduced. [ABSTRACT FROM AUTHOR]

Amylases can hydrolyze the O-glycosyl linkage of starch and related polymers. They are ubiquitously present in all living systems. However, microbial amylases meet the demands of industrial applications. Amylase and related enzymes are classified in different glycosyl hydrolases (GH) families. The GH13 is the largest family in the carbohydrate-active enzyme (CAZy) database, which comprises α-amylase, α-glucosidase, maltogenic amylase, debranching enzymes, CGTase, pullulanase, neopullulanase, and others. Despite GH13, some other families also contain α-amylase and related enzymes. Most of the starch-degrading enzymes have a common (β/α)8 barrel structure and four or five conserved sequences containing catalytic residues. α-Amylase and related enzymes follow the α-retaining double displacement mechanism during catalysis. The enzymes of the α-amylase family are potentially applied in food, pharmaceutical, textile, paper, detergent, biofuel, and animal feed producing industries. α-Amylase-mediated liquefaction and saccharification of starch is the essential step for the production of glucose, maltose, high fructose-containing syrups, maltooligosaccharides, cyclodextrins. These products are potentially used for the preparation of geriatric and infant foods. In conclusion, starch degrading enzymes bear a common structural arrangement and catalytic activity, and are broadly exploited in different sectors ranging from food, pharmaceutical industries to wastewater treatment. [ABSTRACT FROM AUTHOR]

In present time, manufacturing industries are facing a very competitive, unpredictable, and ever changing environment, with growing complexity and high levels of customization. In order to achieve the customer satisfaction without sacrificing profitability, one hand industry leaders are trying to invent and adopt newer technologies and on the other hand, top management of industry requires an assurance of early return on their investment from its technical people/managers prior to actual investment in any new technology. Flexibility is probably among the most sought after manufacturing technologies. To address the issue, a prior study of the effect of different flexibility levels on manufacturing process is required. In the present paper an attempt has been made to understand the various flexibility types and their effect on the performance of a Manufacturing System (MS). It is observed that beyond a certain level of flexibility manufacturing system performance starts deterioting. A theoretical frame work for manufacturing system, factors affecting its performance & Manufacturing Flexibility (MF) is laid down. Further, an effort has also been made to present simple probable measure of various flexibility types. Towards the end with the arrangement of various flexibility dimensions in different categories on a flexibility pyramid, the concept of flexibility pyramid is proposed. Some further probable research areas are also identified. [ABSTRACT FROM AUTHOR]

In the present paper, a laboratory test rig is designed and constructed at Hashemite University to study and analyze the effects of road terrains on automotive suspension systems. It is also used to study and analyze the nonlinear dynamic behavior of suspension systems. The proposed experimental suspension setup facilitates testing and validating various identification and controller designs. Hence, a useful educational, training, and research tool is introduced to emulate the effects of wide range of realistic road conditions on automotive suspension systems, while rapidly measuring, recording, and analyzing system variables. It should be noted that the focus of this paper is on the design and construction of a laboratory automotive suspension system test rig. Experimental testing is intended to be conducted in the future to practically demonstrate the performance of vehicular suspension under different operating modes. [ABSTRACT FROM AUTHOR]