Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0

Abstract

Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.     

Effects of Solvent Exchange Period and Heat Treatment on Physical and Chemical Properties of Rice Husk Derived Silica Aerogels

In this study, hydrophobic silica aerogels were synthesized from rice husk ash-derived sodium silicate through sol-gel processing, solvent exchange, surface modification and ambient pressure drying. By volume, 10% of trimethylchlorosilane (TMCS) in 90% of n-hexane was used as a hydrophobic solution in the surface modification process. The physical and chemical properties of silica aerogels were characterized by density and porosity measurements, scanning electron microscopy (SEM), Fourier transforms infrared (FTIR) spectroscopy, Brunauer–Emmett–Teller theory (BET) and dynamic scanning calorimetry (DSC). The hydrogels prepared were in the form of 2.5 ± 0.5 mm beads and then converted into alcogels through solvent exchange with ethanol for repetition of 3, 6 and 9 days. It is found that the optimal quality of silica aerogels with the BET surface area as high as 668.82 m²/g was obtained from the alcogels of the solvent exchange period of 9 days. Depending on the size of the gel’s block, a longer solvent exchange period will ensure adequate removal of pore water. Post heat treatment on silica aerogels obtained from the 9 days of solvent exchange at 200, 300 and 400 °C for 2 h results in slight decreased of aerogel’s density from 0.048 g/cm³ to 0.039 g/cm³ and the hydrophobicity of the aerogels is decreased above 380 °C as confirmed by DSC analysis.

     

Satellite-Based Water Quality Mapping from Sequential Simulation with Parameter Outlier Removal

The satellite-based regression model provides the data model that identifies water quality for inland and coastal waters. However, the satellite regression usually depends on the selection of observation, satellite data, and model type. A resampling simulation technique, such as sequential simulation using geographically weighted regression (GWR simulation), can be applied in generating multiple realizations for water quality estimation to reduce the sampling effect and consider spatial heterogeneity. Traditional models often result in considerable underestimation in extreme observations. The GWR simulation provides the best goodness of fit and spatial varying relationship between observed water quality and remote sensing considering parameter outlier and noise removal for parameter stability. This simulation model can increase the sampling diversity from various observations and reduce the neighboring effects of observations using outlier and noise removal. The model that handles spatial uncertainty and heterogeneity is a novel tool for inferring the characteristics of water quality from a series of sample subsets.

     

An interpretability security framework for intelligent decision support systems based on saliency map

International Journal of Information Security - Benefiting from the high-speed transmission and super-low latency, the Fifth Generation (5G) networks are playing an important role in contemporary...     

Stress Reduction of 3D Printed Compliance‐Tailored Multilayers

Multilayered multi‐material interfaces are encountered in an array of fields. Here, enhanced mechanical performance of such multi‐material interfaces is demonstrated, focusing on strength and stiffness, by employing bondlayers with spatially‐tuned elastic properties realized via 3D printing. Compliance of the bondlayer is varied along the bondlength with increased compliance at the ends to relieve stress concentrations. Experimental testing to failure of a tri‐layered assembly in a single‐lap joint configuration, including optical strain mapping, reveals that the stress and strain redistribution of the compliance‐tailored bondlayer increases strength by 100% and toughness by 60%, compared to a constant modulus bondlayer, while maintaining the stiffness of the joint with the homogeneous stiff bondlayer. Analyses show that the stress concentrations for both peel and shear stress in the bondlayer have a global minimum when the compliant bond at the lap end comprises ≈10% of the bondlength, and further that increased multilayer performance also holds for long (relative to critical shear transfer length) bondlengths. Damage and failure resistance of multi‐material interfaces can be improved substantially via the compliance‐tailoring demonstrated here, with immediate relevance in additive manufacturing joining applications, and shows promise for generalized joining applications including adhesive bonding.     

Implementation of VLSI on Signal Processing-Based Digital Architecture Using AES Algorithm

Continuous improvements in very-large-scale integration (VLSI) technology and design software have significantly broadened the scope of digital signal processing (DSP) applications. The use of application-specific integrated circuits (ASICs) and programmable digital signal processors for many DSP applications have changed, even though new system implementations based on reconfigurable computing are becoming more complex. Adaptable platforms that combine hardware and software programmability efficiency are rapidly maturing with discrete wavelet transformation (DWT) and sophisticated computerized design techniques, which are much needed in today’s modern world. New research and commercial efforts to sustain power optimization, cost savings, and improved runtime effectiveness have been initiated as initial reconfigurable technologies have emerged. Hence, in this paper, it is proposed that the DWT method can be implemented on a field-programmable gate array in a digital architecture (FPGA-DA). We examined the effects of quantization on DWT performance in classification problems to demonstrate its reliability concerning fixed-point math implementations. The Advanced Encryption Standard (AES) algorithm for DWT learning used in this architecture is less responsive to resampling errors than the previously proposed solution in the literature using the artificial neural networks (ANN) method. By reducing hardware area by 57%, the proposed system has a higher throughput rate of 88.72%, reliability analysis of 95.5% compared to the other standard methods.     

Exploring the relationship between Internet ethics in university students and the big five model of personality

The widespread use of the Internet and the convenient mechanism it provides, such as easy access, easy downloads, and easy copy and paste functions have made many types of unethical behaviors easier, particularly those involving students in academic settings. Among the issues in ethics within the academic environment that can be triggered by the Internet are fraudulence, plagiarism, falsification, delinquency, unauthorized help, and facility misuse. Given these issues, the study seeks to investigate the extent to which students at a public university in Malaysia engage in such unethical behavior and their relationship with the big five personality model. This study was conducted using a survey method of 252 students in three different academic faculties. The results of factor analyses confirm and refine the reliability of the scales for both big five personality variables and unethical Internet behaviors as conceptualized through Internet triggered academic dishonesty (ITADS). The findings indicate that personality traits such as (1) agreeableness, (2) conscientiousness and (3) emotional stability are significantly and negatively correlated with unethical Internet behavior in university students. Significant differences in facility misuse are also observed between the three academic faculties investigated. This research should provide significant contributions to educators in designing the computer ethics curriculum and in allowing for educational institutions as well as other organizations in developing relevant policies and guidelines on matters pertaining to academic conduct, utilization of computers and Internet, and recruitment exercises.     

In vitro antioxidant and in vivo xanthine oxidase inhibitory activities of Pandanus amaryllifolius in potassium oxonate‐induced hyperuricemic rats

Xanthine oxidase (XO) plays an important role in the regulation of uric acid and prevents it from being overproduced as in hyperuricemia disease. The combined effects of antioxidant and xanthine oxidase inhibitor would become a promising approach for hyperuricemia treatment. In this research, the antioxidant and xanthine oxidase inhibitory activities of Pandanus amaryllifolius leaf were evaluated. The leaf water extract (PA‐W) showed highest total phenols, and petroleum ether extract (PA‐PE) showed highest total flavonoids contents. The antioxidant activity of DPPH, metal chelating and hydrogen peroxide was highest in PA‐W extract. The treatment of PA‐W extract at 1000 mg kg^?1 body weight in potassium oxonate‐induced hyperuricemic rats showed significant (P < 0.001) decrease in serum uric acid level by 85% and XO activity by 64%, respectively, as compared to the hyperuricemic rats. In conclusion, the P. amaryllifolius possess the dual effect of antioxidant and XO inhibition as potential therapeutic agents in the hyperuricemia treatment.     

Application of common transformers faults diagnosis methods on biodegradable oil-filled transformers

Due to environmental concerns regarding the use of mineral oil, biodegradable oil is increasingly being used as an alternative dielectric fluid. This paper presents results of experiments performed in the laboratory on the use of biodegradable oils for transformer application. The investigations cover two important diagnostic techniques for insulation assessment: (i) an investigation of partial discharge (PD) activity and characteristics in such oils and (ii) an investigation of the standard hydrocarbon dissolved gas products produced due to transformer faults. The fundamental aim of the investigation was to provide information as to whether the existing analysis techniques of PD fault pattern recognition and dissolved gas analysis methods, developed for mineral oil, are valid when used for insulation assessment with biodegradable transformer oil. The experiments were conducted on test samples to simulate three common types of transformer faults: low-energy PDs, high-energy arcing/sparking, and overheating. For the purpose of comparison, the same tests were performed using a mineral oil (Shell Diala MX) and a biodegradable oil (Envirotemp FR3). Also, each oil type was tested at three different moisture levels and with or without the presence of solid insulating materials (pressboard). PD activity was monitored using the standard IEC60270 phase-resolved analysis method. The fault gases produced were extracted and analysed by standard gas chromatography methods. Test results indicate that the PD phase resolved patterns are, in general, similar for the two oil types and thus existing PD pattern interpretations can be used to distinguish different types of PD faults, e.g. corona versus surface discharges. However, the values of various discharge quantities (PD magnitudes, repetition rate, current, etc) are very different under the same test condition. The quantities and the trend of dissolved gases for faults in biodegradable oil are substantially different compared with mineral oil. For the PD fault, biodegradable oil was found to release only a limited number of gases. For arcing and overheating faults, the main key gas produced is different between the two oils. Also, the presence of cellulosic materials such as pressboard influences the extent of hydrocarbon gases dissolved in the oil. It was found that for biodegradable oil, fewer amounts of gases are produced as the oil gets wetter.     

Experimental study of the natural organic matters effect on the power generation of reverse electrodialysis

In this paper, the effect of natural organic matters (NOMs), which are typically present in river and seawater, on the power generation of reverse electrodialysis was studied. Bovine serum albumin, humic acid, and sodium alginate were used as models of NOMs. A NOM model was added to concentrated salt water, diluted salt water, and/or both of them. Power density was used to measure the resulted power generation. Fourier transform infrared spectroscopy and scanning electron microscope were used to characterize the presence of NOMs on the membrane surfaces. The effect of NOMs on the generated power density was clearly observed. This effect was influenced by the NOM's type, the NOMs concentration, and the compartment in which NOMs are added. Fourier transform infrared spectroscopy and scanning electron microscope data confirmed that NOMs are deposited on both anion and cation exchange membrane surfaces. While all NOMs added to concentrated salt water did not influence the generated power density, different power density behavior was resulted from the different NOMs added to diluted salt water, where NOMs could increase or decrease or remain the generated power density. Thus, besides NOM's type, the salt concentration is very critical to determine the effect of NOMs on the generated power density. Copyright © 2017 John Wiley & Sons, Ltd.