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.     

Effect of Thin Film Thicknesses and Materials on the Response of RTDs and Microthermocouples

Fabrication and thermal characterization of a resistance temperature detector (RTD) heater and microthermocouples (MTs) on silicon substrates have been reported in this paper. The influence of film thickness and nickel-gold (Au) electroplating on RTD on its steady-state temperature with respect to its steady-state electrical power input and resistance is studied. Further, the thermal effects of multiple thermocouples in a thermopile as well as the effects of Au layers in the contact pads of the thermopiles on their open-circuit Seebeck voltage are studied. Therein lies the novelty of this paper. The in situ operating relationships for the RTD heater and the MT are provided     

Haemolytic activity of Aeromonas species isolated in Libya

Twenty seven Aeromonas strains (5A. hydrophila, 8A. sobria and 14A. caviae) isolated from children with diarrhoea and 34 Aeromonas strains (9A. hydrophila, 7A. sobria an 18A. caviae) isolated from children without diarrhoea were tested from haemolysin production. The results obtained showed that haemolysin production using human, horse or sheep erythrocytes was significantly associated with A.hydrophila and A sobria but not with A.caviae, regardless of whether these strains were isolated from children with or without diarrhoea. Human or horse rather than sheep erythrocytes are recommended for use in the haemolysin assay.     

A dynamic variability management approach working with agile product line engineering practices for reusing features

The Journal of Supercomputing - Agile software development (ASD) and software product line (SPL) have shown significant benefits for software engineering processes and practices. Although both...     

Ambient‐cured polyesteramide‐based anticorrosive coatings from linseed oil—A sustainable resource

Ambient‐cured polyesteramide (APEA) coating resin synthesized from dihydroxy fatty amide obtained from linseed oil, a sustainable resource, and poly(styrene‐co‐maleic anhydride), a bifunctional acid component, was found to exhibit improved physicomechanical and anticorrosive properties. The structural elucidation of APEA resin has been carried out by FTIR, ¹H‐NMR, and ¹³C‐NMR spectroscopies. The physicomechanical and chemical resistance properties were investigated by standard methods. The corrosion resistance performance was evaluated in acid, alkali, and organic solvent. The thermal behavior was studied by TGA technique. A comparative study of these properties of APEA with reported baked polyesteramide (PEA) coatings was carried out. A remarkable improvement in the drying property of APEA was observed. The APEA coatings also showed improved physicomechanical and anticorrosive properties as compared to the baked PEA coatings. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 1818–1824, 2005     

Silhouette-based human action recognition using SAX-Shapes

Human action recognition is an important problem in Computer Vision. Although most of the existing solutions provide good accuracy results, the methods are often overly complex and computationally expensive, hindering practical applications. In this regard, we introduce the combination of time-series representation for the silhouette and Symbolic Aggregate approXimation (SAX), which we refer to as SAX-Shapes, to address the problem of human action recognition. Given an action sequence, the extracted silhouettes of an actor from every frame are transformed into time series. Each of these time series is then efficiently converted into the symbolic vector: SAX. The set of all these SAX vectors (SAX-Shape) represents the action. We propose a rotation invariant distance function to be used by a random forest algorithm to perform the human action recognition. Requiring only silhouettes of actors, the proposed method is validated on two public datasets. It has an accuracy comparable to the related works and it performs well even in varying rotation.     

Miscibility behavior of blend of polyesteramides of linseed oil and dehydrated castor oil with poly(methacrylic acid)

Blending of two polymers in solution is a simple and cost‐effective technique to improve upon the physical and mechanical properties of the component polymers through synergism. To obtain maximum synergy in their properties, the component polymers should be miscible with each other on molecular scale. Polymer blends of complex physicomechanical properties are being actively investigated. Poly(methacrylic acid) (PMAA), a commercial polymer, yields transparent, hard, brittle, and water‐sensitive films. It has been blended with natural polymers like dextran, collagen, and gelatin to obtain films with improved physical and mechanical characteristics. Polyesteramides, which are easily synthesized from vegetable seeds oil, a sustainable resource, have found application in surface coatings. These oligomeric products do not make free standing films in the ambient condition. The polyesteramides from vegetable seeds oil can be used to obtain blend with PMMA of improved mechanical and water absorption properties. In this study, linseed oil polyesteramide (LOPEA) and dehydrated castor oil polyesteramide (DCPEA), the source oils with different unsaturation in their fatty acid chains, were blended with PMAA through mixing in solution in the ratio DCPEA/LOPEA: PMAA as 80/20, 70/30, 60/40, 50/50, 40/60, 30/70, and 20/80. In the first instance, the miscibility of the two components was investigated in solution by viscosity and ultrasonic measurements and in solid phase through differential scanning calorimetry (DSC) and scanning electron microscopy (SEM). Moisture absorption by the blend was also studied. DCPEA and LOPEA show immiscibility with PMAA in solution phase while LOPEA with more unsaturation in the fatty acid chain of the oil was found more immiscible than DCPEA. DCPEA shows a narrow miscibility window in the solid phase while LOPEA was found immiscible with PMAA in the solid phase too. Uptake of moisture was found to be markedly reduced in the blends of DCPEA/LOPEA with PMAA. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 1367–1374, 2007:     

Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks

Anomaly detection in resource constrained wireless networks is an important challenge for tasks such as intrusion detection, quality assurance and event monitoring applications. The challenge is to detect these interesting events or anomalies in a timely manner, while minimising energy consumption in the network. We propose a distributed anomaly detection architecture, which uses multiple hyperellipsoidal clusters to model the data at each sensor node, and identify global and local anomalies in the network. In particular, a novel anomaly scoring method is proposed to provide a score for each hyperellipsoidal model, based on how remote the ellipsoid is relative to their neighbours. We demonstrate using several synthetic and real datasets that our proposed scheme achieves a higher detection performance with a significant reduction in communication overhead in the network compared to centralised and existing schemes.     

Light weight model for intra mode selection in HEVC

Multimedia Tools and Applications - The High Efficiency Video Coding (HEVC) efficiently reduces the size of the multimedia contents, but at the cost of high computation complexity. In order to make...     

哈尔滨地区汛期径流量变化趋势与复杂性分析

区域水文要素复杂性研究是当今的热点问题,为了研究哈尔滨地区汛期径流量的复杂性特征及变化趋势,将R/S分析法和等概率粗粒化LZC算法引入到区域径流复杂性分析与变化趋势预测中,对地区内10个水文站点的汛期径流序列的复杂性进行诊断并对其变化趋势进行分析。研究结果表明:哈尔滨、通河、阿城、依兰、烟囱山各站未来的汛期径流量呈减少趋势,岔林河、莲花、西北河、延寿、四平山各站未来的汛期径流量呈增长趋势;各站点汛期径流序列的复杂度由高到低依次为:四平山、烟囱山、岔林河、阿城、西北河、依兰、莲花、通河、哈尔滨、延寿;从河流集水面积对其径流长程相关性和复杂性的影响可以看出,站点的河流集水面积越大,其径流量的长程相关性越强,复杂性指数越小。研究成果揭示了本地区汛期径流量的变化趋势以及复杂性演变特征,该特征可为区域径流预测及水资源优化配置提供科学依据。