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.     

A Code Assignment Algorithm for Nonblocking OVSF Codes in WCDMA

OVSF codes are used as channelization codes in WCDMA. Due to code blocking property of OVSF codes, the bandwidth available in the system is severely limited. Code reassignments mitigate the impact of the blocking property at the expense of causing delays and decreasing the throughput of the system. Nonblocking OVSF (NOVSF) codes have been proposed to alleviate the adverse effect of code reassignments. This paper presents a code assignment algorithm for NOVSF codes, which does not require any code reassignments. Simulation results show that NOVSF codes achieve better throughput than OVSF codes, even though code reassignments are allowed in the assignments of OVSF codes.     

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     

Characterization of rheological properties of systems containing sugar substitutes and carrageenan

The effects of addition of κ-carrageenan to solutions containing 40% (w/w) sugar substitute on the rheological properties of these systems were investigated at 25 °C using a rotational viscometer at rotational speeds of 6, 12, 30, and 60 rev min⁻¹. The flow behaviour of the solutions was adequately described by the power law model with or without yield stress. The consistency index ( K ) and the flow behaviour index ( n ) were determined from shear stress vs. shear rate data. The flow parameters of the solutions depended on the carrageenan concentration. The apparent viscosities of the systems decreased with increasing shear rate, indicating pseudoplastic behaviour. The final carrageenan concentration was found to be an effective factor controlling the degree of sliminess of the model food systems studied.     

Studies on the interactions of metal oxides and Na2 SO4 at 1100 and 1200 K in oxygen

The interaction of different metal oxides such as Co₃O₄, NiO, Al₂O₃, Cr₂O₃, Fe₂O₃ and SiO₂ with Na₂SO₄ at a temperature of 1100 and 1200 K in flowing oxygen has been studied. The thermogravimetric studies for each system were carried out as a function of Na₂SO₄ in the mixture. The presence of different constituents in the reaction products were identified by X-ray diffraction analysis and the morphologies of the reaction products were characterized using metallography and scanning electron microscopy (SEM). The formation of products was also investigated by thermodynamic computation of free energies of the reactions and the study of relevant equilibrium phase diagrams. The soluble species in the aqueous solutions of the reaction products were determined quantitatively using atomic absorption spectrophotometry. The high temperature interaction products usually contain a 3-phase structure namely, Na₂O·M₂O _x , M₂O _x and metal sulphide and/or metal sulphate. The formation of Na₂O·M₂O _x depends upon the solid state solubility of metal oxide in the molten salt at high temperatures. Under limited solubility conditions Na₂O·M₂O _x is invariably formed, but as soon as this condition is relaxed the oxide. M₂O _x , precipitates and forms a separate phase.     

Simultaneous mass and heat transfer under mixed convection along a vertical cone

Steady laminar binary mixed convection flow along a vertical circular cone under the combined buoyancy effects of thermal and species diffusion is studied analytically. The analysis is confined to mass diffusion processes with low concentration levels. In the analysis the surface of the cone is assumed to be at a uniform temperature and uniform concentration. Numerical results for the local Sherwood number, local Nusselt number and local friction factor are presented. Representative temperature, concentration and velocity profiles are also shown. The analysis covers the diffusion of common gases and vapours into air. Considerations are given to the situations where the buoyancy forces assist and oppose the forced convection flow for various possible combinations of the thermal and species diffusion processes.     

Intelligent non-linear modelling of an industrial winding process using recurrent local linear neuro-fuzzy networks

This study deals with the neuro-fuzzy (NF) modelling of a real industrial winding process in which the acquired NF model can be exploited to improve control performance and achieve a robust fault-tolerant system. A new simulator model is proposed for a winding process using non-linear identification based on a recurrent local linear neuro-fuzzy (RLLNF) network trained by local linear model tree (LOLIMOT), which is an incremental tree-based learning algorithm. The proposed NF models are compared with other known intelligent identifiers, namely multilayer perceptron (MLP) and radial basis function (RBF). Comparison of our proposed non-linear models and associated models obtained through the least square error (LSE) technique (the optimal modelling method for linear systems) confirms that the winding process is a non-linear system. Experimental results show the effectiveness of our proposed NF modelling approach.     

Data stream classification with novel class detection: a review,comparison and challenges

Knowledge and Information Systems - Developing effective and efficient data stream classifiers is challenging for the machine learning community because of the dynamic nature of data streams. As a...     

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...