Business analytics in industry 4.0: a systematic review

Recently, the term “Industry 4.0” has emerged to characterize several Information Technology and Communication (ICT) adoptions in production processes (e.g., Internet-of-Things, implementation of digital production support information technologies). Business Analytics is often used within the Industry 4.0, thus incorporating its data intelligence (e.g., statistical analysis, predictive modelling, optimization) expert system component. In this paper, we perform a Systematic Literature Review (SLR) on the usage of Business Analytics within the Industry 4.0 concept, covering a selection of 169 papers obtained from six major scientific publication sources from 2010 to March 2020. The selected papers were first classified in three major types, namely, Practical Application, Reviews and Framework Proposal. Then, we analysed with more detail the practical application studies which were further divided into three main categories of the Gartner analytical maturity model, Descriptive Analytics, Predictive Analytics and Prescriptive Analytics. In particular, we characterized the distinct analytics studies in terms of the industry application and data context used, impact (in terms of their Technology Readiness Level) and selected data modelling method. Our SLR analysis provides a mapping of how data-based Industry 4.0 expert systems are currently used, disclosing also research gaps and future research opportunities.The work of P. Cortez was supported by FCT - Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. We would like to thank to the three anonymous reviewers for their helpful suggestions

An Approach for Online Weight Update Using Particle Swarm Optimization in Dynamic Fuzzy Cognitive Maps

Fuzzy cognitive maps (FCM) is a method to update a given initial vector to obtain the most stable state of a system, using a neighborhood of weights between these vectors and updating it over a series of iterations. FCMs are modeled with graphs. Neighbor weights between nodes are between-1 and 1. Nowadays it is used in business management, information technology, communication, health and medical decision making, engineering and computer vision. In this study, a dynamic FCM structure based on Particle Swarm Optimization (PSO) is given for determining node weights and online updating for modeling of dynamic systems with FCMs. Neighborhood weights in dynamic FCMs can be updated instantly and the system feedback is used for this update. In this work, updating the weights of the dynamic FCM is a PSO based approach that takes advantage of system feedback. In previous literature suggestions, dynamic FCM structure performs the weight updating process by using rule-based methods such as Hebbian. Metaheuristic methods are less complex and more efficient than rule-based methods in such optimization problems. In the developed PSO approach, the initialize vector state of the system, the weights between the vector nodes, and the desired steady state vector are taken into consideration. As a fitness function, the system has benefited from the convergence state to the desired steady state vector. As a stopping criterion for PSO, 100 ∗ n number of iteration limits have been applied for the initial vector with n nodes. The proposed method has been tested for five different scenarios with different node counts. © 2018 IEEE

Effect of Sc Addition on the Microstructure and Mechanical Properties of Melt-Spun Al-10Ni Alloys

In the present work, rapidly solidified Al-10Ni-XSc (X = 0, 1 and 2) alloys were fabricated by melt spinning under Ar atmosphere. The Effects of Sc on the microstructural and thermal properties and microhardness values were investigated by scanning electron microscopy (SEM), X-ray diffractometer (XRD) and a Vickers microhardness tester. Experimental results revealed that the addition of 2 wt. % Sc to melt-spun Al-10Ni alloys changed their brittle nature and hindered formation of cracks. The addition of Sc to melt-spun Al-10Ni alloys also changed the morphology of Al3 Ni intermetallics from an acicular/needle – like to a rounded particle-like structure and led to reduction in their size. Formation of the metastable Al9 Ni2 phase was observed due to the higher constitutional undercooling caused by Sc addition. A considerable improvement in microhardness value (from 95. 9 to 230. 1 HV) was observed with the addition of Sc

Type-2 fuzzy based quadrotor control approach

2013 9th Asian Control Conference, ASCC 2013 -- 23 June 2013 through 26 June 2013 -- Istanbul -- 100340Unmanned air vehicles has recently become applications that are being increasingly used in both unmilitary and military areas and that are popular fields of research. The quadrotor type among the unmanned air vehicles, which come in different types, sizes and models depending on their area of use, come into prominence with several advantages it offers. This study performs the modeling, simulation, altitude and direction controls by means of a type-2 fuzzy system of an unmanned air vehicle. A proper algorithm is required for a quadrotor due to the environmental conditions, uncertainty and noise effects. Therefore, type-2 fuzzy controller was preferred and the performance of type-2 controller was provided against the type-1 and PID control methods in the simulations were carried out in this study. Simulation results obtained in the study show the effectiveness of type-2 fuzzy controller over the other controllers. © 2013 IEEE

Production of CNT-bearing melt-spun Al-2Sc-0.05CNT alloys

In the present work, rapidly solidified Ale2Sc-XCNT (X = 0, 0.05) alloys were successfully fabricated by melt spinning under Ar atmosphere. The effects of addition of CNT on the microstructural, thermal, microhardness, and electrical properties were investigated by using scanning electron microscopy (SEM), X-ray diffractometer (XRD), differential calorimeter (DSC), Vickers microhardness testing and a four point probe resistivity tester. Experimental results illustrated that the addition of 0.05 wt% CNT to melt-spun Al -2Sc alloys led to the formation of equiaxed globular-like morphologies with size from 0.3 to 2.7 mu m in. In the microstructure of Al-2Sc-0.05CNT alloy, CNTs covered by Al with size (width and length) changing from 40 to 55 nm and 255-295 nm, respectively, were observed. The addition of CNT led to a net increment (similar to 25%) in microhardness values due to solitary strengthening of the carbon nanotubes, solute solution hardening and modification of the morphologies of Al3Sc intermetallics. In addition, because of CNT addition there was a decrease in the electrical resistivity. (C) 2017 Elsevier B.V. All rights reserved

Multiple Object Tracking with Dynamic Fuzzy Cognitive Maps Using Deep Learning

Object tracking is the process of matching objects detected on image sequences onto image frames. There are different types of object tracking applications used for different scenarios. For example, if a single object is being traced on an image, this is a single object tracking application. Tracking multiple objects on an image is called multiple object tracking. Fuzzy cognitive maps, on the other hand, form the model of a system by using the features of a system and the relationships between these features. Here, the single object tracking process is a matching problem, so FCM assumes a classifier role. In conventional operations, FCMs use the same weight matrix for all initial concept values. This can reduce the performance of the solution that the FCM produces for the problem it tackles. The FCM structure we use here takes advantage of the dynamic learning of FCM weights with deep learning. The study was tested on different image sequences and the performance of the proposed method were very satisfactory. © 2019 IEEE

Formation of novel rice-like intermetallic phases and changes in the mechanical, microstructural and electrical properties of Sn-5Sb alloys with addition Ag and Bi

In the present study, the effects of Ag and Bi additions (1 wt.%) on the microstructural, thermal, mechanical and electrical properties of Sn-5Sb solder alloys were investigated by scanning electron microscopy (SEM), X-ray diffraction (XRD), differential scanning calorimetry (DSC), microhardness tests, and four probe measurements. It was observed that the melting point of Sn-5Sb solder alloy decreased with the addition of Ag and Bi. It was found that the final microstructure of rapidly solidified Sn-5Sb-1X (X = Ag and Bi) alloys was strictly dependent upon the wheel speeds; the microstructures changed from a coarse dendritic and needle-like structure to a refined ultra fine dendritic and rice-like structure with increasing wheel speed. Cooling rate was also effective on both the mechanical and electrical properties. It was found that all of the alloys exhibit higher mechanical properties with increasing cooling rate and/or decreasing testing temperature. Similarly, significant improvements of 32% and 9% in electrical conductivity of both of the alloys were obtained with the addition of Ag and Bi, respectively. The microstructural evolution of the Sn-5Sb based alloys plays a crucial role in influencing the mechanical properties of these alloys. (C) 2015 Elsevier B.V. All rights reserved