Blockchain Interoperability: Towards a Sustainable Payment System

The highly fragmented blockchain and cryptocurrency ecosystem necessitates interoperability mechanisms as a requirement for blockchain-technology acceptance. The immediate implication of interchain interoperability is automatic swapping between cryptocurrencies. We performed a systematic review of the existing literature on Blockchain interoperability and atomic cross-chain transactions. We investigated different blockchain interoperability approaches, including industrial solutions, categorized them and identified the key mechanisms used, and list several example projects for each category. We focused on the atomic transactions between blockchain, a process also known as atomic swap. Furthermore, we studied recent implementations along with architectural approaches for atomic swap and deduced research issues and challenges in cross-chain interoperability and atomic swap. Atomic swap can instantly transfer tokens and significantly reduce the associated costs without using any centralized authority, and thus facilitates the development of a sustainable payment system for wider financial inclusion.

Membrane applications in the food industry

Current trends in the food industry for the application of membrane techniques are presented. Industrial solutions as well as laboratory research, which can contribute to the improvement of membrane efficiency and performance in this field, are widely discussed. Special attention is given to the main food industries related to dairy, sugar and biotechnology. In addition, the potential of membrane techniques to assist in the treatment of waste sources arising from food production is highlighted.

Digital Training and Advanced Learning in Occupational Safety and Health Based on Modern and Affordable Technologies

Occupational safety and health (OSH) is a very important issue for both practical purposes in industry and business due to numerous reasons, so a number of software, educational and industrial solutions are available. In this paper, the cloud-based mobile application for digital training and advanced learning in the field of occupational safety was presented. The proposed framework architecture was based on a novel approach: Node.JS for the server backend and the React Native for the front-end development; while MongoDB was used for implementing the cloud data storage using sensors that are all available on the Android platform. In the development of this application, a number of options were developed (using open-source software) such as the reading of a QR code, usage of built-in sensors within android platforms, reporting, and voice messages. The developed SafeST solution is presented through a real industry example. It emphasizes two main possibilities of the solution, improving OHS reporting and significant empowerment of the students in the OHS field based on the learning-by-doing approach. In this way, the additional engagement (identification, recording and reporting of UA/UC) of OSH managers has been reduced to a minimum, taking into account requested reports from management and authorities, and the continual training of the employees and preparation of the students for future working activities. The system was tested for educational purposes with the initial idea to develop an application for smartphones which could be useful and well adopted among engineering students in the OSH field.

Project and Software of a Robotic Welding Station Using Virtual Reality Technology

The use of VR technology in various industries, including in the industry is constantly growing. ABB is one of the first companies to introduce programming using virtual reality to its offer. This system greatly facilitates the work of an engineer, allowing the user to interact with 3D models through virtual reality goggles. The article presents the design and software of a robotic station that enables the creation of movement instructions using virtual reality technology. The review of the existing industrial solutions using VR technology in welding simulators and other industries. A project of a welding station in the RobotStudio environment was presented and built. Software was written using virtual reality and a model of the real tool was made using the 3D printing method. The designed welding station was tested.

An Automated Recognition of Work Activity in Industrial Manufacturing Using Convolutional Neural Networks

The automated assessment and analysis of employee activity in a manufacturing enterprise, operating in accordance with the concept of Industry 4.0, is essential for a quick and precise diagnosis of work quality, especially in the process of training a new employee. In the case of industrial solutions, many approaches involving the recognition and detection of work activity are based on Convolutional Neural Networks (CNNs). Despite the wide use of CNNs, it is difficult to find solutions supporting the automated checking of work activities performed by trained employees. We propose a novel framework for the automatic generation of workplace instructions and real-time recognition of worker activities. The proposed method integrates CNN, CNN Support Vector Machine (SVM), CNN Region-Based CNN (Yolov3 Tiny) for recognizing and checking the completed work tasks. First, video recordings of the work process are analyzed and reference video frames corresponding to work activity stages are determined. Next, work-related features and objects are determined using CNN with SVM (achieving 94% accuracy) and Yolov3 Tiny network based on the characteristics of the reference frames. Additionally, matching matrix between the reference frames and the test frames using mean absolute error (MAE) as a measure of errors between paired observations was built. Finally, the practical usefulness of the proposed approach by applying the method for supporting the automatic training of new employees and checking the correctness of their work done on solid fuel boiler equipment in a manufacturing company was demonstrated. The developed information system can be integrated with other Industry 4.0 technologies introduced within an enterprise.

Data Protection through Data Security-as-a-Service using Blockchain Enabled Platform

Data access is inevitable in today’s world and it is prone to threat attacks and hence data security is utmost important for any enterprise to handle industrial solutions. The economics of data being used across the industries rapidly growing in current digital world so the potential data related threats is also rapidly growing. Data security is an integrated solution component for any Enterprise solution but with the growing demand on data security and potential threat handling, Data Security as a Service (DSaaS)f is a new model widely accepted in modern age architecture in Blockchain and Big Data world combining the power of cloud based security services, decentralized network in Blockchain and tamper-proof ledger management. Any Enterprise Security architecture comprises of how data is handled in a secured way and how integration between services (consumers/producers or API interaction or any middleware services) handles data between them. Hence it is inevitable to that future technology adoption should include Data Security-as-a-service for zero-trust solution design complying with compliance and security standards for industry.

Use of Membrane Technologies in Dairy Industry: An Overview

The use of treatments of segregated process streams as a water source, as well as technical fluid reuse as a source of value-added recovery products, is an emerging direction of resource recovery in several applications. Apart from the desired final product obtained in agro-food industries, one of the challenges is the recovery or separation of intermediate and/or secondary metabolites with high-added-value compounds (e.g., whey protein). In this way, processes based on membranes, such as microfiltration (MF), ultrafiltration (UF), nanofiltration (NF) and reverse osmosis (RO), could be integrated to treat these agro-industrial streams, such as milk and cheese whey. Therefore, the industrial application of membrane technologies in some processing stages could be a solution, replacing traditional processes or adding them into existing treatments. Therefore, greater efficiency, yield enhancement, energy or capital expenditure reduction or even an increase in sustainability by producing less waste, as well as by-product recovery and valorization opportunities, could be possible, in line with industrial symbiosis and circular economy principles. The maturity of membrane technologies in the dairy industry was analyzed for the possible integration options of membrane processes in their filtration treatment. The reported studies and developments showed a wide window of possible applications for membrane technologies in dairy industry treatments. Therefore, the integration of membrane processes into traditional processing schemes is presented in this work. Overall, it could be highlighted that membrane providers and agro-industries will continue with a gradual implementation of membrane technology integration in the production processes, referring to the progress reported on both the scientific literature and industrial solutions commercialized.

Control Strategies for Reactive Extrusion of Polypropylene by Peroxide Degradation A Brief Review and an Experimental Study

Industry 4.0 and digitalization are widely argued for the future success of numerous industrial solutions. Big data management might lead to the assumption that every issue can be solved numerically without any physical background. To some extent, this strategy will help within the plastics industry in general and in the extrusion technology in particular. However, a deep process knowledge together with process-relevant sensors, as well as the right process arrangements within the processing chain combined with smart data mining methods will be still the key success of industry 4.0. This presentation illustrates, based on a brief review on existing control strategies (Part 1), including sensory and predictive control models for reactive extrusion applied at a real-life on-site best practice project (Part 2), possibilities in combination of process tasks with digitalization approaches for PP-Polymer production. Specifically, rheological research conducted with a novel, patented multi-point rheometer (part 3), will provide a deeper insight into dynamic processes such as reactive extrusion. With those results and derivations thereof, improvements in predictive process control in addition to artificial control systems are made and might even lead to further interesting opportunities.