International Scientific Journals
of Scientific Technical Union of Mechanical Engineering "Industry 4.0"

All production processes in the world are implementing Industry 4.0 by using the basic technologies such as robotics & automation, intelligent sensors, 3D printers, radio frequency identification – RFID, cloud computing, Internet of Things and Internet of Services. Implementation of Industry 4.0 in all production processes is not possible without the use of both industrial and service robots, their development and implementation. In addition, there are other technologies on which the fourth industrial revolution is based that will provide us with intelligent devices, intelligent production processes, intelligent logistics in production processes, i.e. intelligent factories. The Cyber-Physical Systems (CPS) in the global environment provide machine networking in production processes and logistics systems. This paper provides an example of the use of service robots and their role in solving smart transport in production processes.

The article deals with current situation of design of production lines in modern factories and describes possibilities of realization new type of industry lines. The main research deals with proposal of modular production system established from intelligent manufacturing cells. Main positive features of suggested structure are possibility of rapid reconfigurability of the production line, easy maintenance and possibility of simple and fast design of new production lines, thanks to modularity. To achieve these features in the Industry 4.0 ecosystem is necessary to use of modern communication methods and technologies, such as wireless industrial communication and IoT together with cooperative robots. Moreover, the entire system has to be designed as hierarchical, demand synchronized, flexible and is using standardized construct components.

Production starts with supply of raw materials and cutting of this input to the desired dimensions in order to be taken to the production line. Sawing machines used to bring the raw material to the desired dimensions in the industrial manufacturing companies are of great importance and maintain the identity of being the indispensable machine tool of almost all the enterprises’ machine parks. Considering the transition to Industry 4.0 in next 10-15 years, Turkey, which has a significant market share in the production of sawing machines, still needs to be sustainable export to countries like EU Countries and the United States which have the highest level of preparation for Industry 4.0 is directly related to meeting the expectations of these countries. In this study, for both of to raise the level of preparedness and to increase the export potential of Turkey, it is aimed to determine which criteria should be taken as basis in the development of saw machines capable of meeting industry 4.0 requirements. As a result of the evaluation, to meet Industry 4.0 requirements it have been come fore to meet the needs such as adaptation of processing and cutting conditions with barcode data, optimization of cutting conditions by data analysis, remote monitoring and control by communication with desktop and mobile devices, real-time tracking for predictive maintenance and apply maintenance plan in concept of dark factories.

The Industrial Predictive Analytics for Industry 4.0 is a system that predict and prevent machine failures and breakdown by analyzing time-series data (temperature, pressure, vibration etc.) received from sensors embedded in machines and equipment. The system can analyze machine parameters to identify patterns and predict breakdowns before they happen. The core of the proposed system is based on Artificial Neural Network approach (both Deep and Shallow Neural Networks). Artificial Intelligence and Artificial Neural Networks allow analyses the huge amounts of data collected from the manufacturing process and predict what will go wrong, and when. The proposed system works in the paradigm of Industry 4.0 and provides the abilities in the area of predictive maintenance. The Industrial Predictive Analytics for Industry 4.0 also contains a decision-making system and support system that significantly increases the level of maintenance.

The strategic initiative Industry 4.0 implies integration of Cyber-Physical Production Systems (CPPS), Internet of Things (IoT) and cloud computing, leading to what is called “smart factory”. The lack of theoretical foundation and methodologies for development of CPPS creates barriers that may hamper the adoption, commercialization, and market success of the new CPPS applications. Standardization and digitalization are at the heart of the methodologies for developing intelligent cyber-physical production systems. OPC UA is the only recommended communication standard within the RAMI reference architecture. Here comes the main purpose of the paper to analyze OPC UA in respect to the information model creation and measures to ensure security of applications. An important place in the paper is devoted to the specification of standardized information models of other organizations, such as those of the ISA-95 (IEC-62264).

While many modern industries are tending to use UFV (unmanned flying vehicles) in a near future, there are also many problems of yet unknown procedures to make possible the usage of such UFV. In a current age of aviation development there is an approach of FRA (free routing area) utilization to support growing congestion of many flying vehicles in air space. From our prospective, those manufacturing implementing “Industry 4.0” ideas are expected to use UFV to support supply chains. Hence, both problems and solution approaches to support many aircraft in airspace and to control airspace congestion within safe boundaries can be used also in a local scale of UFV supported manufacturing. This research paper is focused on problems and ability to build routes within FRA and analysis of possible use of known approaches to solve similar problems of modern automated manufacturing.

Smart Products have information about their manufacturing processes, management of their quality, future application and recycling. They actively support the production processes (when they will be produced, with what parameters, with what materials they should be produced, where their quality control should be located , when, what modifications, etc.). In these conditions, quality management should meet new requirements imposed by the fourth industrial revolution.

This publication addresses the factors that support the process of developing an individual approach to customers, which is one of the main tasks of the so-called Fourth Industrial Revolution or Industry 4.0. The emphasis is on the study of the interrelationships and the interaction between these factors and their integration in a structured way, with the help of the so-called Interpretive Structural Modeling (ISM) to help integrate them into a comprehensive conceptual framework that represents producer-customer interactions under Industry 4.0 conditions and, as a result, increase the efficiency of the process of creating value according to the individual requirements and expectations of the customer.

Bulgaria is considerably lagging behind the general trends in the EU for the introduction of a digital society and it is therefore necessary to adopt specific measures and to focus efforts on overcoming the lagging behind. Creating the right conditions for the introduction of Industry 4.0 will support, on the one hand, the competitiveness of production and attracting investment in the economy and, on the other, will help to increase efficiency in optimal resource use. The aim of the study is to reveal the possibilities for digital transformation of the Bulgarian business and to give recommendations for process transformation, using adequate strategic tools. The results of the study show that investment and innovation in IT are a key factor in boosting productivity in the EU and it is expected that three quarters of the value of the digital economy will come from traditional sectors (industry), so it is crucial to support its digital transformation.

The small and medium sized enterprises (SMEs) are the foundation of the growth of most European economies. Although increasing of their competitiveness is high on the agendas of the policy makers, the business support organisations, and the entrepreneurs and managers themselves, there is still lack of relevant discussion regarding the SMEs’ development through implementation of Industry 4.0 principles. The conducted analysis has also noted a difference in the relevant literature for the definition of the I4.0 and its scope. Based on this we find it necessary to propose definition which clearly explains the objectives of I4.0 and defines its scope. Furthermore, this paper presents potential opportunities for and implemented impact of I4.0 on SMEs with insight in the developments in Bulgaria. The analysis presents the benefits from and the obstacles for implementation of Industry 4.0. Such transformation raises critical discussion for the influence over the workers’ education and skills, and the product lifecycles. This paper also examines the role of the governments as enabler of SMEs in the implementation process.

Airspace is now one of the most frequently mentioned environments when discussing technologies of autonomous or unmanned vehicles or machines. There is a number of technologies developed to support unmanned flying vehicles (UFV) and so called air drones. The actual influence of such kind of machines on transport industry is crucial. It is also obvious, that many modern military operations involve UFV with built-in AI or remote control. Nevertheless, one of important problems for any flying vehicle (aircraft or drone either) is to plan the most suitable route satisfying all necessary primary and collateral requirements: reach destination, consume minimum fuel or energy, follow the safest areas, avoid adverse circumstances etc. Among the tasks to build the effective route for the flight we find an important problem to cut a relevant area in airspace to perform route search. This research is dedicated to discuss and ground the basics of a reliable approach to solve this problem.

The strategic initiative Industry 4.0 implies integration of Cyber-Physical Systems (CPS), Internet of Things (IoT) and cloud computing, leading to what is called “smart factory”. The lack of theoretical foundation and methodologies creates barriers that may hamper the adoption, commercialization, and market success of the new CPS applications. The reference frameworks and architectures support the analysis and specification of domains, and facilitates the unification of methods used by various disciplines such as industrial engineering, control theory, communication and information technology, thus making possible their combined use. The paper presents an analysis of the benefits and use of reference frameworks and architectures in the development of CPS. Standardized meta-models of reference frameworks and architectures are presented. Particular attention is paid to the NIST reference framework and architecture of CPS, with a view to establishing a methodology for development of Cyber-Physical Production Systems.