Bojana Bajic

Bojana Bajic
University of Novi Sad Faculty of Technical Sciences · Department of Industrial Engineering and Engineering Management

PhD of Engineering

About

23
Publications
28,751
Reads
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364
Citations
Introduction
Bojana holds Ph.D. in Industrial Engineering and Management. She currently works as a Research Associate at the Department of Industrial Engineering and Management, at the Faculty of Technical Sciences, University of Novi Sad and at the Institute for AI Research and Development of Serbia. Bojana has more than 5 years of research and teaching experience at the university level. She does research in fields of Industry 4.0 and Smart Manufacturing, Big Data Analytics, and applied AI in industry.
Additional affiliations
April 2022 - present
The Institute for Artificial Intelligence Research and Development of Serbia
Position
  • Research Assistant

Publications

Publications (23)
Article
Full-text available
In recent years, researchers and practitioners have focused on Industry 4.0, emphasizing the role of cyber-physical systems (CPSs) in manufacturing. However, the operationalization of Industry 4.0 has presented many implementation challenges caused by the inability of available technologies to meet industry needs effectively. Furthermore, Industry...
Conference Paper
Full-text available
Kaizen, a continuous improvement methodology, serves as a fundamental element for companies to maintain their competitiveness in an increasingly demanding market. The advent of Industry 4.0, with the support of Kaizen, has been considered to answer these never-ending demands by bringing significant transformations in manufacturing processes through...
Conference Paper
Full-text available
The paper represents a systematic literature review regarding AIoT trends in the segment of Industry 4.0 referred to as Intelligent manufacturing. It is based on a secondary data analysis to identify the effects of AIoT as an emerging technology impact on the manufacturing sector with the aim to create an overview of current state in terms of both,...
Article
Full-text available
In the last decade, researchers have focused on digital technologies within Industry 4.0. 13 However, it seems Industry 4.0 hype did not fulfil industry expectations due to many implementa-14 tion challenges. Today, Industry 5.0 proposes a human-centric approach to implement digital sus-15 tainable technologies for smart quality improvement. One im...
Conference Paper
Full-text available
Industry 5.0 represents the integration of advanced technologies, such as artificial intelligence, robotics, and the Internet of Things, with human capabilities. However, this paradigm shift poses challenges in terms of the skills required by the workforce. The main aim of this paper is to examine the concept of Industry 5.0 and its implications fo...
Article
Full-text available
The ecological state of the Danube River, as the world’s most international river basin, will always be the focus of scientists in the field of ecology and environmental engineering. The concentration of orthophosphate anions in the river is one of the main indicators of the ecological state, i.e., water quality and level of eutrophication. The sed...
Conference Paper
The greatest potential for innovation in the industry is reflected in the application of advanced digital technologies.The era of advanced digital technologies has been started by the fourth industrial revolution, better known as Industry 4.0. Many industries expect Industry 4.0 to have a significant impact on their supply chains, manufacturing pro...
Chapter
The Industry 4.0 is moving the production towards smart production systems, based on new technologies (i.e. Internet of Things, Cyber-Physical Systems, Cloud Computing, Big Data and Artificial Intelligence). Companies rightfully have high expectations of Industry 4.0. However, one of the major obstacles is how to transform reactive, via proactive,...
Article
During the last decade, we have witnessed steady movement of industry and academia toward Industry 4.0. Industry 4.0 is a concept aimed at achieving the integration of physical and cybernetic parts of the manufacturing process via networks and driven by Industry 4.0 technology categories used for the prediction, control, maintenance, and integratio...
Article
Full-text available
Industry 4.0 is a concept aimed at achieving the integration of physical parts of the manufacturing process (i.e., complex machinery, various devices, and sensors) and cyber parts (i.e., advanced software) via networks and driven by Industry 4.0 technology categories used for prediction, control, maintenance, and integration of manufacturing proces...
Chapter
Full-text available
Innovations refer to the actions required to create new ideas, processes or products. The implementation of new ideas, processes or products leads to positive effective change in a company. The positive effective change in a company is accomplished through savings. Thus, company makes savings in different types of resources via innovations, contrib...
Article
Full-text available
Industry 4.0 and its innovative technologies (e.g., Internet of Things, Cyber-Physical Systems, Cloud Computing, Big Data and Artificial Intelligence) represent great promise. Still, companies experience hardship when transforming from reactive to predictive manufacturing systems. The latter, driven by data science development, use predictive model...
Conference Paper
Full-text available
Today, the rapid development of information and communication technology (ICT) leads to the generation and collection of large amounts of raw data, which represents the undiscovered source of information. The demand of the industry sectors for the constant improvement of production systems leads to the expectation that processing such data, using t...
Conference Paper
Full-text available
With the technological development of advanced technologies and the use of the Internet of Things (IoT), the number of connected devices is increasing in manufacturing processes. As devices become more and more incorporated using more processing power, the big data is generated. However, increasing the generation of big data leads to problems relat...
Conference Paper
Full-text available
Nowadays, breast cancer is the most common malignancy in women around the world. It has been proven that a large number of new cases of breast cancer are identified each year. That increases the number of operations that impair the quality of women’s lives. Reconstruction after mastectomy, called nipple-sparing mastectomy (NSM), has become standard...
Conference Paper
Full-text available
The Industry 4.0 is now underway, changing traditional manufacturing into smart manufacturing and creating new opportunities, where machines learn to understand those processes, interact with environment and intelligently adapt their behaviour. Big data and artificial intelligence (AI) make machines in industrial production smarter than before addr...
Conference Paper
Full-text available
Cartographic heritage of historical cadastral maps represent remarkable geospatial data. Historical cadastral maps are generally regarded as an essential part of the land management infrastructure (buildings, streets, canals, bridges, etc.). Today these cadastral maps are still in use in a digital raster form (scanned maps). Digitization of cadastr...
Conference Paper
Full-text available
The fourth industrial revolution, known as Industry 4.0, has tendency to push the boundaries of science and technology. This is especially true for the manufacturing industry. One of the biggest challenges facing the manufacturing industry today is how to make intelligent systems for production with “self-aware”, “self-predict and “self-maintain” a...
Conference Paper
Full-text available
Brownfield sites have negative effects on the spatial, economic, environmental and social aspects of community life. During the past decades, examples of good practice around the world showed that the revitalization of brownfields contributed to material and non-material prosperity, and the realization of a sustainable economic and social developme...

Questions

Questions (2)
Question
In scientific sense, model fitting is a measure of how well a machine learning model generalizes to similar data to that on which it was trained, where model can be described as well-fitted, overfitted or underfitted. But how to draw the line between well-fitted, overfitted or underfitted models?
Also, in an engineering approach to the problem, if well-fitted model does not provide good enough results during real-time manufacturing process, is it good solution to overfit model?
Question
Is CPS part of Industry 4.0 concept or are they synonyms for digital industrial transformation?

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