Luka Celent

Dr. Luka Celent

University of Portsmouth
+1
orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
19 July 2022 in Energies
Verified
Journal Article
Open access
PDF file
MŽMarina Crnjac Žižić
Marina Crnjac Žižić
MMMarko Mladineo
Marko Mladineo
NGNikola Gjeldum
Nikola Gjeldum
LCLuka Celent
Luka Celent
The industry is a key driver of economic development. However, changes caused by introduction of modern technologies, and increasing complexity of products and production, directly affect the industrial enterprises and workers. The critics of the Industry 4.0 paradigm emphasized its orientation to new technologies and digitalization in a technocratic way. Therefore, the new industrial paradigm Industry 5.0 appeared very soon and automatically triggered a debate about the role of, and reasons for applying, the new paradigm. Industry 5.0 is complementing the existing Industry 4.0 paradigm with the orientation to the worker who has an important role in the production process, and that role has been emphasized during the COVID-19 pandemic. In this research, there is a brief discussion on main drivers and enablers for introduction of these new paradigms, then a literature-based analysis is carried out to highlight the differences between two paradigms from three important aspects—people, organization, and technology. The conclusion emphasizes the main features and concerns regarding the movement towards Industry 5.0, and the general conclusion is that there is a significant change of the main research aims from sustainability towards human-centricity. At the end, the analysis of maturity models that evaluates enterprises’ readiness to introduce features of new paradigms is given as well.

23 January 2024 in Machines
Verified
Journal Article
Open access
PDF file
MMMarko Mladineo
Marko Mladineo
LCLuka Celent
Luka Celent
VMVili Milković
Vili Milković
IVIvica Veza
Ivica Veza
It has been more than a decade since the introduction of the Industry 4.0 paradigm. Since then, many issues have been raised in the world: the COVID-19 pandemic, sustainable development goals, and recent dramatic changes in global politics. The global value chains were broken during the pandemic, and the importance of humans as the most important element of the production system was highlighted. It caused rethinking about current industrial paradigms, including the brand new paradigm of Industry 4.0. More focus has been put on human workers, sustainability, and the resilience of the value chain, so the Industry 4.0 update was presented as Industry 5.0. A specific methodology to evaluate the maturity level of the manufacturing industry with regard to Industry 4.0/5.0 is presented and tested in the Croatian manufacturing industry. The developed methodology is unique since it puts Industry 5.0 in the right context with Industry 4.0. Therefore, the Industry 4.0 index remains the main indicator; however, alignment with three Industry 5.0 aims (human-centricity, sustainability, and resilience) represents three additional indicators. The results of the current state analysis are presented as a case study with a discussion about the results and methodology itself.

21 January 2022 in Energies
Verified
Journal Article
Open access
PDF file
LCLuka Celent
Luka Celent
MMMarko Mladineo
Marko Mladineo
NGNikola Gjeldum
Nikola Gjeldum
MŽMarina Crnjac Žižić
Marina Crnjac Žižić
Sustainatableble development assumes the meeting of humanity’s everyday needs and development goals while sustaining the ability of nature to provide the resources and ecosystem on which the economy and society depend. It means that an increase of economic benefit cannot be a single optimization problem anymore, instead, the multi-criteria approach is used with the accent on ecology and social welfare. However, it is not easy to harmonize these aims with machining, which is a well known industrial pollutant. On the other hand, new industrial paradigms such as Industry 4.0/5.0, are driving toward the smart concept that collects data from the manufacturing process and optimizes it in accordance with productivity and/or ecologic aims. In this research, the smart concept is used through the development of the multi-criteria decision support system for the selection of the optimal machining process in terms of sustainability. In the case of milling process selection, it has been demonstrated that green machining, without a multi-criteria approach, will always remain an interesting research option, but not a replacement for conventional machining. However, when applying realistic ecological and social criteria, green machining becomes a first choice imperative. The multi-criteria decision-making PROMETHEE method is used for the comparison and ranking, and validation of results is made through criteria weights sensitivity analysis. The contribution of this concept is that it could also be applied to other manufacturing processes.

10 February 2023 in Machines
Verified
Journal Article
Open access
PDF file
LCLuka Celent
Luka Celent
DBDražen Bajić
Dražen Bajić
Sonja JozićSonja Jozić
Sonja Jozić
MMMarko Mladineo
Marko Mladineo
Improving machining performance and meeting the requirements of sustainable production at the same time represents a major challenge for the metalworking industry and scientific community. One approach to satisfying the above challenge is to apply different types of cutting fluids or to optimise their usage during the machining process. The fact that cutting fluids are well known as significant environmental pollutants in the metalworking industry has encouraged researchers to discover new environmentally friendly ways of cooling and lubricating in the machining process. Therefore, the main goal is to investigate the influence of different machining conditions on the efficiency of hard machining and find a sustainable solution towards smart manufacturing. In the experimental part of the work, the influence of various machining parameters and conditions on the efficiency of the process was investigated and measured through the surface roughness, tool wear and cutting force components. Statistical data processing was carried out, and predictive mathematical models were developed. An important achievement is the knowledge of the efficiency of compressed cold air cooling for hard milling with the resulting lowest average flank wear of 0.05 mm, average surface roughness of 0.28 µm, which corresponds to grinding procedure roughness classes of N4 and N5, and average tool durability increase of 26% compared to dry cutting and conventional use of cutting fluids. Becoming a smart machining system was assured via technological improvement achieved through the reliable prediction of tool wear obtained by radial basis neural networks modelling, with a relative prediction error of 3.97%.