SYNCHRONOUS ETHNOGRAPHY OF ECCLESIASTICAL-FOLK HERITAGE, CIRCUIT ORAL LYRIC SONGS, TRADITIONS AND ANCIENT GAMES IN DOL, HVAR ISLAND

Dol svete Marije na otoku Hvaru maleno je, ali životno mjesto bogato crkveno-pučkom baštinom. Tradicija toga mjesta uvjetovana je crkvenom liturgijskom godinom pa se gotovo svi običaji povezuju sa kršćanskim blagdanima. Posebno se ističe procesija Za Križen na otoku Hvaru koja je uvrštena u popis svjetske nematerijalne baštine UNESCO-a. Većinu običaja prakticiraju svi mještani zajedno pa se može reći da oni imaju veliku ulogu u ujedinjavanju Doljana unutar njihova identiteta. Tako se prenose legende o kraljici Teuti, koledarske pjesme i starinske igre te razne pobožnosti koje su u Doljane utkale zajedništvo i ponos male sredine koja baštinom odolijeva ravnodušnosti novog vremena.Saint Mary Dol on the island of Hvar is a small but lively village rich in church and folk heritage. The tradition of this place is conditioned by the church liturgical year, so almost all customs are associated with Christian holidays. The Za Križen procession on the island of Hvar, which is included in the UNESCO World Intangible Heritage List, is particularly noteworthy. Most of the customs are practiced by all the locals together, so it can be said that they have a great role in uniting the Doljans within their identity. This is how the legends about Queen Teuta, calendar songs and old-fashioned games are transmitted, as well as various devotions that have woven into people of Dol the unity and pride of a small community that resists the indifference of the new time

Current State Analysis of Croatian Manufacturing Industry with Regard to Industry 4.0/5.0

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

Hard Milling Process Based on Compressed Cold Air-Cooling Using Vortex Tube for Sustainable and Smart Manufacturing

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%

Hard Milling Process Based on Compressed Cold Air-Cooling Using Vortex Tube for Sustainable and Smart Manufacturing

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%

Multi-Criteria Decision Support System for Smart and Sustainable Machining Process

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