A Guide for the Food Industry to Meet the Future Skills Requirements Emerging with Industry 4.0

Akyazi, Tugce; Goti, Aitor; Oyarbide-Zubillaga, Aitor; Alberdi, Elisabete; Bayón, Felix

doi:10.3390/foods9040492

Cited by 107 publications

(82 citation statements)

References 11 publications

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“…The fourth industrial revolution, Industry 4.0, is the other main factor that directly affects the competitiveness and future skills needs of the construction sector. The term "Industry 4.0" refers to the novel manufacturing processes that are partially or entirely automated through the technological innovations which enable the machines along the value chain to share information with each other in an autonomous way [12][13][14]. The digital transformation is the foundation of the current industrial revolution [15,16].…”

Section: Introductionmentioning

confidence: 99%

Skills Needs of the Civil Engineering Sector in the European Union Countries: Current Situation and Future Trends

et al. 2020

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The construction sector has always occupied a strategic place in the European economy. The European construction industry suffered during the 2007–2008 global financial crisis, and today the sector is undergoing a recovery process. Among all the construction subsectors, civil engineering has the highest growth rate. Currently, the sector has to face profound industrial changes emerging with digital transformations (Industry 4.0), sustainability, climate change and energy efficiency. To promote the growth of the civil engineering sector and accelerate the recovery, we need to create a highly qualified and competent workforce that can handle the challenges coming up with the technological progress and global competitiveness. The main condition to achieve this capable workforce is to define the expected evolution of skills requirements. For that purpose, our work focuses on identifying current and near-future key skills required by the civil engineering occupations. To achieve this, we developed an automated sectoral database for the current and near-future skills requirements of the selected professional profiles. It is our belief that this sectoral database is a fundamental framework that will guide the sector through the future changes. We also believe that our research can be used as a key tool for construction companies, policy-makers, academics and training centers to develop well-designed and efficient training programs for upskilling and reskilling the workforce.

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Section: Introductionmentioning

confidence: 99%

Skills Needs of the Civil Engineering Sector in the European Union Countries: Current Situation and Future Trends

et al. 2020

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“…An important challenge for nutrients research is also their integration with research on the use of medical robotics. Perhaps the development and application of AI in nutrients research requires modification of both mentality and professional competences, as is already postulated in relation to the food industry [ 81 ].…”

Section: Discussionmentioning

confidence: 99%

Artificial Intelligence in Nutrients Science Research: A Review

Sak

Suchodolska

2021

Nutrients

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Artificial intelligence (AI) as a branch of computer science, the purpose of which is to imitate thought processes, learning abilities and knowledge management, finds more and more applications in experimental and clinical medicine. In recent decades, there has been an expansion of AI applications in biomedical sciences. The possibilities of artificial intelligence in the field of medical diagnostics, risk prediction and support of therapeutic techniques are growing rapidly. The aim of the article is to analyze the current use of AI in nutrients science research. The literature review was conducted in PubMed. A total of 399 records published between 1987 and 2020 were obtained, of which, after analyzing the titles and abstracts, 261 were rejected. In the next stages, the remaining records were analyzed using the full-text versions and, finally, 55 papers were selected. These papers were divided into three areas: AI in biomedical nutrients research (20 studies), AI in clinical nutrients research (22 studies) and AI in nutritional epidemiology (13 studies). It was found that the artificial neural network (ANN) methodology was dominant in the group of research on food composition study and production of nutrients. However, machine learning (ML) algorithms were widely used in studies on the influence of nutrients on the functioning of the human body in health and disease and in studies on the gut microbiota. Deep learning (DL) algorithms prevailed in a group of research works on clinical nutrients intake. The development of dietary systems using AI technology may lead to the creation of a global network that will be able to both actively support and monitor the personalized supply of nutrients.

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“…As in the previous studies of our research team [41][42][43], the methodology developed in this work combines detailed desk research of publications, cross-sectorial European frameworks and projects with the compilations of subject matter experts' opinions about the skills needs of the machine tool sector.…”

Section: Methodsmentioning

confidence: 99%

Skills Requirements for the European Machine Tool Sector Emerging from Its Digitalization

Akyazi

Goti

Oyarbide-Zubillaga

et al. 2020

Metals

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The machine tool industry, which is the starting point of all the metal producing activities, is presently undergoing rapid and continuous changes as a result of the fourth industrial revolution Industry 4.0. Manufacturing models are profoundly transforming with emerging digitalization. Smart technologies like artificial intelligence (AI), big data, the Internet of Things (IoT), digital twin, allow the machine tool companies to optimize processes, increase efficiency and reduce waste through a new phase of automation. These technologies, as well, enable the machine tool producers to reach the aim of creating products with improved performance, extended life, high reliability that are eco-efficient. Therefore, Industry 4.0 could be perceived as an invaluable opportunity for the machine tool sector, only if the sector has a competent workforce capable of handling the implementation of new business models and technological developments. The main condition to create this highly qualified workforce is reskilling and upskilling of the current workforce. Once we define the expected evolution of skills requirements, we can clarify the skills mismatch between the workers and job profiles. Only then, we can reduce them by delivering well-developed trainings. For this purpose, this article identifies the current and foreseen skills requirements demanded by the machine tool industry workforce. To this end, we generated an integrated database for the sector with the present and prospective skills needs of the metal processing sector professionals. The presented sectoral database is a fundamental structure that will make the sector acquire targeted industrial reforms. It can also be an essential instrument for machine tool companies, policymakers, academics and education or training centers to build well-designed and effective training programs to enhance the skills of the labor force.

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A Guide for the Food Industry to Meet the Future Skills Requirements Emerging with Industry 4.0

Cited by 107 publications

References 11 publications

Skills Needs of the Civil Engineering Sector in the European Union Countries: Current Situation and Future Trends

Skills Needs of the Civil Engineering Sector in the European Union Countries: Current Situation and Future Trends

Artificial Intelligence in Nutrients Science Research: A Review

Skills Requirements for the European Machine Tool Sector Emerging from Its Digitalization

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