Manufacturing upgrading in industry 4.0 era

Chen, Yongdang; Han, Zhiyou; Cao, Kunyu; Zheng, Xianrong; Xu, Xiaoxia

doi:10.1002/sres.2717

Cited by 23 publications

(8 citation statements)

References 45 publications

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“…The integrated sensor in production enables a flexible and targeted strategy of predictive maintenance and control [ 27 ]. Sensors that are part of the IoT can proactively monitor the device and issue alerts when the device deviates from the specified parameters, we speak of so-called facility management [ 28 ]. Karabegovic [ 29 ] adds that the sensors convert physical parameters (temperature, speed, humidity) into signals that can be measured electronically.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Predictive Maintenance and Intelligent Sensors in Smart Factory: Review

Pech

Vrchota

Bednář

2021

Sensors

210

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With the arrival of new technologies in modern smart factories, automated predictive maintenance is also related to production robotisation. Intelligent sensors make it possible to obtain an ever-increasing amount of data, which must be analysed efficiently and effectively to support increasingly complex systems’ decision-making and management. The paper aims to review the current literature concerning predictive maintenance and intelligent sensors in smart factories. We focused on contemporary trends to provide an overview of future research challenges and classification. The paper used burst analysis, systematic review methodology, co-occurrence analysis of keywords, and cluster analysis. The results show the increasing number of papers related to key researched concepts. The importance of predictive maintenance is growing over time in relation to Industry 4.0 technologies. We proposed Smart and Intelligent Predictive Maintenance (SIPM) based on the full-text analysis of relevant papers. The paper’s main contribution is the summary and overview of current trends in intelligent sensors used for predictive maintenance in smart factories.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Predictive Maintenance and Intelligent Sensors in Smart Factory: Review

Pech

Vrchota

Bednář

2021

Sensors

210

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“…New technologies with high-performance computing potential enable the creation of complex AI systems (Oliveira et al, 2021). An intelligent manufacturing system is considered the key to gaining a competitive advantage (Chen et al, 2020). AI is used, for example, in the chemical (Oliveira et al, 2021), pharmaceutical (Kshirsagar et al, 2022), and food processing and handling industries (Kumar et al, 2021).…”

Section: Artificial Intelligence In the 21st Centurymentioning

confidence: 99%

The state of development of artificial intelligence in polish industry: opinions of employees

Kądzielawski

2022

International Journal of Contemporary Management

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Purpose The purpose of the article is to show how employees of industrial organizations perceive the development of artificial intelligence (AI) within them and to gather their opinions on what AI solutions are most commonly used in Polish industry. The literature review pointed to the lack of knowledge on how employees of Polish industrial companies perceive the development of AI in their respective companies and what AI solutions they already use. Design/methodology/approach Literature review and surveys were used to collect the data. The study was carried out using a survey questionnaire. The sample was taken with a specific aim in mind: first, 30 entities were selected for that purpose, while in the second stage the employees (managers and specialists) were chosen from among those. Findings In most cases, employees are not afraid of losing their jobs due to the development of AI systems in their industries. They are positive about the use of solutions that include AI elements. In the opinion of the vast majority of respondents, modern technologies, including AI, help them in their work and facilitate it. Most popular current industrial applications are: robotic process automation technologies, Cognex cameras using neural networks, machine-learning and data technologies, distributed control systems (DSCs), enterprise resource planning (ERP)) systems, and security information and event management (SIEM) systems. Practical implication-Results of this research can be useful for developing programs aimed at reducing the fear and anxiety associated with the ongoing Industrial Revolution. Originality/value The presented research results are the only ones that show the opinions of employees regarding artificial intelligence in Polish organizations.

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“…The studies conducted in the area of industry 4.0 show various benefits that are practical and theoretical (Yuksel, 2020). The increasing demand of the customers and competitiveness encourage companies to enhance their manufacturing skills and technologies (Chen et al, 2020). These technological adoption and innovative methods are important for any company to compete in the longer run.…”

Section: Industry 40 Needs and Benefitsmentioning

confidence: 99%

Perceived Impediments and Anticipated Solutions to HR (Human Resource) Towards Implementing Industry 4.0 in SMEs

Sharma

Kumar

Lai

et al. 2022

International Journal of Technology and Human Interaction

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The study aims to evaluate perceived impediments and anticipated solutions to HR while implementing Industry 4.0 initiatives in SMEs. A group of 10 decision-makers from these SMEs was tasked with assigning ratings to a variety of parameters. To create the model for 10 perceived impediments and five anticipated solutions and subsequently rank them, the TOPSIS technique is employed. According to the data analysis, job reductions, unemployment, and job uncertainty have emerged as the top three significant hurdles, while challenges to trainers, replacement of humans, and training costs have been recognized as the bottom three. Smart HR 4.0 and AI & Data Analytics are the top and lowest-ranked solutions respectively. HR in I4.0 in SMEs parameters have been graded based on their contributing attributes. However, it is also true that there are several impediments associated with the implementation of Industry 4.0. These impediments become more challenging in the context of SMEs.

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Manufacturing upgrading in industry 4.0 era

Cited by 23 publications

References 45 publications

Predictive Maintenance and Intelligent Sensors in Smart Factory: Review

Predictive Maintenance and Intelligent Sensors in Smart Factory: Review

The state of development of artificial intelligence in polish industry: opinions of employees

Perceived Impediments and Anticipated Solutions to HR (Human Resource) Towards Implementing Industry 4.0 in SMEs

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