IIot Platform for Agile Manufacturing in Plastic and Rubber Domain

Bosi, Ilaria; Rosso, Jure; Ferrera, Enrico; Pastrone, Claudio

doi:10.5220/0009573304360444

Cited by 5 publications

(3 citation statements)

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“…A key enabler of the Fourth Industrial Revolution is the IIoT, also known as the Industrial Internet, the Internet of Everything and Internet 4.0 [32,33]. It involves the development of a network of industrial devices [34,35], including sensors, complex industrial robots and actuators. These devices are connected through communication technologies, allowing for the monitoring, analysis, delivery, collection, and exchange of data in a fast and efficient manner [36].…”

Section: Industry 40 and Iiotmentioning

confidence: 99%

Power-Efficient Dispatching of Time-Sensitive Requests in the Fog-Enabled Industrial Internet of Things

Huda Qasim ALGawwam

2024

jes

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Recent advancements in service offerings and the emergence of new application areas have reveal the limitations of cloud computing as a solely solution. One of these new areas is the industrial internet of things, where industrial processes are controlled in a network-based and automated way which brings many new challenges. To solve the challenges, fog computing has been introduced as a complementary paradigm to the cloud. Resource management is one of those challenges need further investigation. The industrial internet of things by its own characteristics has led traditional methods to be inefficient within this evolving ecosystem. Therefore, fully utilizing potential of the new system necessitates effective resource management. This manuscript aims to investigate the problem of resource management in the emerging cloud-fog ecosystem of the industrial internet of things. Considering the dynamic nature of users, this study proposes the algorithms for dynamic resource allocation and provisioning based on deadlines. We formulate the problem as a multiple criteria stochastic problem and introduced an online solution. Our proposed solution takes into account the unique characteristics of Fog computing and the dynamic behavior of users. To effectively handle the scheduling of requests, the research suggests utilizing the Lyapunov optimization method and Lyapunov drift theory. The Lyapunov method helps to merge and measure all the related objectives in terms drift. The objective function is optimized, in each time slot, using a drift-plus-penalty weight parameter. By adopting this approach, the system can operate efficiently while meeting the constraints and performance requirements of IoT applications.

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Section: Industry 40 and Iiotmentioning

confidence: 99%

Power-Efficient Dispatching of Time-Sensitive Requests in the Fog-Enabled Industrial Internet of Things

Huda Qasim ALGawwam

2024

jes

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“…Optimization refers to expanding systems from a connection to a network of human operators at the human-machine interface. At the same time, context illustrates the ability to interact within an existing environment and respond immediately if something changes using advanced objects [23]. On the other hand, omnipresence provides the advanced object's information, including location, physical, and atmospheric conditions.…”

Section: Internet Of Things (Iiot)mentioning

confidence: 99%

“…Therefore, on a large scale, data analytics tools and procedures fill this gap by enabling companies to analyze the high volume, high velocity, and high variety data sets and obtain new insights critical for decision-making and strategizing. According to Bosi et al [23], the gathering and complete assessment of data from several sources, including manufacturing equipment and systems and corporate and customer management systems, has become common to facilitate real-time decision-making as companies strive to increase performance and productivity in the current competitive global business environment since. This argument is supported by Daissaoui et al [27] explanation that analysis of previously recorded data is used to determine threats in different production processes earlier in the industry.…”

Section: Big Data and Analyticsmentioning

confidence: 99%

A Bibliometric Analysis of the role of Industry 4.0 Sensors in Digital Transformation

Dias¹,

Rosário²

2023

Preprint

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This study aims to determine the role of Industry 4.0 sensors in digital transformation. Using a systematic literature review with a bibliometric analysis, we examine a sample of 52 studies from the SCOPUS database to identify research activity on this topic until December 2022. We find that 2022 was the year with the highest number of peer-reviewed documents on the subject, with 18 publications. We also examine current themes and find that sensors can connect multiple systems and devices, thus enabling machine-to-machine communication and facilitating great precision during product designing, development, and production, thus enabling customization and improving quality. However, despite these benefits, the current sensor technologies face multiple challenges that undermine their maximum adoption.

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Advancing zero defect manufacturing: A state-of-the-art perspective and future research directions

Powell

Magnanini

Colledani

et al. 2022

Computers in Industry

114

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IIot Platform for Agile Manufacturing in Plastic and Rubber Domain

Cited by 5 publications

References 0 publications

Power-Efficient Dispatching of Time-Sensitive Requests in the Fog-Enabled Industrial Internet of Things

Power-Efficient Dispatching of Time-Sensitive Requests in the Fog-Enabled Industrial Internet of Things

A Bibliometric Analysis of the role of Industry 4.0 Sensors in Digital Transformation

Advancing zero defect manufacturing: A state-of-the-art perspective and future research directions

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