High level control of chemical plant by industry 4.0 solutions

Bellini, Pierfrancesco; Cenni, Daniele; Mitolo, Nicola; Nesi, Paolo; Pantaleo, Gianni; Soderi, Mirco

doi:10.1016/j.jii.2021.100276

Cited by 21 publications

(8 citation statements)

References 6 publications

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“…The scope of I4.0 is quite broad, and the extent to which it occurs might be resultant from the combined effects of different components, such as the organisation's information systems infrastructure (Ashrafi and Mueller, 2015; Gorkhali, 2022), organisational environment (Mithas et al ., 2013) and government policies (Erro-Garcés and Aranaz-Núñez, 2020). Despite the digital frenzy promoted by the envisioned benefits of digitalisation, many companies still struggle to grasp its concepts, which may be associated with the existing low I4.0 maturity in most industry sectors (Sony and Naik, 2019; Bellini et al ., 2022).…”

Section: Background and Hypothesesmentioning

confidence: 99%

Role of leadership in the digitalisation of manufacturing organisations

Tortorella

Prashar²,

Antony³

et al. 2023

JMTM

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PurposeThis study examines the moderating role of leadership behaviours on the relationship between Industry 4.0 (I4.0) maturity and operational performance in manufacturers.Design/methodology/approachFor that, 189 leaders from manufacturing organisations located in India and Brazil that are undergoing I4.0 implementation were surveyed. The collected data was analysed using multivariate data techniques, which allowed to verify the validity of our research hypotheses. This study was grounded on the concepts from the socio-technical systems (STS) theory.FindingsThe findings indicated that task-oriented leadership behaviours positively moderate the relationship between technologies for digitalisation and operational performance. A similar effect was found for the interaction between change-oriented leadership behaviours and strategy for digitalisation. In turn, the moderating effects of relations-oriented and change-oriented leadership behaviours were negative when considering the I4.0 maturity dimensions of employee and culture for digitalisation and technology for digitalisation, respectively.Originality/valueThis study offers arguments to better understand the role of leaders' behaviours in the digitalisation of organisations. Changing behaviours is usually a long-term and time-consuming activity. The identification of the leadership behaviours that are more likely to support digitalisation allows companies to anticipate potential issues and prioritise efforts to assertively develop leaders.

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Section: Background and Hypothesesmentioning

confidence: 99%

Role of leadership in the digitalisation of manufacturing organisations

Tortorella

Prashar²,

Antony³

et al. 2023

JMTM

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“…Every Dense layer in our neural networks apart from the output one, is activated through the ReLu activation function (3), where x denotes the value inputted to the neuron:…”

Section: B Deep Neural Network and Attack Responsementioning

confidence: 99%

“…Industrial Control Systems (ICS)/Supervisory Control And Data Acquisition (SCADA) systems' utility and benefit in the industrial domain is undoubtful [1] [2] [3]. Such solutions boost automation in contemporary, Internet of Things (IoT)-enabled industrial processes, by supervising, monitoring, and controlling the manufacturing procedures [4] [5].…”

Section: Introductionmentioning

confidence: 99%

Attacking and Defending DNP3 ICS/SCADA Systems

Kelli

Radoglou-Grammatikis

Sesis³

et al. 2022

2022 18th International Conference on Distributed Computing in Sensor Systems (DCOSS)

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The highly beneficial contribution of intelligent systems in the industrial domain is undeniable. Automation, supervision, remote control, and fault reduction are some of the various advantages new technologies offer. A protocol demonstrating high utility in industrial settings, and specifically, in smart grids, is Distributed Network Protocol 3 (DNP3), a multi-tier, application layer protocol. Notably, multiple industrial protocols are not as securely designed as expected, considering the highly critical operations occurring in their application domain. In this paper, we explore the internal vulnerabilities-by-design of DNP3, and proceed with the implementation of the attacks discovered, demonstrated through 8 DNP3 attack scenarios. Finally, we design and demonstrate a Deep Neural Network (DNN)-based, multi-model Intrusion Detection Systems (IDS), trained with our experimental network flow cyberattack dataset, and compare our solution with multiple machine learning algorithms used for classification. Our solution demonstrates a high efficiency in the classification of DNP3 cyberattacks, showing an accuracy of 99.0%.

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“…Also in the manufacturing sector, sensors and Internet-of-Things (IoT) data were also integrated into dashboards to monitor the productive process [12]. Concerning the specific chemical industry, we have found one one dashboard example that was proposed to control and monitor the production of a chemical plant [3].…”

Section: Related Workmentioning

confidence: 99%

An Industry 4.0 Intelligent Decision Support System for Analytical Laboratories

Silva

Cortez

2022

IFIP Advances in Information and Communication Technology

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This paper presents an Intelligent Decision Support System (IDSS) to enhance the management of Analytical Laboratories (AL) of a company operating in the chemical industry. This IDSS incorporates two predictive Machine Learning (ML) models, related with the prediction of the arrival of samples at the AL and the consumption of AL materials, which are then used to perform prescriptive analytics for AL instrument allocation tasks. The IDSS is also complemented with descriptive analytics of instrument similarities regarding the tests performed, for better supporting the AL manager decisions. The IDSS includes interactive dashboards and it was successfully validated by the AL managers using the Technology Acceptance Model (TAM) 3 and open interviews, which resulted in a positive feedback.

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High level control of chemical plant by industry 4.0 solutions

Cited by 21 publications

References 6 publications

Role of leadership in the digitalisation of manufacturing organisations

Role of leadership in the digitalisation of manufacturing organisations

Attacking and Defending DNP3 ICS/SCADA Systems

An Industry 4.0 Intelligent Decision Support System for Analytical Laboratories

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