Conceptual Framework for Applying Internet of Things in Production Systems for Sensing Enterprises

Boza, Andrés; Cortes, B. Conceição; Alemany, M; Cuenca, Llanos

doi:10.14488/bjopm.2016.v13.n1.a7

Cited by 3 publications

(9 citation statements)

References 29 publications

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“…Sub-indexes of IIoT include encryption, transmission time, scalability, flexibility, resource optimization and availability. These results support Chen (2020), Kumar et al (2016), Boza et al (2016) and Shrouf et al (2014), who found positive and significant effects to the IIoT on production systems' success. It is the total capacity that IIoT presents to the industries that will be deployed because, with the integration of cyber-physical manufacturing processes, intelligent computers, intelligent K 51,6 systems, and automation fully integrate with physical equipment, facilities, fleets and networks.…”

Section: Discussionsupporting

confidence: 86%

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Assessing the implementation feasibility of intelligent production systems based on cloud computing, industrial internet of things and business social networks

Sun

Yang

2021

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PurposeThe increasing demands for customized services and frequent market variations have posed challenges to managing and controlling the manufacturing processes. Despite the developments in literature in this area, less consideration has been devoted to the growth of business social networks, cloud computing, industrial Internet of things and intelligent production systems. This study recognizes the primary factors and their implications for intelligent production systems' success. In summary, the role of cloud computing, business social network and the industrial Internet of things on intelligent production systems success has been tested.Design/methodology/approachIntelligent production systems are manufacturing systems capable of integrating the abilities of humans, machines and processes to lead the desired manufacturing goals. Therefore, identifying the factors affecting the success of the implementation of these systems is necessary and vital. On the other hand, cloud computing and the industrial Internet of things have been highly investigated and employed in several domains lately. Therefore, the impact of these two factors on the success of implementing intelligent production systems is examined. The study is descriptive, original and survey-based, depending on the nature of the application, its target and the data collection method. Also, the introduced model and the information collected were analyzed using SMART PLS. Validity has been investigated through AVE and divergent validity. The reliability of the study has been checked out through Cronbach alpha and composite reliability obtained at the standard level for the variables. In addition, the hypotheses were measured by the path coefficients and R2, T-Value and GOF.FindingsThe study identified three variables and 19 sub-indicators from the literature associated that impact improved smart production systems. The results showed that the proposed model could describe 69.5% of the intelligence production systems' success variance. The results indicated that business social networks, cloud computing and the industrial Internet of things affect intelligent production systems. They can provide a novel procedure for intelligent comprehensions and connections, on-demand utilization and effective resource sharing.Research limitations/implicationsStudy limitations are as below. First, this study ignores the interrelationships among the success of cloud computing, business social networks, Internet of things and smart production systems. Future studies can consider it. Second, we only focused on three variables. Future investigations may focus on other variables subjected to the contexts. Ultimately, there are fewer experimental investigations on the impact of underlying business social networks, cloud computing and the Internet of things on intelligent production systems' success.Originality/valueThe research and analysis outcomes are considered from various perspectives on the capacity of the new elements of Industry 4.0 for the manufacturing sector. It proposes a model for the integration of these elements. Also, original and appropriate guidelines are given for intelligent production systems investigators and professionals' designers in industry domains.

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Section: Discussionsupporting

confidence: 86%

“…But, the paper suffers from a limited sample size. Boza et al (2016) offered a conceptual framework within the sensing sector about IoT in the production environment. A literature review was done to establish this structure.…”

Section: Related Workmentioning

confidence: 99%

Assessing the implementation feasibility of intelligent production systems based on cloud computing, industrial internet of things and business social networks

Sun

Yang

2021

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“…Nevertheless, SMEs that go through training from either public or private institutions may stand a better chance of survival and profitability than those that did not go through the said training [116,119]. Furthermore, business owners of start-up SMEs should consider training to acquire a 360-degree skillset instead of just one training element to grow their businesses [120][121][122][123].…”

Section: The Need For Supporting Institutions' Servicesmentioning

confidence: 99%

“…Consequently, aspects of standardisation form part of our framework. An animal track-and-trace enterprise supply chain IoT conceptual framework from [121] is depicted in Figure 1. The BPM in Figure 2 is divided into three categories, starting with the 3D printing sector for digital manufacturing, where tags are created and attached to cattle.…”

Section: Iot Framework For Rapid Integration Of Iot Systems In Smesmentioning

confidence: 99%

A Control Framework for a Secure Internet of Things within Small-, Medium-, and Micro-Sized Enterprises in a Developing Economy

2023

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Small and medium enterprises (SMEs) play a critical role in the economic growth of a nation, and their significance is increasingly acknowledged. More than 90% of commercial establishments, almost 70f% of jobs, and 55% of the GDP are held by SMEs in mature economies. Additionally, this sector accounts for 70% of employment possibilities and up to 40% of the GDP in developing countries. Technologically, the Internet of Things (IoT) enables multiple connected devices, i.e., “things”, to add value to businesses, as they can communicate and send messages or signals promptly. In this article, we investigate various challenges SMEs experience in IoT adoption to further their businesses. Amongst others, the challenges elicited include IoT considerations for SMEs, data, financial availability, and challenges related to the SME environment. Having analysed the challenges, a three-tiered solution framework coined the Secure IoT Control Framework (SIoTCF) to address the said challenges is developed and briefly validated through a theoretical analysis of the elements of the framework. It is hoped that the proposed framework will assist with aspects of design, governance, and maintenance in enhancing the security levels of IoT adoption and usage in SMEs, especially start-ups or less experienced SMEs. Future work in this area will involve surveying SME owners and ICT staff to validate the utility of the SIoTCF further. The study adds to the body of knowledge in general by developing a secure IoT control framework. In the field of ICT, this paradigm is expected to be useful for academics, researchers, and students.

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“…The architecture from which we start our study is based on views of (Oprea 1999), (Cretu 2006), (Dospinescu and Perca 2011), (Fotache and Cogean 2013), (Dospinescu and Perca 2013), (Pavaloaia 2013), (Greavu-Serban 2015). Considering the changes generated by the integration of the IoT into the architecture of a company, new terms have been used, such as sensing enterprises (Boza et al 2016), generic enablers (Barmpounakisa 2015), smart enterprises (Fang et al 2015), and we suggest the term connected and synchronized enterprises. These terms underline the challenges faced by enterprises through the IoT, data now attract objects and objects generate data requiring an integration and perfect synchronization of systems, objects and companies.…”

mentioning

confidence: 99%

Change of Functional Requirements For Information Systems Integration With Internet of Things

Mesnita¹

2017

JSSD

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Conceptual Framework for Applying Internet of Things in Production Systems for Sensing Enterprises

Cited by 3 publications

References 29 publications

Assessing the implementation feasibility of intelligent production systems based on cloud computing, industrial internet of things and business social networks

Assessing the implementation feasibility of intelligent production systems based on cloud computing, industrial internet of things and business social networks

A Control Framework for a Secure Internet of Things within Small-, Medium-, and Micro-Sized Enterprises in a Developing Economy

Change of Functional Requirements For Information Systems Integration With Internet of Things

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