A data model for collaborative manufacturing environments

Andrés, Beatriz; Mula, Josefa; Sanchís, Raquel

doi:10.1016/j.compind.2021.103398

Cited by 17 publications

(5 citation statements)

References 128 publications

(56 reference statements)

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“…We split them into two sub-layers based on their progression: a knowledgedriven and technology-driven sub-layer. This result is aligned with Andres et al (2021) who argue that the data integration between actors is also divided into two levels: the first one is based on raw data and the second on processed data. The knowledge-driven sub-layer represents the ability of agricultural machinery manufacturers to configure smart products to capture data with low human intervention, and to ensure security aspects (e.g., trust, ethics, and data ownership) on data collection (e.g., Al-Jaroodi et al, 2020;Barlette and Baillette, 2020).…”

Section: Conceptual Frameworksupporting

confidence: 83%

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The relationships between digitalization and ecosystem-related capabilities for service innovation in agricultural machinery manufacturers

Smania

Mendes

Filho

et al. 2022

Journal of Cleaner Production

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Section: Conceptual Frameworksupporting

confidence: 83%

“…Among the capabilities placed at level V of the ISM model (see Fig. 2), they represent primary capabilities (Andres et al, 2021). In particular, they allow raw data integration (Al-Jaroodi et al, 2020;Barlette and Baillette, 2020) as well as ensure cybersecurity to address customer concerns (Redelinghuys et al, 2020).…”

Section: Fuzzy Micmac Results Analysismentioning

confidence: 99%

The relationships between digitalization and ecosystem-related capabilities for service innovation in agricultural machinery manufacturers

Smania

Mendes

Filho

et al. 2022

Journal of Cleaner Production

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“…It was demonstrated that the uncertainty of the production output and customer demand deviation could have various impacts. Andres et al [16] assessed the problem of information exchange required for collaborative manufacturing and planning processes at supply network levels. The collaborative manufacturing environments (CMData) were validated through their application in the automotive industry.…”

Section: Introductionmentioning

confidence: 99%

A Computational Framework for Enhancing Industrial Operations and Electric Network Management: A Case Study

Pedroso,

Silva,

Campilho

et al. 2024

Technologies

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Automotive industries require constant technological development and the capacity to adapt to market needs. Hence, component suppliers must be able to adapt to persistent trend changes and technical improvements, acting in response to customers’ expectations and developing their manufacturing methods to be as flexible as possible. Concepts such as layout flexibility, management of industrial facilities, and building information modeling (BIM) are becoming ever more addressed within the automotive industry in order to envision and select the necessary information exchanges. Given this question and based on the gap in the literature regarding this subject, this work proposes a solution, developing a novel tool that allows the monitoring and assignment of newer/relocated equipment to the switchboards within a given industrial plant. The solution intends to increase the flexibility of production lines through the assessment, analysis, improvement, and reorganization of the electrical load distribution to develop projects accurately implying layout changes. The tool is validated with an automotive manufacturer. With the implementation of this open-source tool, a detailed electrical flow management system is accomplished, and it has proven successful and essential in raising levels of organizational flexibility. This has guaranteed the company’s competitiveness with effective integrated administration methods and tools, such as a much easier study upon inserting new/relocated equipment without production line breaks.

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“…In terms of heterogeneous resource integration, Ming Li et al proposed a blockchain-based digital twin resource sharing platform to achieve reuse, sharing, and protection of digital resources [10]. Beatriz Andres et al proposed a new model of CMData to identify the data needed to collaborate on replenishment, generation, and delivery plans, meeting the need for data sharing between participants [11]. In terms of the interactive need for data value, Mohammad Najjar suggested that data information can be transformed into value through hardware, while also pointing out the need to share data between suppliers [12].…”

Section: Introductionmentioning

confidence: 99%

Blockchain-Based and Value-Driven Enterprise Data Governance: A Collaborative Framework

Liang

2023

Sustainability

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The traditional mode of cooperation between enterprises still suffers from major problems, including data privacy leakage, data falsification, and inefficient collaboration in data sharing. These challenges make it difficult for enterprises to ensure that their cooperative suppliers adopt sustainable practices in standards identification and operation processes. This paper proposes a “Value–Standard–Process” collaborative framework for blockchain-based enterprise data governance that helps ensure a high degree of data security, a high reliability of collaborative tasks, and a high transparency of value transformation. First, this paper proposes a new collaborative mode for blockchain-based manufacturing in the sharing economy, including the non-linear dynamic evaluation and value balancing mechanism of data with multiple attributes, a trusted data governance mechanism for blockchain-based manufacturing, and a smart contract generation mechanism for value-driven collaboration. Second, this paper explains these three components and the implementation of the overall framework. Third, this paper verifies the applicability and achievability of the proposed framework through experiments. Establishing the value-driven multi-level blockchain-based collaboration mode facilitates the effective flow of production factors and promotes trust in the digital economy of sustainability.

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A data model for collaborative manufacturing environments

Cited by 17 publications

References 128 publications

The relationships between digitalization and ecosystem-related capabilities for service innovation in agricultural machinery manufacturers

The relationships between digitalization and ecosystem-related capabilities for service innovation in agricultural machinery manufacturers

A Computational Framework for Enhancing Industrial Operations and Electric Network Management: A Case Study

Blockchain-Based and Value-Driven Enterprise Data Governance: A Collaborative Framework

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