The role of big data analytics in the context of modeling design and operation of manufacturing systems

Psarommatis, Foivos; Dreyfus, Paul Arthur; Kiritsis, Dimitris

doi:10.1016/b978-0-12-823657-4.00012-9

Cited by 17 publications

(3 citation statements)

References 65 publications

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“…Despite the evident benefits, implementing a DPP system is not without hurdles. Data privacy and security pose a significant challenge [37]. With sensitive consumer and product information at stake, robust cybersecurity measures must be in place to prevent unauthorized access or misuse.…”

Section: Potential Challenges and Mitigation Strategiesmentioning

confidence: 99%

Digital Product Passport: A Pathway to Circularity and Sustainability in Modern Manufacturing

Psarommatis,

May

2024

Sustainability

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The primary aim of this study is to explore and understand the potential benefits and applications of the Digital Product Passport (DPP) system within the modern manufacturing industry. To achieve this, we developed a unique methodology, model, and a template for creating a DPP, identifying the key characteristics essential for effective implementation. Our approach involved an analysis of the literature and the formulation of a unified DPP framework, tailored to enhance supply chain transparency and support sustainable manufacturing practices. The empirical findings from our research demonstrate the DPP’s impact on supply chain transparency, providing crucial product lifecycle information that bolsters decision-making and facilitates optimal resource management. Additionally, our study suggests that the DPP model, when applied to sectors such as electronics manufacturing, promises transformative results. This research underpins the pivotal role of DPPs in the future of manufacturing, highlighting their potential to catalyze a shift towards greater transparency and sustainability. Actionable guidelines are provided for manufacturers considering the adoption of this innovative system.

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Section: Potential Challenges and Mitigation Strategiesmentioning

confidence: 99%

Digital Product Passport: A Pathway to Circularity and Sustainability in Modern Manufacturing

Psarommatis,

May

2024

Sustainability

Self Cite

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“… Gray-box models Gray-box models construct the model by model mechanism and optimize the model by using data samples, which guarantees the accuracy of the model [ 5 , 14 ]. However, the gray-box model requires a certain level of expertise in both data science and domain knowledge, which can be a disadvantage for users with limited expertise in either field [ 31 ]. Gao et al first applied the Evidential Reasoning (ER) rule to synthesize the opinions of financial analysts for stock investment decisions.…”

Section: Literature Reviewmentioning

confidence: 99%

An interpretable model for stock price movement prediction based on the hierarchical belief rule base

Yin,

Zhang,

et al. 2023

Heliyon

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“…Based on the degree to which users are fulfilled with the program, the UX-aware framework defines UX criteria as quality requirements. Since prototypes and releases are usually used to evaluate UX, effective UX evaluation methods are applied early in the requirements development process [7]. The preliminary analysis is hampered by the lack of measuring measures or a benchmark dataset.…”

Section: Introductionmentioning

confidence: 99%

Software Requirements Engineering and User Experience Design Modeling of Big Data Analysis using Convolution-Bidirectional Temporal Convolutional Network

Xu Yang

2024

jes

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The study of user perception and interaction with applications is referred to as user experience, or UX. The intricacy and versatility of software products, from requirements engineering to product functionality are well recognized. UX evaluations are often depends on prototypes, but it's important to consider the semantics embedded in software requirements to ensure project success. In this manuscript, Software Requirements Engineering and User Experience Design Modeling of Big Data Analysis using Convolution-Bidirectional Temporal Convolutional Network (SRE-UEDM-BDA-CBTCN) is proposed. The input data are collected from Requirements dataset. The collected data are given to the Convolution-Bidirectional Temporal Convolutional Network (CBTCN) to Design Modeling of Big Data Analysis user experience based on the dataset. In general, CBTCN does not express any adaption of optimization techniques for determining the ideal parameters to accurate Design user experience. Hence, African Vultures Optimization Algorithm (AVOA) is proposed in this work to improve the weight parameter of CBTCN. The proposed model is implemented and the efficiency is evaluated utilizing some performance metrics like accuracy, precision, specificity, sensitivity and F1-Score. The proposed SRE-UEDM-BDA-CBTCN method provides 28.46%, 21.34 and 33.81% higher accuracy, 22.88%, 26.52% and 34.63% higher Precision and 28.46%, 21.34 and 33.81% higher specificity compared with the existing techniques like Holistic big data integrated artificial intelligent modeling to improve privacy and safety in data management of smart cities (AIM-BDI-SDM), Exploring the factors that affect user experience in mobile-health applications: A text-mining and machine-learning approach (MHA-UED-MLA) and Towards Measuring User Experience based on Software Requirements (TM-UEB-SR).

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The role of big data analytics in the context of modeling design and operation of manufacturing systems

Cited by 17 publications

References 65 publications

Digital Product Passport: A Pathway to Circularity and Sustainability in Modern Manufacturing

Digital Product Passport: A Pathway to Circularity and Sustainability in Modern Manufacturing

An interpretable model for stock price movement prediction based on the hierarchical belief rule base

Software Requirements Engineering and User Experience Design Modeling of Big Data Analysis using Convolution-Bidirectional Temporal Convolutional Network

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