A MaaS platform architecture supporting data sovereignty in sustainability assessment of manufacturing systems

Landolfi, Giuseppe; Barni, Andrea; Izzo, Gabriele; Fontana, Alessandro; Bettoni, Andrea

doi:10.1016/j.promfg.2020.01.069

Cited by 12 publications

(6 citation statements)

References 14 publications

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“…The contemporary challenge of safety is the security of the stored data from sensors. In addition to the sensors that collect data, which is a physical prerequisite for the Industry 4.0 concept, the sovereignty of the data is important [ 174 ], especially from a psychological point of view. Only enterprises that trust the security of their networks are also willing to store and share their data.…”

Section: Discussionmentioning

confidence: 99%

Predictive Maintenance and Intelligent Sensors in Smart Factory: Review

Pech

Vrchota

Bednář

2021

Sensors

207

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With the arrival of new technologies in modern smart factories, automated predictive maintenance is also related to production robotisation. Intelligent sensors make it possible to obtain an ever-increasing amount of data, which must be analysed efficiently and effectively to support increasingly complex systems’ decision-making and management. The paper aims to review the current literature concerning predictive maintenance and intelligent sensors in smart factories. We focused on contemporary trends to provide an overview of future research challenges and classification. The paper used burst analysis, systematic review methodology, co-occurrence analysis of keywords, and cluster analysis. The results show the increasing number of papers related to key researched concepts. The importance of predictive maintenance is growing over time in relation to Industry 4.0 technologies. We proposed Smart and Intelligent Predictive Maintenance (SIPM) based on the full-text analysis of relevant papers. The paper’s main contribution is the summary and overview of current trends in intelligent sensors used for predictive maintenance in smart factories.

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Section: Discussionmentioning

confidence: 99%

Predictive Maintenance and Intelligent Sensors in Smart Factory: Review

Pech

Vrchota

Bednář

2021

Sensors

207

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“…Landolfi et al (2019) [26] describe a reference architecture for an MaaS platform architecture called MANUSQUARE, which has been developed in an EU project of the same name (www.manusquare.eu, accessed on 17 July 2023). MANUSQUARE enables an ecosystem and includes a virtual marketplace that connects manufacturing service providers and consumers.…”

Section: Deshmukh Et Al (2021)mentioning

confidence: 99%

Building a Digital Manufacturing as a Service Ecosystem for Catena-X

Schöppenthau,

Patzer,

Schnebel

et al. 2023

Sensors

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Manufacturing as a Service (MaaS) enables a paradigm shift in the current manufacturing landscape, from integrated production and inflexible, fragile supply chains to open production and flexible, robust supply chains. As part of this evolution, new scaling effects for production capacities and customer segments are possible. This article describes how to accomplish this paradigm shift for the automotive industry by building a digital MaaS ecosystem for the large-scale automotive innovation project Catena-X, which aims at a standardized global data exchange based on European values. A digital MaaS ecosystem can not only achieve scaling effects, but also realize new business models and overcome current and future challenges in the areas of legislation, sustainability, and standardization. This article analyzes the state-of-the-art of MaaS ecosystems and describes the development of a digital MaaS ecosystem based on an updated and advanced version of the reference architecture for smart connected factories, called the Smart Factory Web. Furthermore, this article describes a demonstrator for a federated MaaS marketplace for Catena-X which leverages the full technological potential of this digital ecosystem. In conclusion, the evaluation of the implemented digital ecosystem enables the advancement of the reference architecture Smart Factory Web, which can now be used as a blueprint for open, sustainable, and resilient digital manufacturing ecosystems.

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“…One of the first examples is the creation of the term of Software-as-a-Service [29], that applies the 'aaS' approach to software. Shortly afterwards, the Manufacturing-as-a-Service (MaaS) concept followed, an ecosystem that acts as a virtual marketplace bringing production capacity, as well as other virtual and physical assets, closer to the production demand, to aim for their optimal matching [30].…”

Section: 3mentioning

confidence: 99%

Servitization for Teaching and Research Laboratories

2022

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In this paper, we present a pattern for assessing the feasibility of laboratories and lab networks to operate in a service-oriented form of business. Our focus is on the field of engineering, and on a network of academic labs, and we aim to provide a practical tool for disclosing the opportunity of servitization, or to use Laboratories-as-a-Service (LaaS), for interested companies. By using a traditional pitch deck approach, we define the available digital online offer of the specific labs, and we structure a questionnaire to investigate the market demand. Afterwards, we sketch the main servitization characteristics required to digital online labs from a business perspective. The pattern we propose has been used as a guideline for interviews to selected stakeholders of two specific labs, namely a remotely available RFID lab for internal logistics in the retail sector, and a serious game for operations and supply chain management. The answers we collected suggested the feasibility of the labs servitization, by defining both strengths and weaknesses.

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A MaaS platform architecture supporting data sovereignty in sustainability assessment of manufacturing systems

Cited by 12 publications

References 14 publications

Predictive Maintenance and Intelligent Sensors in Smart Factory: Review

Predictive Maintenance and Intelligent Sensors in Smart Factory: Review

Building a Digital Manufacturing as a Service Ecosystem for Catena-X

Servitization for Teaching and Research Laboratories

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