Implementing Intelligent Asset Management Systems (IAMS) within an Industry 4.0 Manufacturing Environment

Candón, Eduardo; Martínez-Galán, Pablo; Fuente, Antonio de la; González-Prida, Vicente; Márquez, Adolfo Crespo; Gómez, J.F.; Sola, Antônio Vanderley Herrero; Macchi, Marco

doi:10.1016/j.ifacol.2019.11.580

Cited by 18 publications

(9 citation statements)

References 3 publications

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“…These layers are considered being orthogonal to those of IT ecosystems, which apply here too [17]: i) operational: governing shop-floor activities, reporting of key performance indicators; ii) tactical: transformation of long-term objectives to medium/short-term decisions; and iii) strategic level: governing an organization's asset portfolio to support capital investment decisions. By this, asset and configuration management leverages the ability to generate and manage knowledge [5], as well as to achieve the balance between performance, costs and risks in a company's business objectives [13].Furthermore, it enables self-X features, which keeps complex CPPS controllable by being self-configurable, self-optimizing, self-healing, self-explanatory and self-protecting [15].…”

Section: Management Viewmentioning

confidence: 99%

Reference Network and Localization Architecture for Smart Manufacturing based on 5G

Ludwig¹,

Aschenbrenner²,

Scharle³

et al. 2022

Preprint

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5G promises to shift Industry 4.0 to the next level by allowing flexible production. However, many communication standards are used throughout a production site, which will stay so in the foreseeable future. Furthermore, localization of assets will be equally valuable in order to get to a higher level of automation. This paper proposes a reference architecture for a convergent localization and communication network for smart manufacturing that combines 5G with other existing technologies and focuses on high-mix low-volume application, in particular at small and medium-sized enterprises. The architecture is derived from a set of functional requirements, and we describe different views on this architecture to show how the requirements can be fulfilled. It connects private and public mobile networks with local networking technologies to achieve a flexible setup addressing many industrial use cases.

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Section: Management Viewmentioning

confidence: 99%

Reference Network and Localization Architecture for Smart Manufacturing based on 5G

Ludwig¹,

Aschenbrenner²,

Scharle³

et al. 2022

Preprint

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“…In the domain of planningwhich refers to the identification of tasks, tools and resources necessary for interventions (what and how) -ABC analysis and analytic hierarchy process (AHP) (Gopalakrishnan et al, 2015), failure mode effect and criticality analysis (FMECA) Literature review methodology (Cand on et al, 2019), genetic algorithms (Upasani et al, 2017), general optimization algorithms (Chang et al, 2019), a combination of methods like k-means and NSGA-II (Chang et al, 2019) or other supporting tools such as those discussed by Mourtzis et al (2020) are proposed. Two main approaches can be identified: one more oriented to define criticalities (e.g.…”

Section: Literature Reviewmentioning

confidence: 99%

Data-based decision-making in maintenance service delivery: the D3M framework

Sala

Bertoni

Pirola

et al. 2021

JMTM

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PurposeThis paper aims to present a dual-perspective framework for maintenance service delivery that should be used by manufacturing companies to structure and manage their maintenance service delivery process, using aggregated historical and real-time data to improve operational decision-making. The framework, built for continuous improvement, allows the exploitation of maintenance data to improve the knowledge of service processes and machines.Design/methodology/approachThe Dual-perspective, data-based decision-making process for maintenance delivery (D3M) framework development and test followed a qualitative approach based on literature reviews and semi-structured interviews. The pool of companies interviewed was expanded from the development to the test stage to increase its applicability and present additional perspectives.FindingsThe interviews confirmed that manufacturing companies are interested in exploiting the data generated in the use phase to improve operational decision-making in maintenance service delivery. Feedback to improve the framework methods and tools was collected, as well as suggestions for the introduction of new ones according to the companies' necessities.Originality/valueThe paper presents a novel framework addressing the data-based decision-making process for maintenance service delivery. The D3M framework can be used by manufacturing companies to structure their maintenance service delivery process and improve their knowledge of machines and service processes.

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“…Through analysis of retrospective and current data and the use of special prognostic tools, it is now possible to predict the failure of machines or their parts and thus optimize the costs of maintenance and repair in the future. As a result, risk-and efficiency-based asset management strategies are becoming more widely spread [9], [10]. Such strategies are particularly relevant in relation to critical infrastructure, emergency situations, such as unexpected asset failure may lead to huge financial and reputation losses and in some cases have even more disastrous consequences of the technogenic, social and economic nature.…”

Section: Emerging Opportunities In Assetmentioning

confidence: 99%

Asset Management Tools in the Digital Environment

Gitelman

Gavrilova

Kozhevnikov

2021

WIT Transactions on the Built Environment

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The paper summarizes the changing approaches to asset management of manufacturing companies amid the unprecedented uncertainty in markets, progressing digital transformation and production facilities being enriched with intelligent information and communication systems. A conceptual model has been designed that reflects the new principles and the key conditions of asset management systems' operation in the digital industry. Having examined the cases of the energy sector and high-tech industries, the authors identify the main trends in the innovative development of production asset management: cutting-edge reliability-focused repair and maintenance methods, the digital twin technology, and platform solutions for business customization. The results of the study could be used for asset management strategy development in manufacturing and for improvement of the relevant legal and regulatory frameworks, including the international standards PAS 55 and ISO 55000.

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Implementing Intelligent Asset Management Systems (IAMS) within an Industry 4.0 Manufacturing Environment

Cited by 18 publications

References 3 publications

Reference Network and Localization Architecture for Smart Manufacturing based on 5G

Reference Network and Localization Architecture for Smart Manufacturing based on 5G

Data-based decision-making in maintenance service delivery: the D3M framework

Asset Management Tools in the Digital Environment

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