The Role of Industry 4.0 and BPMN in the Arise of Condition-Based and Predictive Maintenance: A Case Study in the Automotive Industry

Fernandes, Jorge M.; Reis, João; Melão, Nuno; Teixeira, Leonor

doi:10.3390/app11083438

Cited by 45 publications

(11 citation statements)

References 67 publications

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“…The objective of this study is to present an implementation model of Industry 4.0. A holistic model for implementing Industry 4.0 was proposed, based on cleaner production as a fundamental tool for the development of production systems that meet the Sustainable Development Goals (SDGs) and social stakeholders considered pillars for this implementation process, helping to develop sustainable infrastructure [74][75][76][77][78][79], processes [18,80] and technologies [16][17][18][19][20]47,[74][75][76]79,84] to increase the sustainable transformation of these companies towards Industry 4.0. The model was evaluated and improved by specialists through the Delphi technique.…”

Section: Discussionmentioning

confidence: 99%

“…In the companies the process must be conducted by ( 5) top executives, supported by qualified and committed technicians, as it involves substantial changes, requiring leaders who can move forward, correct directions and maintain the necessary change actions to minimize risks, keep investments within budget and keep everyone involved in this process of change and open to innovation [19,84].…”

Section: The Proposed Modelmentioning

confidence: 99%

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Implementing Industry 4.0 through Cleaner Production and Social Stakeholders: Holistic and Sustainable Model

Sátyro

Contador

et al. 2021

Sustainability

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Although Industry 4.0 has received much attention in recent years due to the possibility of increasing companies’ productivity, the implementation process is complex. The aim of this study is to present a holistic model for implementing Industry 4.0 based on cleaner production as a fundamental tool for the development of production systems that meet the Sustainable Development 04026-002Goals (SDGs), and social stakeholders that cooperate with this implementation process, helping to develop sustainable infrastructure, processes and technologies to increase the sustainable transformation of these companies towards Industry 4.0. The method used was literature research, and the Delphi technique was used to ask specialists to contribute with their experience to evaluate and propose improvements to the model, in the form of a consensus. The model contributes to the Sustainable Development Goals 9, 12 and 15. This holistic and sustainable model is a contribution to theory and practice, helping executives, technicians, entrepreneurs and those involved with Industry 4.0 to base the implementation process in the needs and specificities of each company, avoiding the “one fits all” models, considering the peculiarities of each company and the complexity of the implementation process in a more efficient and collaborative digital production ecosystems base, seeking to reduce inequalities, through the joint effort of social stakeholders to find ways to restore and/or improve social harmony, impacted by Industry 4.0.

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Section: Discussionmentioning

confidence: 99%

Section: The Proposed Modelmentioning

confidence: 99%

Implementing Industry 4.0 through Cleaner Production and Social Stakeholders: Holistic and Sustainable Model

Sátyro

Contador

et al. 2021

Sustainability

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“…La metodología BPM se caracteriza por tratar de mejorar la eficiencia y eficacia de los procesos a través del análisis e implementación de puntos para mejorar la productividad de sus operaciones. Para obtener resultados alentadores se deben aplicar herramientas como la estandarización de procesos, el correcto análisis de la toma de decisiones, la eliminación o reducción del impacto de actividades redundantes y la gestión eficiente de los recursos (Fernandes et al, 2021) Para esta implementación de la herramienta se debe tener en cuenta la reconfiguración dinámica del negocio, ya que el compromiso de la alta dirección y de cada trabajador es vital para lograr el éxito del uso de BPM; la transición de las viejas metodologías de procesos a las nuevas es determinante y siempre se debe hacer un control constante de las mismas para buscar una mejora continua (De Masellis et al, 2019;Nahabedian et al, 2021).…”

Section: Gestión De Procesos De Negocio (Business Process Management)unclassified

Modelo de Producción en la Industria Acuícola Peruana

Quiroz-Flores¹,

Rios-Del-Castillo²,

Guia-Espinoza³

2022

RVG

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Esta investigación busca validar un modelo de producción para mejorar los procesos productivos del cultivo de trucha arco iris del sector acuícola de la región sur del Perú. El planteamiento del modelo de producción se determinó a través de la combinación de las metodologías como Lean Manufacturing y Business Process Management para facilitar el control de procesos, la gestión de los inventarios y la planificación de la producción. Estas metodologías se integraron a partir de la revisión de la literatura y el diagnóstico realizado a través de la recopilación de información primaria de los productores aledaños dentro del departamento de Junín, en el centro del Perú. Los resultados dan cuenta del éxito del modelo a través de su implementación en las piscigranjas de los acuicultores de Junín y una simulación en el software ARENA versión 14.0, de este modo se obtuvieron resultados óptimos que muestran una mejora significativa de la productividad. Los resultados obtenidos luego de la implementación y la simulación muestran un incremento del 71,87% en la productividad con respecto al estado inicial, además se logra reducir en 16.67% el tiempo del ciclo de producción. Se concluye que el modelo de producción propuesto es exitoso y compatible para mejorar los procesos de producción en el sector acuícola.

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“…If the machine is part of a production line, the entire line can suffer from the resulting downtimes, causing significant cost and production backlogs. Numerous fault diagnosis methods have been developed and applied to counteract this [ 1 , 2 , 3 , 4 ]. These diagnosis methods are based on measurements that are recorded and analyzed in conjunction with further information by experts to detect or predict a defect.…”

Section: Introductionmentioning

confidence: 99%

Transfer-Learning-Based Estimation of the Remaining Useful Life of Heterogeneous Bearing Types Using Low-Frequency Accelerometers

Schwendemann

Sikora

2023

J. Imaging

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Deep learning approaches are becoming increasingly important for the estimation of the Remaining Useful Life (RUL) of mechanical elements such as bearings. This paper proposes and evaluates a novel transfer learning-based approach for RUL estimations of different bearing types with small datasets and low sampling rates. The approach is based on an intermediate domain that abstracts features of the bearings based on their fault frequencies. The features are processed by convolutional layers. Finally, the RUL estimation is performed using a Long Short-Term Memory (LSTM) network. The transfer learning relies on a fixed-feature extraction. This novel deep learning approach successfully uses data of a low-frequency range, which is a precondition to use low-cost sensors. It is validated against the IEEE PHM 2012 Data Challenge, where it outperforms the winning approach. The results show its suitability for low-frequency sensor data and for efficient and effective transfer learning between different bearing types.

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The Role of Industry 4.0 and BPMN in the Arise of Condition-Based and Predictive Maintenance: A Case Study in the Automotive Industry

Cited by 45 publications

References 67 publications

Implementing Industry 4.0 through Cleaner Production and Social Stakeholders: Holistic and Sustainable Model

Implementing Industry 4.0 through Cleaner Production and Social Stakeholders: Holistic and Sustainable Model

Modelo de Producción en la Industria Acuícola Peruana

Transfer-Learning-Based Estimation of the Remaining Useful Life of Heterogeneous Bearing Types Using Low-Frequency Accelerometers

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