scholarly journals Industry 4.0 based process data analytics platform: A waste-to-energy plant case study

Author(s):  
James Clovis Kabugo ◽  
Sirkka-Liisa Jämsä-Jounela ◽  
Robert Schiemann ◽  
Christian Binder
2021 ◽  
Author(s):  
Ulrich Weber ◽  
Niko Kampman ◽  
Tomas Mikoviny ◽  
Jørgen Thomassen ◽  
Anja Sundal

2016 ◽  
Vol 48 ◽  
pp. 593-603 ◽  
Author(s):  
Yunna Wu ◽  
Kaifeng Chen ◽  
Bingxin Zeng ◽  
Meng Yang ◽  
Shuai Geng

Detritus ◽  
2018 ◽  
Vol Volume 06 - June 2019 (0) ◽  
pp. 1 ◽  
Author(s):  
Giovanni Lonati ◽  
Alberto Cambiaghi ◽  
Stefano Cernuschi

2020 ◽  
Author(s):  
Avinash Wesley ◽  
Bharat Mantha ◽  
Ajay Rajeev ◽  
Aimee Taylor ◽  
Mohit Dholi ◽  
...  

2021 ◽  
Vol 11 (8) ◽  
pp. 3438
Author(s):  
Jorge Fernandes ◽  
João Reis ◽  
Nuno Melão ◽  
Leonor Teixeira ◽  
Marlene Amorim

This article addresses the evolution of Industry 4.0 (I4.0) in the automotive industry, exploring its contribution to a shift in the maintenance paradigm. To this end, we firstly present the concepts of predictive maintenance (PdM), condition-based maintenance (CBM), and their applications to increase awareness of why and how these concepts are revolutionizing the automotive industry. Then, we introduce the business process management (BPM) and business process model and notation (BPMN) methodologies, as well as their relationship with maintenance. Finally, we present the case study of the Renault Cacia, which is developing and implementing the concepts mentioned above.


2021 ◽  
Vol 11 (3) ◽  
pp. 1312
Author(s):  
Ana Pamela Castro-Martin ◽  
Horacio Ahuett-Garza ◽  
Darío Guamán-Lozada ◽  
Maria F. Márquez-Alderete ◽  
Pedro D. Urbina Coronado ◽  
...  

Industry 4.0 (I4.0) is built upon the capabilities of Internet of Things technologies that facilitate the recollection and processing of data. Originally conceived to improve the performance of manufacturing facilities, the field of application for I4.0 has expanded to reach most industrial sectors. To make the best use of the capabilities of I4.0, machine architectures and design paradigms have had to evolve. This is particularly important as the development of certain advanced manufacturing technologies has been passed from large companies to their subsidiaries and suppliers from around the world. This work discusses how design methodologies, such as those based on functional analysis, can incorporate new functions to enhance the architecture of machines. In particular, the article discusses how connectivity facilitates the development of smart manufacturing capabilities through the incorporation of I4.0 principles and resources that in turn improve the computing capacity available to machine controls and edge devices. These concepts are applied to the development of an in-line metrology station for automotive components. The impact on the design of the machine, particularly on the conception of the control, is analyzed. The resulting machine architecture allows for measurement of critical features of all parts as they are processed at the manufacturing floor, a critical operation in smart factories. Finally, this article discusses how the I4.0 infrastructure can be used to collect and process data to obtain useful information about the process.


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