Mitigating Electromagnetic Noise When Using Low-Cost Devices in Industry 4.0

Herrero, Angel C.; Sanguesa, Julio A.; Martínez, Francisco J.; Garrido, Piedad; Calafate, Carlos T.

doi:10.1109/access.2021.3074588

Cited by 5 publications

(2 citation statements)

References 17 publications

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“…(4) The use of these new technologies in industrial installations with high electromagnetic noise may condition the use of BLE since it can cause temporary disturbances and data loss, system failures, and even loss of life. Electromagnetic interference (EMI) mitigation strategies can be used to prevent high-frequency coupling to sensitive signals, such as increasing the distance between the traces or adding an EMI Shield [46,47].…”

Section: Discussionmentioning

confidence: 99%

Enhanced Real-Time Maintenance Management Model—A Step toward Industry 4.0 through Lean: Conveyor Belt Operation Case Study

Mendes,

Gaspar,

Charrua-Santos

et al. 2023

Electronics

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Conveyor belts (CBs) are widely used for the continuous transport of bulk materials. CBs must be extremely reliable due to the cost associated with their failure in continuous production systems. Thus, it is highly relevant in terms of maintenance and planning to find solutions to reduce the existing stoppages from these assets. In this sense, it is essential to monitor and collect real-time data from this piece of equipment. This work presents a case study, where a model that combines the Lean Philosophy, Total Productive Maintenance (TPM), and the enabling technologies of Industry 4.0 is applied to a CB. The proposed model monitors the CB and provides data on its operation, which, using the calculation of indicators, allows a more accurate and thorough view and evaluation, contributing to improving and supporting decision making by those responsible for maintenance. The data collected by the sensor help those responsible for maintenance and production, in the readjustment of more accurate and optimized planning, programming, and execution, supporting decision making in these areas. During the field test of a two-hour monitoring period (10 a.m. to 12 p.m.), the model identified six stoppages, resulting in approximately 88.6% of operational time for the conveyor. The field test showed that this model can result in more accurate maintenance decision making than conventional approaches. This research also contributes to the advancement of electronics and industrial automation sectors by empowering companies to transform maintenance methodologies. The potential of this approach and its implications for enhanced productivity and overall performance are therefore highlighted.

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Section: Discussionmentioning

confidence: 99%

Enhanced Real-Time Maintenance Management Model—A Step toward Industry 4.0 through Lean: Conveyor Belt Operation Case Study

Mendes,

Gaspar,

Charrua-Santos

et al. 2023

Electronics

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“…Scheme of the low-cost OEE estimation system [4].During the design and development process of our low-cost system, based on the Raspberry Pi platform, we encountered significant EMI problems in the signals we gathered; this is because low-cost devices are placed alongside other electromechanical elements. We solved this problem by eliminating the wrong signals due to EMI using two filtering mechanisms that were designed to detect and eliminate all wrong signals due to EMI[5], thereby avoiding any additional equipment. Specifically, these mechanisms make it possible to eliminate noise in two types of signals from thermosealing machines: sealing signals and availability signals.…”

mentioning

confidence: 99%

MoBiSea: A Binary Search Algorithm for Product Clustering in Industry 4.0

Herrero,

Sanguesa,

Garrido

et al. 2023

Electronics

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Proprietary systems used to modernize Industry 4.0 usually involve high financial costs. Consequently, using low-cost devices with the same functionalities, capable of replacing these proprietary systems but at a lower cost, has become an incipient trend. However, these low-cost devices usually come with electromagnetic interference problems as they are encapsulated in electrical panels, sitting alongside electromechanical devices. In this article, we present Mode Binary Search, an algorithm specifically designed for use in a low-cost automated-industrial-productivity-data-collection system. Specifically, productivity data are obtained from the availability and sealing signals of the thermoplastic sealing machines in production lines belonging to the agri-food industry. Mode Binary Search was designed to cluster sealing signals, thus enabling us to identify which products have been made. Furthermore, the algorithm determines when the manufacturing of each product starts and ends, in other words, the exact moment a product change occurs and all this without the need for operator supervision or intervention. Finally, we compared our algorithm, based on binary search, with three clustering mechanisms: k-means, k-rms and x-means. Out of all the cases we analyzed, the maximum error committed by Mode Binary Search is limited to 2.69%, thereby outperforming all others.

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Application of the Overall Equipment Effectiveness to a Service Company

Facchinetti

Citterio

2022

IEEE Access

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Competitiveness has reached outstanding levels in every marketplace sector. The Overall Equipment Effectiveness (OEE ) framework has gained increasing interest in different contexts as a leading measure for improving production. The application of the OEE as a driver of improvement is an extensively covered topic in scientific literature. However, the existing research mainly focuses on case studies showing the obtained results on specific applications, typically in the manufacturing domain. This paper proposes the adaptation of the OEE framework for its application to service companies. The obtainable results and the involved possible errors in the use of the framework are addressed. We show the benefits of the proposed framework for allowing a meaningful comparison of employees performing different types of activities. Inefficiencies can be identified and classified by associating them with causes. Methods, procedures and territorial aspects are related in general to the company organization. The application of the OEE transforms the measures from targets to drivers of improvements by identifying the areas of loss in the process. The proposed framework is demonstrated on a case study consisting in a service company operating in the telecommunication's field. The evaluation has been done over a time-span of 12 months, addressing the behavior of 952 employees. The analysis allows producing results that are useful to assess the behavior of the company. In particular, we can distinguish the causes of losses either related to the employees and the ones related to the company. Different types of losses are quantified, and this information can be used to optimize the various aspects in details. The assessment of the losses enables the comparison of the performance among different areas and different employees.

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Mitigating Electromagnetic Noise When Using Low-Cost Devices in Industry 4.0

Cited by 5 publications

References 17 publications

Enhanced Real-Time Maintenance Management Model—A Step toward Industry 4.0 through Lean: Conveyor Belt Operation Case Study

Enhanced Real-Time Maintenance Management Model—A Step toward Industry 4.0 through Lean: Conveyor Belt Operation Case Study

MoBiSea: A Binary Search Algorithm for Product Clustering in Industry 4.0

Application of the Overall Equipment Effectiveness to a Service Company

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