Real-Time Event-Driven Learning in Highly Volatile Systems: A Case for Embedded Machine Learning for SCADA Systems

Goncalves, Manuel; Sousa, Pedro; Mendes, Jérôme; Danishvar, Morad; Mousavi, Amir

doi:10.1109/access.2022.3173376

Cited by 10 publications

(3 citation statements)

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“…See: https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publicationpolicies/ intervals. This step involves monitoring the system, tracking events, and clustering them into discrete units of information, or process genes which can be named parameter identification and discretization [8]- [9].…”

Section: Industrial Genomicsmentioning

confidence: 99%

Industrial Genomics: A Novel Approach to System Behaviour Discovery

Danishvar,

Mousavi

2023

2023 11th International Conference on Control, Mechatronics and Automation (ICCMA)

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This paper explores a deeper discovery of the concept of industrial genomics which proposes a technique for registering and relating events causing an observable and definable system state and its transfer to another observable state. These industrial genomes are information quanta captured through the digital process to align and represent a chain of activities or processes. They outline the cause-andeffect relationships between events, forming patterns or pathways that ultimately lead to specific outcomes, such as the presence of defects in a product or a machine breakdown. Constructing industrial genomics necessitates understanding the observed or latent parameters of the system's state and how it changes over discrete time intervals.The concept of the proposed industrial genomes, when applied to manufacturing processes, provides a systematic and holistic approach to process optimization, predictive maintenance, and quality control. It has the potential to transform traditional manufacturing processes into smart, efficient, and reliable systems. It could be categorised as a unique method for machine learning.

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Section: Industrial Genomicsmentioning

confidence: 99%

Industrial Genomics: A Novel Approach to System Behaviour Discovery

Danishvar,

Mousavi

2023

2023 11th International Conference on Control, Mechatronics and Automation (ICCMA)

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“…Untuk meningkatkan efisiensi dan menurunkan biaya produksi yang ada di dalam industri, banyak industri yang beralih ke sistem SCADA [10][11][12][13][14][15]. Namun masih jarang industri yang menerapkan metode kontrol PID dengan sistem SCADA pada sistem conveyor yang ada.…”

Section: Pendahuluanunclassified

Implementasi sistem SCADA dengan metode kontrol PID pada motor DC penggerak conveyor belt

Khairuddin¹,

Amalia

Budi³

et al. 2022

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Sistem SCADA (Supervisory Control and Data Acquisition) merupakan teknologi komputer yang banyak digunakan pada sistem kendali di dunia industri saat ini. Pada penelitian ini sistem SCADA digunakan pada plant motor penggerak konveyor karena plant tersebut sangat banyak digunakan di industri, hampir semua jenis industri menggunakan konveyor untuk memindahkan barang dari satu tempat ketempat lainnya. Implementasi kontrol yang digunakan pada penelitian ini adalah metode kontrol PID (Proportional Integral Derivative) yang akan mengoreksi error secara otomatis dari pengukuran variabel input sensor kecepatan dengan menggunakan rotary encoder sehingga kecepatan putaran motor DC bisa sesuai dengan nilai setpoint yang ditentukan melalui sistem SCADA. Kontroler utama pada sistem ini adalah PLC (Programmable Logic Controller) Siemens S7-1200 yang berperan sebagai RTU (Remote Terminal Unit) pada sistem SCADA. Nilai parameter PID yang ditentukan pada sistem SCADA adalah Kp = 0,25, Ti = 0,8 dan Td= 0,08. Berdasarkan hasil pengujian, sistem SCADA bisa mengendalikan plant dengan baik dengan nilai error steady state sebesar 1,1% - 3,4% baik saat conveyor belt bekerja dengan beban maupun tanpa beban. Dengan sistem SCADA, monitoring sistem bisa dilakukan dari jarak jauh tanpa harus datang langsung ke lokasi tempat plant berada sehingga lebih memudahkan proses monitoring dan kontrol plant di dunia industri. ABSTRACT The SCADA (Supervisory Control and Data Acquisition) system is a computer technology that is widely used in control systems in today's industrial world. In this study, the SCADA system was used in a motor conveyor driving because the plant is very widely used in industry, almost all types of industry use conveyors to move goods from one place to another. The control implementation used in this study is the PID (Proportional Integral Derivative) control method which will correct errors of the speed sensor input variable using a rotary encoder so that the DC motor rotation speed match the setpoint value determined through the SCADA system. The main controller in this system is the Siemens S7-1200 PLC (Programmable Logic Controller) which acts as the RTU (Remote Terminal Unit) on the SCADA system. The PID parameter values determined in the SCADA system are Kp = 0.25, Ti = 0.8 and Td = 0.08. Based on the test results, the SCADA system can control the plant well with a steady state error value of 1.1% - 3.4% both when the conveyor belt is working with or without load. With the SCADA system, monitoring the system can be done remotely without having to come directly to the location where the plant is located, making it easier for the process of monitoring and controlling plants in the industrial world.

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“…Secured deployment [54]; • Event tracking in supervisory control and data acquisition system [55]; • Fuzzy-logic-based flame image processing for rotary kiln temperature control [56]; • IoT-regulated moisture sensor [57]; • Real-time carbon dioxide monitoring based on IoT cloud technologies-MQ135 carbon dioxide sensor, ESP8266 Wi-Fi module, Firebase cloud storage service, and Android application [58].…”

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confidence: 99%

Continuous Assessment of the Environmental Impact and Economic Viability of Decarbonization Improvements in Cement Production

Oguntola,

Simske

2023

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Growing awareness of the importance of mitigating climate change is driving research efforts toward developing economically viable technologies for reducing greenhouse gas emissions. The high energy consumption and carbon-intensive nature of cement manufacturing make it worthwhile to examine the environmental and economic characteristics of process improvements in cement production. This study examines the environmental impact of cement production and its economic considerations and demonstrates an IoT-inspired deployment framework for continuously assessing these. It contributes a practical approach to integrating sustainability into cement manufacturing and analyzes four different scenarios from a combination of two cement types (ordinary Portland cement, Portland-limestone cement) and two energy sources for thermal heating (coal, dried biosolids). It indicates that increased production and adoption of blended cement that has up to 15% limestone as an alternative to ordinary Portland cement can significantly reduce climate change effects from cement production (6.4% lower carbon footprint). In addition, significant emission reduction is possible with the use of waste from sewage sludge as a combustion fuel for heating in the cement production process (7.9% reduction compared with baseline). The information on environmental and financial trade-offs helps informed decisions on cement production improvements and can potentially contribute to greenhouse gas reduction targets.

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Real-Time Event-Driven Learning in Highly Volatile Systems: A Case for Embedded Machine Learning for SCADA Systems

Cited by 10 publications

References 32 publications

Industrial Genomics: A Novel Approach to System Behaviour Discovery

Industrial Genomics: A Novel Approach to System Behaviour Discovery

Implementasi sistem SCADA dengan metode kontrol PID pada motor DC penggerak conveyor belt

Continuous Assessment of the Environmental Impact and Economic Viability of Decarbonization Improvements in Cement Production

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