S M A K Azad | Industrail communicaiton protocols | Best Paper Award

Dr S M A K Azad | Industrail communicaiton protocols | Best Paper Award 

Professor, SV College of Engineering, India

Dr. S.M.A.K. Azad is a prominent researcher in Instrumentation and Control Engineering at the National Institute of Technology, Tiruchirappalli, India. With a robust focus on Industrial Automation, IoT, and communication protocols, he is dedicated to advancing information integration in industrial settings. His career includes significant roles, including R&D Engineer at ABB GISL and Assistant Manager at Yokogawa India Limited. Dr. Azad has over a decade of teaching experience complemented by four years in the industry, collaborating with leaders like ABB and Yokogawa. His contributions have shaped automation projects in organizations like ONGC and NTPC, and he has been instrumental in establishing a center of excellence in “Industrial Automation and Control.” A mentor to students, he has guided many to achieve success in national competitions, showcasing his commitment to education and industry collaboration.

Profile

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Strengths for the Award

Dr. S.M.A.K. Azad stands out as a leading researcher in Instrumentation and Control Engineering, particularly in the fields of Industrial IoT, communication protocols, and automation. With a Ph.D. from the National Institute of Technology, Tiruchirappalli, his academic credentials are complemented by over a decade of teaching experience and substantial industry exposure. His publications in reputed journals and conferences highlight his innovative approaches to integrating diverse data types and securing IoT landscapes. Moreover, his successful mentorship of students in national competitions demonstrates his commitment to fostering new talent in engineering and technology. Dr. Azad’s collaborative efforts with industry leaders, alongside his ability to establish a center of excellence in Industrial Automation, further underline his significant contributions to the field.

Areas for Improvements

While Dr. Azad’s research is commendable, there is room for further engagement in interdisciplinary collaborations that can enhance the applicability of his work. Expanding his research scope to include emerging technologies such as machine learning and AI in industrial automation could provide valuable insights and broaden his impact. Additionally, increasing the visibility of his work through active participation in international conferences and workshops could strengthen his global presence and foster new partnerships.

Education 

Dr. Azad completed his Ph.D. in Instrumentation and Control Engineering at the National Institute of Technology Tiruchirappalli in 2021. His foundational education includes a Master’s degree in Electronics and Communication from the National Institute of Science and Technology, Berhampur, completed in 2008, and a Bachelor’s degree in Electrical and Electronics Engineering from Kandula Sreenivasa Reddy Memorial College of Engineering in 2003. His academic journey reflects a strong emphasis on integrating theoretical knowledge with practical applications, preparing him for a successful career in both academia and industry. Dr. Azad’s educational background has equipped him with the necessary skills to innovate in industrial automation and control systems, making him a valuable asset in his field. He continues to engage with students and colleagues, promoting an environment of learning and advancement in technology.

Experience 

Dr. Azad currently serves as a Senior Assistant Professor at VIT-AP Campus, Amaravati, where he has been since June 2019. Previously, he held the position of Associate Professor in Electrical and Electronics Engineering at the National Institute of Science and Technology in Berhampur from 2014 to 2019. His industry experience spans over four years, including roles as R&D Engineer at ABB India and Assistant Manager at Yokogawa Electric, focusing on customer service and process automation. He has played a pivotal role in numerous projects across sectors, contributing to organizations like SABIC in Saudi Arabia and ONGC in India. Dr. Azad is actively involved in various administrative roles and project coordination, emphasizing his leadership and organizational skills. His extensive experience bridges academic research and practical applications, making him a recognized figure in the field of industrial automation.

Awards and Honors 

Dr. Azad has received several accolades for his contributions to education and research in industrial automation. His mentorship in national competitions, such as KPIT Sparkles and the SMART India Hackathon, has resulted in significant job placements for students, showcasing his commitment to developing future talent. He has also been recognized for establishing a center of excellence in “Industrial Automation and Control,” reflecting his leadership in academia. His collaboration with industry leaders, including ABB and Yokogawa, has earned him respect in both educational and professional circles. Dr. Azad’s work has been published in several esteemed journals, enhancing his reputation as a thought leader in his field. His dedication to enhancing industrial IoT and communication protocols has positioned him as a prominent figure, garnering admiration from peers and students alike.

Research Focus 

Dr. S.M.A.K. Azad’s research focuses on Industrial IoT, communication protocols, and automation systems. His work seeks to bridge the gap between traditional industrial processes and modern technological advancements, ensuring seamless information integration. He explores networked control systems, process control, and data analytics, aiming to enhance operational efficiency in industrial settings. His research contributions are significant in developing frameworks for data scheduling and anomaly detection in control systems, providing practical solutions to industry challenges. Dr. Azad actively collaborates with students and industry professionals, facilitating knowledge transfer and innovation. His emphasis on practical applications ensures that his research has a real-world impact, addressing critical issues in industrial automation. By advancing the understanding of distributed control systems and IoT applications, Dr. Azad is at the forefront of transforming how industries operate in the digital age.

Publication Top Notes

  1. A Framework for Integrating Diverse Data Types for Live Streaming in Industrial Automation 📊
  2. Securing the IoT Landscape: A Comprehensive Review of Secure Systems in the Digital Era 🔒
  3. Aqua-stream: an IoT based smart water management system for sustainable living 💧
  4. A computational scheme for data scheduling in industrial enterprise network using linear mixed model approach 🛠️
  5. Anomaly Detection in Estimation of Load and Prediction of Load in Networked Control System Using Correlation and Regression Data Analysis 📉
  6. Bandwidth assessment of scheduled and unscheduled communication in hybrid networked control system 🌐
  7. Analysis of time delays in scheduled and unscheduled communication used in process automation ⏳
  8. Markov Chain Modelling of Standby Redundant Networked Control System 📈
  9. Delay analysis of ControlNet and devicenet in distributed control system 🖥️
  10. Fuzzy Based Controller for Lidar Sensor of an Autonomous Vehicle 🚗
  11. Implementation of open communication protocol through wireless medium for process automation 📡

Conclusion

Dr. S.M.A.K. Azad is a well-rounded candidate for the Best Researcher Award, demonstrating exceptional expertise and a commitment to advancing the field of Industrial Automation. His research initiatives and dedication to mentorship have made significant contributions to both academia and industry. By addressing the identified areas for improvement, he can further enhance his impact and continue to be a pivotal figure in shaping the future of industrial technology. His passion for innovation and education positions him as an exemplary candidate for this prestigious recognition.

Zisheng Wang – Industrial Big Data – Best Researcher Award

Zisheng Wang - Industrial Big Data - Best Researcher Award

Tsinghua University - China

AUTHOR PROFILE

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CURRENT ROLE AT TSINGHUA UNIVERSITY 🎓

As of December 2023, Zisheng Wang has been contributing to the field of industrial engineering as a Research Assistant at Tsinghua University in Beijing. His role focuses on advancing research in intelligent maintenance systems, particularly for high-end CNC machine tools, furthering his impact in the academic and industrial sectors.

DOCTORATE FROM HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY 🎓

Zisheng earned his Doctorate in Engineering from the School of Mechanical Science and Engineering at Huazhong University of Science and Technology in Wuhan. From September 2018 to September 2023, he conducted groundbreaking research that laid the foundation for his current work in digital twin systems and fault diagnosis methods.

BACHELOR'S DEGREE FROM NORTHEASTERN UNIVERSITY 🎓

Before his doctoral studies, Zisheng completed his Bachelor's degree in Engineering at the School of Mechanical Engineering and Automation at Northeastern University in Shenyang. His undergraduate education, from October 2014 to June 2018, provided a solid grounding in mechanical engineering principles and automation technologies, which he continues to build upon in his research career.

INNOVATIVE FAULT DIAGNOSIS METHODS FOR CNC MACHINES 🛠️

Zisheng's research is distinguished by the development of a variety of CNC machine tool fault diagnosis methods. These methods address the challenges posed by multi-source sensors, compound faults, and semi-supervised conditions, systematically enhancing state monitoring and maintenance practices. His work aims to revolutionize the maintenance strategies for high-end CNC machine tools, ensuring higher efficiency and reliability in industrial applications.

LEADERSHIP IN CROSS-DOMAIN FAULT IDENTIFICATION 🔍

A key aspect of Zisheng's research is cross-domain fault identification, which is crucial for maintaining the performance and longevity of complex equipment. His methods integrate deep reinforcement learning and time-frequency transformation to effectively identify and address faults across different operational domains, showcasing his expertise in advanced diagnostic technologies.

COMMITMENT TO ADVANCING INDUSTRIAL ENGINEERING 🏭

Through his current role at Tsinghua University and his extensive academic background, Zisheng Wang continues to push the boundaries of industrial engineering. His dedication to developing intelligent maintenance systems for high-end CNC machine tools highlights his commitment to innovation and excellence in the field.

A VISIONARY IN MACHINE TOOL MAINTENANCE 🌟

Zisheng Wang's work exemplifies the fusion of advanced theoretical frameworks with practical engineering applications. His contributions to digital twin systems and intelligent maintenance strategies are paving the way for more resilient and efficient industrial machinery, positioning him as a visionary in the realm of machine tool maintenance and industrial engineering.

NOTABLE PUBLICATION

Multi-source information fusion deep self-attention reinforcement learning framework for multi-label compound fault recognition 2023 (14)

An autonomous recognition framework based on reinforced adversarial open set algorithm for compound fault of mechanical equipment 2024

Measuring compound defect of bearing by wavelet gradient integrated spiking neural network 2023 (1)

Alternative multi-label imitation learning framework monitoring tool wear and bearing fault under different working conditions 2022 (12)

Multi-label fault recognition framework using deep reinforcement learning and curriculum learning mechanism 2022 (11)