Business Challenges
For manufacturing businesses, particularly in industries reliant on heavy-duty machinery like power plants, steel plants, power transmission lines, and aviation, the continuous and uninterrupted operation of these assets is crucial. Any abrupt stoppage can result in significant financial losses and, more alarmingly, pose grave risks to human lives. Detecting early signs of anomalies in real time has, thus, emerged as a paramount need to avert such disruptions.
Traditionally, addressing this challenge has relied on periodic maintenance schedules and manual inspections. However, this approach has its downsides. It is often reactive, responding to problems after they have already occurred, leading to costly downtime and potential safety hazards. Additionally, adhering strictly to maintenance schedules can be wasteful when equipment may not require it.
This is where the application of AI, specifically Anomaly Detection in Data Analytics, has come to the fore as a groundbreaking solution. Leveraging advanced algorithms and data analytics techniques, manufacturing companies can now proactively identify deviations from normal equipment behavior. This proactive approach enables them to detect issues long before they escalate into full-blown failures.
The integration of Anomaly Detection into data analytics offers multiple benefits. It not only minimizes downtime but also facilitates predictive maintenance, optimizing asset performance and extending their operational lifespan. By analyzing vast amounts of data in real time, AI can pinpoint anomalies and irregularities that human operators might miss. Moreover, AI systems can continuously learn and adapt, improving their accuracy over time. This transformative force is safeguarding both economic interests and human well-being in these critical industries, ensuring that machinery operates smoothly, efficiently, and safely.
AI Solution
The implementation of the Attention-CNN-LSTM model yielded highly promising outcomes:
- Exceptional Accuracy: The model achieved a remarkable accuracy rate, nearly 99%, in detecting the three states of power transformers. This precision is vital for field engineers to make timely decisions regarding maintenance schedules.
- Proactive Maintenance: By understanding the timing of these states, field engineers can proactively schedule maintenance, reducing the risk of sudden power transformer failures.
- Operational Continuity: This proactive approach ensures uninterrupted operations, minimizes risks, and safeguards against potential financial losses and safety hazards.
In conclusion, this case study exemplifies the transformative potential of advanced AI solutions in anomaly detection for heavy-duty machinery. By leveraging AI technologies, industries can enhance operational efficiency, reduce risks, and prioritize safety, ultimately leading to more robust and resilient operations.
Expected Outcome
The implementation of the Attention-CNN-LSTM model yielded highly promising outcomes:
- Exceptional Accuracy: The model achieved a remarkable accuracy rate, nearly 99%, in detecting the three states of power transformers. This precision is vital for field engineers to make timely decisions regarding maintenance schedules.
- Proactive Maintenance: By understanding the timing of these states, field engineers can proactively schedule maintenance, reducing the risk of sudden power transformer failures.
- Operational Continuity: This proactive approach ensures uninterrupted operations, minimizes risks, and safeguards against potential financial losses and safety hazards.
In conclusion, this case study exemplifies the transformative potential of advanced AI solutions in anomaly detection for heavy-duty machinery. By leveraging AI technologies, industries can enhance operational efficiency, reduce risks, and prioritize safety, ultimately leading to more robust and resilient operations.
Our Team Members
AI TRANSFORMATION LEAD
Dr. Mikhail Krasnov
Based in Switzerland, Mikhail is an esteemed leader with a Ph.D. in Economics and recognized as a Certified Director by the London Institute of Directors. With a 30-year tenure in the IT sector, he co-founded Verysell Group in 1990 and now drives strategy and innovation across the entire organization. He staunchly believes that AI should be a catalyst for all businesses, not a threat, enhancing and transforming companies. To him, AI is a powerful tool for businesses to harness for their advantage.
Head of Applied AI Lab
Yurii Lozinskyi
Based in England, Yurii is the driving force behind Verysell Applied AI Lab. With 25 years of experience in Healthcare, Insurance, and Finance, he specializes in Business Process & Digital Transformation. Yurii excels in creating neural networks for diverse business automation, from medical diagnostics to machinery anomaly detection. Beyond tech, he’s a proficient software delivery manager and project leader. His leadership has fueled remarkable growth, achieving up to 60% CAGR by guiding 20+ Agile Teams globally.
Chief AI Scientist
Dr. Hung Dao
Based in Vietnam, Dr. Hung leads a dynamic Consulting Team, driving AI innovation across diverse sectors, from industrial visual inspection to medical image segmentation at our AAI Lab. With a PhD in Engineering from Keio University (2014), his expertise extends to groundbreaking research published in renowned conferences such as FG, BMVC, ICASSP, and ACCV, alongside multiple granted patents. With a distinguished track record at FPT, VinBrain & Nautilus AI, he’s a prominent figure in the AI landscape.
STRATEGIC ADVISOR ON AI
Dr. Alexey Minin
Prof. Dr. Alexey Minin, an esteemed expert in the digital economy and artificial intelligence implementation, boasts over 19 years in high-tech. Rising from Siemens engineer to associated partner at MHP – A Porsche Company, Germany, Alexey excels in management consulting, exponential technologies, and creating businesses based on modern tech. A Doctor of Science in AI, Honored Professor, and consultant for several boards of directors, Alexey specializes in digital transformation, AI application, and startup guidance. He co-founded startups, lectures globally, and is a sought-after speaker in digital conferences.
Business Development Manager
Muin Pirzada
Muin brings to the table an extensive background of over 13 years in the fields of Robotic Process Automation (RPA), Test Automation, and Artificial Intelligence (AI). This vast experience has not only equipped him with a profound knowledge of these cutting-edge technologies and deep passion for business growth and operational efficiency, but also with an acute understanding of their capability to revolutionize industries and streamline operations.
Marketing Manager
Ha Nguyen
Based in Hanoi, Ha spearheads marketing endeavors, leveraging over a decade of prowess in the global technology arena. She currently serves as AAI Lab’s Marketing Manager, leveraging her expertise in B2B marketing, branding, content strategies, and Agile methodologies to propel the company’s growth. Her practical know-how equips her to craft and execute effective marketing strategies for AAI Lab and other entities within the Verysell Group.
Software Development Automation Lead
Hieu Tran
Hieu, from Danang, Vietnam, heads the automation team at SmartDev. With a decade of experience in software development, he’s skilled in tech strategy and research. Known for boosting daily operations, Hieu shines in project coordination and customer happiness. Currently, he’s the top engineer at SmartDev and also leads the AAI Lab Software Development Automation.
Head of Project Management
Richard Sharp
Richard, based in Danang Vietnam, has over 40 years of IT experience. He has had many roles including Client Manager, Supplier Manager, and Service Management Program Manager. He has designed, developed and implemented advanced service management solutions for leading organizations across the technology, government, health, telecoms, oil & gas and financial services sectors.
HEAD OF AI EDUCATION
Soan Duong
Dr. Soan is a lecturer at the Computer Science Department within Le Quy Don Technical University. She is also a senior research scientist with keen interest in computer vision and medical imaging. Her research work has been published at prestigious venues, including ISBI, ICIP, ICASSP, BMVC, and CVPR. Soan plays an active role in the academic community by serving as a dedicated reviewer for esteemed publications such as: IEEE Access and NMR in Biomedicine.