Mechanistic Modelling & Problem Solving- A new Data-Driven CAE Process

The automobile industry is constantly evolving and adapting to the fast-paced market demands. To stay ahead of the competition, OEMs are focused on reducing their product development cycle and bringing new vehicles to market in record time. With the help of cutting-edge PLM solutions, the once lengthy 36-month process has now been trimmed down to just 24 months. However, the quest for accelerating product development does not stop there, Auto OEMs are continually exploring new approaches and techniques to achieve the ultimate goal of 12-month development cycle.

This is where EinNel Technologies comes into play, offering a new-age design approach called Data-Driven CAE. The combined expertise of traditional CAE and Data Science inspired the team to leverage the large volumes of data available across the functions right from the concept stage to final production to make predictions about product performance, resulting in a more informed and optimized design process.

Data-Driven CAE prioritizes a reality-driven design rather than a simulation-driven design that takes tooling and manufacturing constraints into account from the very beginning, with the goal of reducing the vehicle design and development cycle by 50%. This eliminates the need for multiple iterations for each design release and provides the most accurate results at the early stage of the design phase by incorporating machine learning and big data solutions.

Based on this approach, we are currently developing a cloud-based platform called EinNel MDOX that connects engineers, data, and resources to effectively model and optimize vehicle designs using real-time data from simulations, physical tests, and field tests. By harnessing the full potential of the cloud, organizations no longer need to rely on high-end computing hardware and validate complex designs with less computing power, allowing engineers to work from anywhere and anytime.

We believe that EinNel MDOX has the potential to revolutionize the way vehicles are designed and pave the way to reducing the vehicle design and development cycle to 12 months.

Mechanistic Problem Solving:

The Data-Driven CAE can be further scaled and redefined as the Mechanistic Solution Approach for solving complex engineering problems by integrating numerical, analytical, and statistical methods. Our technical team has been closely working with various Auto OEMs to identify and resolve vehicle manufacturing challenges using mechanistic solutions.

The conventional method of problem-solving is often time-consuming and resource intensive as it requires extensive domain expertise and experience. In contrast, the Mechanistic Solution Approach provides a faster and more efficient method of problemsolving, delivering results that are accurate and reliable by leveraging our advanced analytics engines.

One of the primary challenges faced by the automotive industry is developing solutions that are compatible with their ecosystems. With a deep understanding of the PLM tools, CAD/CAE software, and ERP products used by the industry, EinNel Technologies is well-equipped to develop solutions that are perfectly suited to the needs of the OEMs’ existing global ecosystems. Also, we understand the importance of delivering solutions that are both effective and easy to use. That is why we have taken the extra step to package our mechanistic solutions into user-friendly applications with interactive dashboards powered by ML algorithms. The dashboards can be tailored to fit the unique requirements of every stakeholder, allowing them to effectively utilize the data and insights we offer. Whether they are looking to improve their manufacturing processes, optimize their designs, or gain a deeper understanding of their product performance, our dashboards give them the tools they need to succeed.


Our Technology Focus – 2023

Albert E George, CEO of EinNel Technologies

During our recent town hall meeting, we unveiled our tech trends for 2023. At EinNel, we regularly reassess and adjust our technology focus to ensure that we are staying up to date with the latest and most advanced technologies in the field.


EinNel Town Hall Meeting 2022


With a vision to help industries fully embrace and implement Industry 4.0 and by realizing the need to incorporate Artificial Intelligence into our solutions as it is increasingly prevalent in our daily lives, we are pivoting to the following technologies:

  1. Platform Engineering
  2. Artificial Intelligence of Things (AIoT)

Platform Engineering:

Platform engineering involves the design and development of data-driven platforms that can be used by industries to digitize their operational workflows and build a continuously growing knowledge base with the help of artificial intelligence.

EinNel drives the automotive and manufacturing industries toward streamlining their product development process through the use of platform engineering. By centralizing their distributed functions under a single platform, EinNel enables these industries to reduce the number of iterations required and improve data management. This allows for quick and easy access to data, which can greatly accelerate product development.

To promote the vision of our data-driven platforms across industries, we have devised a set of product philosophies. Some of them are listed below:

  • Immortalizing Engineering Data - Data must be preserved and continually leveraged to support future growth
  • Propel data at rest into motion - Data at rest is simply potential energy waiting to be harnessed and put into motion to drive progress and innovation
  • Make your data easy to query - Well-organized and easily accessible data is the key to unlocking its full potential and driving powerful insights
  • Live Dashboards in place of reports - Real-time, interactive dashboards provide a more dynamic and engaging way to visualize and understand data, replacing the static nature of traditional reports
  • Confluence data under one platform - Unifying an organization’s data onto a single platform enables more comprehensive and actionable decision-making

As we enter the new year, our technical team is committed to utilizing platform engineering techniques to reduce the time it takes to bring new products or services to market and continuously optimize industrial operations to better serve the customers.

EinNel AIoT Hub:

Artificial intelligence (AI) is becoming an increasingly integral part of our dailylives. From virtual assistants to self-driving cars and medical diagnosis to financial analysis, AI is transforming the way we live and work.


Recognizing the necessity of integrating Artificial Intelligence into our solutions, EinNel has decided to set up a dedicated technology hub that will bring together a team of experts, including Data Scientists, AI and ML Engineers, Domain Experts, Scientific Software Developers, Cloud Architects, and Data Engineers to build a cloud-ready AI infrastructure and unlock the business value from industrial data. By establishing this hub, we aim to stay at the forefront of technological advancements and continue to provide cutting-edge solutions to our clients.

In the first phase of establishing the EinNel AIoT Hub, our focus is to implement the following AIoT capabilities by 2023.

Integrated Data Management:

Seamlessly integrate and manage industrial data from various sources in a way that allows for easy access and predictive analysis for improved decision-making and more efficient operations.

Edge and Cloud Computing:

Building a collaborative computing platform that combines the advantages of both edge and cloud computing to create and deploy AI-powered IoT applications, sophisticated operational processes, and industry compliance standards.

Production-grade AI environment:

By enabling developers and data scientists to create, test, and deploy high-quality AI models and applications at enterprise speed and scale, organizations can adopt and utilize AI technologies to drive business value and innovation.

Industrial AI applications development:

Developing fit-for-purpose, domain-specific industrial applications by combining domain expertise and first principles-based models with artificial intelligence and analytics algorithms.

In 2023, EinNel is positioning itself to play a key role in the realization of Industry 4.0 and bringing industrial functions and technology together in a way that promotes rapid and sustainable product development by focusing on Platform Engineering and Artificial Intelligence of Things.


Current drift and need of AI in life science

Koushika, EinNext Biosciences

Life science is the broad spectrum that entangles all fundamental and applied sciences. It is the study of organisms at different levels and their applications. The umpteen challenges faced during the pandemic to outlook further accuracy with less time consumption can be sorted with the help of Artificial Intelligence (AI). The world which requires both efficacy and expeditious results await none. But we all know studies, experiments and research require enormous patience, skill, and understanding. Scientists and people have different opinions during emergent circumstances like a pandemic. AI comes in handy during such circumstances helping life science scientists to research and come out with quicker and better results. 

The par excellent development of technologies and new breakthroughs has paved the way to upskill in the field of life science. This pandemic has not only hindered the conventional way of research but has taught us an empowering technique of associating life science with AI. AI has become the access point to incalculable data for research. The more the data flows in, the more accuracy we obtain. The ideology in various life science researches includes the whole of humankind.  

  • The drug discovery process nearly takes 15 to 20 years to launch a particular drug in the market. This process involves huge investments, tedious work, and a large workforce with accuracy. If the drug fails to cross the pre-clinical or clinical trials the loss is unimaginable and the chances of finding a cure to that particular disease will become minimal. At this juncture, AI helps scientists to scan and verify large and complicated datasets more accurately. 
  • Radiology is another field where AI can play a vital role wherein various simulations can be run, analyzed, and give doctors/ clinicians a better-detailed understanding of particular malformation or disease. Virtual biopsies will become possible in the upcoming years. 
  • Antibody engineering through machine learning approaches can provide us with solutions where we can get antibodies with more affinity which will reduce the dosage of that particular antibody thus reducing the cost. 
  • Surgeries to the most inaccessible parts of our body can be done using robots very precisely. AI programs can help the robot learn and train to operate with less or no damage. 
  • AI-powered mobile applications to consult and manage hospitals records in developing or remote places will provide immediate connection to the doctors at the time of emergency.  

The above are a few fields in which AI is needed to embrace with life science which will enhance and promote life science research to another level. There are other fields like immunology, drug designing, genetics, etc in which AI can be applied for further research and development. This sudden drift and need of AI is the most promising one for humankind but it also has few restraints. A particular framework of data collection involving various ethics has to be implemented. The requirement of a well-trained or expert workforce to handle and understand both Life science and AI is necessary.  

EinNext Biosciences - the sister company of EinNel Technologies has been practicing this type of research for a few years now. Researches on antibody engineering, AI-powered drug discovery and enzyme engineering, orthopedic research especially in the knee and hip replacement, application of ML in the biomedical field for aneurysm rupture prediction, healthcare management through EinNel H+, pre-surgical knowledge through EinNel S+, and cloud management through EinNel C+ have been the current research fields at EinNext. 

This advancement in life science research after a few years will become a more predominant and highly efficient one. 


EinNel BMS Capability

Magdalene, IoT Engineer

From electric vehicles for a smoother ride home to smart phones for the favorite games, batteries play a major role in our day-to-day life. A healthy battery makes the application last much longer. The safety of the battery that powers all appliances is significantly important. The Battery tends to degrade its capacity under various conditions both electrically and chemically. Aging of batteries is an inevitable phenomenon limiting the lifetime in many applications. Battery Modelling & Management aids in analyzing the life of the battery and saving the appliances from battery failure.

EinNel Technologies is equipped with a team of Industrial experts experienced in estimating a battery’s health. Battery Diagnostics and Prognostics helps in computing a plenty of features. It is done using various Machine learning algorithms that help with the prediction. Predicting the Battery’s State of Charge (SOC) assists in knowing when to charge and how long the battery will last. Electrical parameters like current, voltage, temperature and various other factors play a vital role in determining those features. The prediction of the attributes of a battery will not only ensure cost effectiveness but also enhance its longevity. This prediction is made on the basis of several real time parameters that guarantee the battery’s better performance. With respect to the battery’s usage Remaining Useful Life (RUL), State of Function (SOF) can also be predicted.

State of Health (SOH) monitors the life of the battery under various cycles. Using this feature the degradation of the chemical and electrical properties in the battery is visible over time. The SOH diagnosis helps in calculating the Remaining Useful life of the battery.

The RUL Prediction is very vital as it indicates when the battery needs to be recharged. It also helps in determining the end of life of a battery which indicates when the capacity degrades below its threshold value. Thus, warning how long the battery’s life will last ahead of time.

Another prominent computation for the battery is the State of Function (SOF), while driving an Electric Vehicle, the smart Battery Management System (BMS) calculates beforehand if the vehicle has enough charge to reach the desired destination. This is represented by predicting SOF of the battery with the help of the real time State of Charge. With various factors unsuspectingly affecting the lifetime of the battery, battery diagnosis and prognostics assists in predicting the condition of the battery.

At EinNel, the BMS configuration is provided as a solution to managing the usage of rechargeable batteries and ensuring its safe operation in a wide range of industries. With the emergence of electric vehicles in the automobile industry, BMS has secured a vital significance for guaranteeing the durability and longevity of the EVs, therefore, EinNel offers the best-in-class BMS configurations that not only predicts the life of batteries but also facilities various diagnostic and prognostic solutions for several battery-based industrial issues.


Work-Life Balance

Deborah Joseph, Scientific Software Developer

Desperate times call for desperate measures, whether we’re working from home or the office we are glued to our digital screens, day in and day out, and even after office hours we are on alert anticipating an official call, which means our mind never gets the break it needs. We never really flip the office switch off, which not only disrupts our personal lives and relationships but also results in lowered work performance. “Early to bed early to rise, makes one healthy wealthy and wise!” This is one saying that we all grew up learning in school, when it did seem more practical in some ways. But now that we live in a world that never sleeps, we are encouraged to lose sleep for attaining what’s important instead of being advised on finding the right balance between work and life. There is no such thing as perfection, it’s our progression towards perfection that actually counts and makes a real difference. The more we enjoy the process, the more we tend to learn and develop. We work so hard to be complaisant employees but barely put in any effort to take time out for ourselves and our family. We often underestimate the magnitude of selfcare our body and mind require to be at its best. On our chase after deadlines, we tend to leave our lives bereft of real comfort and happiness. Our brain and body are hardwired to adapt to our lifestyles and that is how even an unhealthy lifestyle begins to seem normal.

This article is nothing but a gentle reminder of how we can keep our body and mind healthy despite our hectic work lives. The major pointers are to maintain a time and involvement balance without curtailing your role either as a part of your family or your organization. For starters, maintaining a healthy sleep cycle by setting your biological clock to wake up and sleep right on time is extremely helpful. The main challenges narrow down to eating healthy and being involved in some sort of regular physical activity. It is excruciating hard if not impossible to resist munching on some snacks while you’re at your desk working continuously for hours. We rely on them for immediate energy boost-ups or even stress busts without realising the long-term damage they cause to our physical and mental health. Apart from choosing to eat healthy, it seems almost impossible to take out time for anything remotely close to physical activities. However, we could adopt some smart strategies to fit in active exercises into our tight and busy schedules. Non-exercise activity thermogenesis (NEAT) is one such strategy that aids in keeping the mind and body active through many small movements that eventually add up to count as a proper exercise. This requires the effort to bring about a change in your daily habits, such as, instead of taking calls while sitting in a comfortable chair, try walking around your office room or your balcony, take the stairs instead of the elevator, volunteer to do chores at home or run errands; but most importantly get into the habit of taking short breaks and follow workout routines that could be done from the comfort of your chair.

We at EinNel always encourage our employees to not only have a flexible working style but also to prioritize one’s health and family. We also have weekly reminders to motivate our employees to maintain a healthy work-life balance and enjoy the process of growing in life.

On the other hand, maintaining a balanced work schedule is equally, if not more important. These unprecedented times have taken a toll on our efficiency to work, thereby making it even more essential to not only plan out a disciplined work agenda but also to execute it without fail. This would require self-determined decision makings; such as predicting and planning ahead for crunch times which are inevitable especially while working on time-constrained projects, creating a prioritization strategy by discretising the tasks and most importantly, stop procrastinating. Creating a private space while working from home is a must, which not only prevents easy distraction but also significantly enhances the concentration and commitment to work. It is very important to adopt a practice of mindfulness which enables one to be more creative, insightful and flexible while under pressure. Employees must develop and follow a routine that fits occurrences of ambivalent circumstances. Paramount significance needs to be given for upholding work ethics regardless of where one works from. Switching responsibility from home to work and vice-versa, while managing time can sometimes be challenging, therefore using post-its, alarms and reminders for sticking to completing the tasks as per the schedule is of utmost importance. It is essential for the employees to allocate strict and unblurred boundaries with regard to time and engagement for both work and home.

In conclusion I would like to quote Jana Kingsford, “Balance is not something you find, it’s something you create”, with the hope that we find our own ways to create the perfect balance between work and life and give our very best to both.