An Exclusive Interview with Basant Sharma, Vice President (VP) of Detroit Engineered Products (DEP)
Engineering services currently range from software to hardware and so much more. The process of conception to production is lengthy and that’s why most of the customers look for an all-rounder expert on this matter who can manage the whole development process. DEP is such a company that customizes the products, processes and services.
Analytics Insight has engaged in an exclusive interview with Basant Sharma, Vice President (VP) of Detroit Engineered Products (DEP).
Kindly brief us about the company, its specialization and the services that your company offers.
DEP is an engineering services, product development, software development and talent acquisition company. Since its inception in 1998 in Troy, Michigan, USA, DEP is now a global company with footprints in Europe, China, Korea, Japan and India.
Our engineering capabilities- right from concept to production- spanning across products, processes and services are customized to drastically reduce overall product development cycle for our customers, enabling them to cut costs, accelerate time to market, and deliver optimized and balanced products. We use the accelerated and transformed product development process, accomplished by utilizing our proprietary CAE platform, DEP MeshWorks, which rapidly reduces the development time of products for all segment.
What is your biggest USP that diﬀerentiates the company from competitors?
CAE has evolved in the last few years to give the customers varied options. Using DEP MeshWorks as a single user integrated platform, they can utilize the modelling process to create CAE models far faster than most other technologies on the market. They will also be able to develop and optimize new concepts. Our customers may carry out several processes, such as optimization, concept generation, and design, using a single platform. This aspect of multi-disciplinary tools provides substantial ROI, which can be calculated with the man-hours saved. Since we can provide solutions using our own custom software, we offer a high degree of flexibility and customization to the customer.
What are the key challenges faced in the self-driving car market? What are the current trends?
The biggest challenge in autonomous vehicles market is the software itself, which defines autonomous vehicles. The software’s are based on machine learning algorithms and deep learning, which are built on a huge database of images and videos of real-world conditions. This itself puts a constraint.
A challenge that will always be will be creating (and maintaining) maps and databases for self-driving cars. Another challenge is driving is a social situation, where humans rely on their intelligence and common sense, and that level of judgment is difficult to train a machine.
Lack of industry standardization is a challenge, where companies are building their own autonomous driving technology and there is no standardization on it. The legal and regulatory framework also needs to be developed around autonomous vehicles. Government bodies need to form a standard regulation and laws on self- driving cars. The range and capability of a self-driving vehicle will always be limited to the sensors that it uses. While sensors are plenty advanced nowadays, unpredictable weather conditions like fog or rain or snow throws up a set of challenges.
How is your company helping customers deliver relevant business outcomes through adoption of the company’s technology innovations?
DEP works with companies on creating innovative solutions to real world problems. We have a long history in the automotive industry, being Headquartered in Michigan, we have worked extensively with leading automakers in the US, Europe and India. We have worked on a range of solutions over the years, to help clients address the problem they were solving. DEP works with companies across industries like automotive, aerospace, defense, biomedical, energy, electronics, oil andgas, consumer products, heavy equipment etc. We are strongest in automotive, as we are based in Detroit, and have the home field advantage there, but we are working on projects pan industries nowadays.
AI is projected to be the next market. How is AI contributing to the making of your products and services?
We are in the business of engineering data. We help organizations optimizes their product performance. This is math data-based approach that synchronizes multiple disciplinary product performances and advises the design team on how design parameters affect product performance. This is model data based predictive approach. We analyze pool of engineering data available in organization and help capture key learnings so that design team could leverage them in their product development. Our tools, techniques and methods do help businesses transform their product development cycle. Some of the tools we have built help organization that are involved in additive manufacturing to optimize the support for the parts. Our sensor and IoT has already been deployed to capture the data from engines in real time to make prediction on the products of combustion inside every cylinder of engine for every cycle. This makes closed loop real time control possible.
Do you also feel that the right kind of talent is a challenge in the industry?
The right talent is definitely a huge challenge that companies are facing, both to hire, and to retain. Especially for engineering companies like ours, where the requirement could be an advanced technical candidate, it can be challenging to get the right candidate, and they get poached easily as well. Losing a candidate after investing in training can be a heavy hot, especially for smaller workforces. Companies need to work with colleges to get more industry-ready talent available and address this problem.
Could you highlight your company’s recent innovations in the AI/ML/analytics space?
In early stages of product design and development, in the CAE design stage, CAE process automation helps companies significantly. Several parts of CAE SoPs (Standard Operating Procedures) are repetitive in nature, and automation provides opportunity to save time spent on those repetitive activities by the CAE User. Process automation in CAE can cover tasks like preprocessing, model assembly and / or post processing activities. Process automation in CAE can be deployed across various industries like automotive, heavy engineering, bio medical and aerospace. These processes and workflows can be automated heavily by using DEP MeshWorks which incorporates AI and ML in CAE processes with features and pattern recognition.
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