Capgemini Driving New-Age Technologies In Auto Industry

Capgemini Driving New-Age Technologies In Auto Industry

July 2020 Interaction Capgemini Driving New-Age Technologies Auto Industry
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The Indian auto market is the fourth largest in the world, and has been an early adopter of new technologies to enhance manufacturing efficiency and quality

Auto Tech Review spoke with Maneesh Pant, Vice-President, Automotive, Mobility & EUC Sector Hubs – India, Capgemini, to understand the significance of next-generation technologies in the auto industry. Capgemini is a provider of consulting, technology and digital transformation services across industry verticals.

While the COVID-19 pandemic has left a trail of negativity across the world, it would fuel implementation of new-age technologies of Industrial Internet of Things (IIoT), Advanced Robotics, Digital Twinning and Blockchain. These technologies were already experiencing growing utilisation in the automotive sector due to the benefits they offer, in terms of designing and manufacturing of components and vehicles, noted Pant.

ADVANCED ROBOTICS

Advanced robotics has been witnessing increasing adoption on the shopfloor due to the precision capabilities it has. In addition, with the COVID-19 situation calling for minimum workforce and social distancing, the adoption of robotics would enable manufacturing plants to continue production with a lower number of employees being physically present at the facility. This technology therefore assists in the prevention of incidents at the workplace, be it related to coronavirus or inefficient workforce.

Traditionally, robots have been used in car manufacturing in areas of painting and welding, and nothing much beyond these operations. However, artificial intelligence (AI) and machine learning (ML) are creating self-learning robots that can take corrective actions, while performing the assigned tasks. As use cases are increasing, there is a development towards robots being fitted with cameras for the purpose of ‘cognitive quality’ inspection, and this is a big leap in the industry, observed Pant. Such advanced robots are used to carry out quality inspections and use image analytics with the power of AI.

Further, edge computing is also seen to be adding to the efficiency of cognitive quality in robots. According to Pant, some of the cognitive quality robots are becoming more efficient with the requirement for use of cloud or internet getting limited. Additionally, the collaborative aspects of robots are making them work with each other as well as enabling them to monitor each other’s health and performance levels. The use of advanced robotics will aid in agile manufacturing, which is highly efficient in nature. Machine learning also has led to the development of Exoskeletons, which are also types of robots that aid human operators in reducing fatigue.

DIGITAL TWINNING

Digital twinning is gaining popularity and relevance in the industrial arena. The digital twin technology can be bifurcated with focus on product and production, at least with regards to the automotive sector. With regards to the product, digital twinning covers recording and storage of data about the performance of the product, with the presence of the simulation environment of all the systems and sub-systems of the product, said Pant. IoT has added to the sophistication of digital twins, thereby making it more insightful for further development.

As a step ahead, AI and ML are being used to offer solutions that can predict likely failures following analysis of information received via sensors. This solution is also helping in drastically reducing test cycle times due to the precise development procedures that can be carried out, opined Pant. Therefore, digital twinning is becoming more insightful and productive in product development, which translates into reduced time in new product introductions.

On the production front, digital twinning plays out a similar concept in the sense that machine conditions can be monitored thoroughly now, with the ability to capture production data, said Pant. Sensor data enables the predictability of likely failures in the line, which could lead to a halt in the product itself. The stoppage of production leads to tremendous losses in a company and this methodology of monitoring production is important for manufacturers. Bringing the connection between product twin and production twin is something known as “digital thread”. This digital connection between the product twin and production twin plays an active role in the work being carried out by automotive companies. Pant said the act of carrying out development work for products and that of production in separate silos has not resulted in efficient production and manufacturing. Digital thread can enable improved overall product design and production, and is nowadays offered through product life cycle management (PLM) platforms themselves.

BLOCKCHAIN

Blockchain was introduced around 2017-18, and was initially viewed with a bullish sentiment in the automotive industry. The technology has the ability to provide trust in terms of data capture, since transactions are stored in guarded ledgers. There is a provision of cyber security of data generated during production as well as from the vehicle from Blockchain. Additionally, in case of vehicle recalls, the product’s genealogy can be traced back using the technology, Pant stated.

The main challenge of Blockchain is concerning the cost involved, and the liability of which party of the automotive ecosystem should pay for the infrastructure. Another uphill task in the use of Blockchain is in making suppliers agree to become a part of this ecosystem.

CONCLUSION

Technologies such as IoT, AI, ML, Digital Twins and Blockchain have been around and are being implemented across the auto sector. However, the technology of augmented reality/ virtual reality (AR/VR) will gain tremendous popularity, especially for use in innovations like digital showrooms for immersive experience, Pant pointed out. However, the challenge lies in finding target customers and leveraging customer data and profiling them, he signed off.

TEXT: Naveen Arul