Industrial Automation Magazine India

After Covid-19, automotive companies have reworked their strategies

Published on : Monday 10-04-2023

Nilesh J Suryavanshi, Manufacturing, Engineering, Industry 5.0 (Cloud) at Tech Mahindra.

The pressure to bring out new models is high. One of the challenges is retooling. How would advanced automation mitigate this challenge?
Seamless integration of technologies like CAD, PLM, interactive 3D publications, MES, robots and IoT has enabled the automotive industry to launch new products regularly without much trouble in a relatively short period of time. It allows organisations to plan the product launch time frame, track the progress and take corrective actions to adhere to the schedule so that the new product is actually launched on the target date.
 
Any CAD model changes for a specific model version are auto-updated at the shop floor in e-SOP and visual video instructions which are fully automated and eliminates any lag in information sharing between the R&D and production departments.
 
Tracking and notification of overall CR health for all new products is monitored on the dashboard and notified to higher management for any critical deviations in the predicted new product launch date.
 
Robotics is a highly favoured technology for many applications in automotives. What are the strategies for re-programming these robots quickly for new models of automobiles?
Automotive industries are adopting industrial robots that comply with ISO 8373: 2012, which have the ability to reprogram multipurpose manipulators programmable in multiple axes, quickly changing the performed processes and desired motion route to launch new models in short duration. Companies are building teams to achieve smooth changeover of robotics according to new models.
 
Robots do perform many tasks efficiently, relieving humans from the drudgery of simple repetitive tasks. In future humans will be asked to perform the more complicated tasks using new technologies. How do companies plan to manage to upgrade the skills of humans alongside the new machines?
After Covid-19, automotive companies have reworked their strategies. Many of them are now planning for ‘Lights-Out manufacturing’ for some percentage of their production. These companies are also focusing on reskilling and up-skilling their workforce to implement industrial automation, robotics, computer vision, technology design and programming, IIoT, AR/VR, etc., in their plants. Most of the repetitive tasks are taken over by robots.
 
One of the key activities in quality assurance is visual inspection. How would automotive finishing lines plan to integrate robots, vision systems and specially AI into this task?
Automotive companies are extensively adopting computer vision, 5G and drones to transform to digital quality assurance; and drone based digital inventory tracking of finished goods in large sized plants. Computer vision, along with robotics, is implemented for paint defect analysis, raw material inspection, etc. Automotive companies are adopting computer vision AI/ML at each stage including raw material inspection till the final product. Even Tier 1 and 2 suppliers are adopting it based on requests from automotive OEMs.
 
Vehicles will have more and more automation on board. What is the kind of automation electronics which is suitable for applications on hot bumpy dusty terrain?
Predictive analytics-powered maintenance benefits car manufacturers as well as car owners. The latter can receive timely alerts about potential technical issues, and turn to manufacturers for maintenance rather than independent car repair shops.
 
Personal voice assistants: such assistants can adjust the temperature, provide information about the amount of gas in the tank, make calls, and change radio stations. Importantly, these tools have high levels of personalisation, meaning they can remember drivers’ preferences and suggest adjustments based on the context and user history.
 
New vehicles are designed with features like radar cruise assisted steering, magnetic adaptive suspension, automatic emergency braking, pedestrian detection, etc.
 
Remote start: one can start the car from home on a cold day. No sitting in the freezing cold waiting for everything to come up to desired temperature. Radar cruise control feature can adjust the speed based on the vehicle in front and assisted steering guides to follow the lane. So there is a lot of automation now available onboard the modern automobile.
  
(The views expressed in interviews are personal, not necessarily of the organisations represented)

Nilesh J Suryavanshi has 22 years of experience across multiple top enterprises and Indian startups with a strong foundation in True Digital Technologies – Industry 4.0 and hands-on experience in MES, IoT, Cloud, PLM, AI/ML and computer vision. He has worked with various industrial manufacturers such as Siemens, GE, Chevron, Spansion, Petronas, and Titan in providing Industry 4.0 solutions. Nilesh is experienced working in different industries such as pulp & paper, automotive, energy & utilities, refineries, petro-chemicals, cement, oil & gas, aerospace, etc; and also in manufacturing & IT consulting, program management, Industry 4.0 manufacturing practice, factory of the future, plant simulation & optimisation, MES (Manufacturing Execution System), IoT, IIoT, CAD, PLM, Cloud, RPA, digital manufacturing & robotics. He is experienced in program management with vendors like Honeywell, ABB, Siemens, Schneider, Aviva, Rockwell, AWS, Azure, and PTC, and has handled services like: Patching, Anti-virus, Remote access, Firewall, Edge Gateway, Storage, Active Directory, DNS, DHCP, File Share, Asset Management and Monitoring, implement CBM, Solution Architect, Solution design and technical architecture support, RPA, UI Path, etc.  Principal Solution Architect and program management for Pulp & Paper, Madras Cement, Shree Cement for digital twin plant simulation, modeling and  optimisation. Create Industry 4.0 roadmap.