Industrial Automation Magazine India

Robots have become the lifeline of the automotive industry

Published on : Monday 10-04-2023

Amit Saluja, Senior Director and Center Head, NASSCOM CoE, Gandhinagar.

The pressure to bring out new models is high. One of the challenges is retooling. How would advanced automation mitigate this challenge?
This is a tough challenge in the current environment where product design is driving the need for new models being launched more often. This makes the organisation much more market focused but at same time puts pressure on the manufacturing cost as most of the time retooling is needed to accommodate the new design. The retooling decisions today are not based on the number of cycles done but more from the point of view of whether the machine will support the changes in product design.
 
This challenge has led to extreme focus on flexible manufacturing in the plants where enterprises can accommodate the product changes with minimum retooling time. Technology is playing a huge role in helping accommodate design changes in the manufacturing process. Control systems enable modular design as machine operations can be programmed with changes in control parameters. PLC programming is not a very difficult skill to build and with the advances in PLC that have happened, the customisation has become much easier. Most of the machines now come with sensors and options to get the operational data, analysis of these data can help in reprogramming which again makes the change over easier. Even in old machines sensor retrofitting options are possible to get critical parameters for analysis. If we look at advanced level, digital twin takes the machine operations monitoring and control to even next level that helps in taking real time decisions on process optimisation. These analysis makes the retooling much easier and more effective, hence brings flexibility in manufacturing operations.
 
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?
Robots have become the lifeline of the automotive industry considering highly repetitive tasks needed to be done with a high amount of precision. The level of productivity and efficiency we have today in automotive manufacturing couldn’t have been possible without robots. Industrial robots are used in every operation in plants like welding, painting, assembly, inspection and even in material movement.
 
While industry is depending heavily on robots, it also brings a challenge of handling situations that need changes in products and processes. The trend of bringing new models every year has made this challenge even bigger. Reprogramming of robots has become a regular activity in the plants, which is extremely time-consuming. As per the analysis, the total cost of robot ownership is mainly the programming cost. Thankfully, industrial IoT and software are making this process easier. Robots connected to systems and additional sensors being installed bring intelligence in the production line. Data acquired from robots and process parameters helps in optimising the reprogramming effort. Simulation software has greatly shifted the programming from online to offline which means no need to have production downtime to create new programs. Offline option also enables testing out various possibilities that are expected due to robot task changes. Adding a digital twin makes the reprogramming even better as multiple trials of robot actions can be done in a short time. The most critical element in the whole process is having good connectivity and integration between the robots and systems to enable seamless data transfer and intelligent decisions, which is nothing but Industry 4.0.
 
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?
Absolutely, automation and robots are not taking the jobs away, but shifting the jobs from regular mundane physical work to more intelligent tasks. This is a big change for which manufacturing enterprises need to prepare themselves by upskilling and reskilling their workforce. With so much focus on data acquisition in plants, we will need better analysis and decision making skills. Basic level of understanding of technology will also be critical in future; workers who are operating machines will need to be trained on operating computers and using software. While this appears daunting, in actual practice, it is not so difficult. It is just about changing mindset; workers do not have to learn software development, it’s more to gain understanding of the application of technology to the manufacturing challenges. We need to drive learning culture in the organisations and give incentives to workers who show interest to understand technology. There are plenty of online courses and awareness sessions being organised by institutions that manufacturers should leverage to train their workforce. At NASSCOM too, we are doing regular awareness sessions for the manufacturing leaders and blue collar workers to help them learn about the benefits of digital solutions to address various challenges in the plant. We have built an ecosystem where manufacturers can learn about the innovative solutions and work with solution providers to co-create customised solutions.
 
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?
Vision systems are very common in the automotive industry today and an integral part of the production system. Considering the high speed and precision needed to do the quality inspection, it is humanly impossible to do the manual visual inspection. Most common use cases are the inspection of component parts and sub-assemblies which could include engine parts, chassis, body parts like bumpers, beams and rails, seating systems and even electronic assemblies.
 
A lot of advancement has happened in the image processing algorithms over the last few years, thanks to AI and machine learning which has enabled building of high speed inspection systems with much more level of accuracy. Systems can detect the defects and do the measurements even up to microns level. Another good application of vision systems is sorting and detecting missing parts.
 
While AI is the core engine of vision systems, robotics also is essential part as solution involves multiple cameras mounted on arms to take images from every angle. The accuracy of system depends on how good the images are and for that even the lighting becomes important. Preprogrammed robots carrying cameras and sensors do the data acquisition which AI engine analyses to take decision on the quality of component being inspected. These robots are intelligent enough to even decide on when to take an image based on part location and lighting conditions. We are seeing exponential increase of vision system applications in plants and this will have a huge role in delivering defect free products with options of track and trace in case defects get reported from the market.
  
(The views expressed in interviews are personal, not necessarily of the organisations represented)

Amit Saluja is Senior Director and Head of NASSCOM center at Gandhinagar
 
In addition to NASSCOM, Amit has held leadership positions at IBM, General Electric, and RPG Transmission in a career spanning over 25 years. Having worked with industrial and technology companies in multiple domains, Amit has gained a rich and diverse experience in using digital technologies such as AI, Cloud, Analytics, and IoT to usher in greater efficiencies in manufacturing and driving business growth. He is a firm believer in making optimum use of technology for transforming internal business processes.
 
Amit is a certified Lean Six Sigma Black Belt and expert in devising Design Thinking methodology for building technology roadmaps. He is also a certified Smart Industry Readiness Index Assessor and trained to evaluate enterprises on digital maturity and advice for manufacturing transformation journey
 
Amit mentors Manufacturing Enterprises and startups on business strategy, process improvement and building technology roadmap.