Revolutionizing the Auto Manufacturing Industry using Smart Technologies
Manufacturing processes have become complex, sophisticated and quick. It has become possible to produce goods, including automobiles, on unprecedented scales in a time-span that would have appeared improbable just a couple of decades back. The fantastic has become commonplace. Earlier, automobile manufacturing processes comprised simple assembly lines, repetitive, laborious work, and prone to a relatively high degree of human error. Automation, based on smart technology, significantly reduces the probability of such errors. This is because technology and machines do very specific work with far greater precision.
In a car manufacturing factory, there are so many steps – carving out a piece of metal with exact specific measurements, carrying different auto parts from one site of the factory to another, assembling the car and then painting and coating it to produce the final product. Additive Manufacturing (AM) has made these processes quicker, easier and more precise. Artificial Intelligence and 3D printing are being used to design entire vehicles – right from their bodies to interiors to engines, and manufacture a wide range of automobile parts.
Robotics and digital technologies have hastened the progress of automobile manufacturing. Already smart robots, human-machine interaction, and advanced quality assurance methods have become integral to automobile manufacturing.
Artificial Intelligence (AI) is another smart technology that has taken automobile manufacturing processes to the next level. Its expert systems process natural languages, machine visions and much more. In fact, AI is all set to further revolutionize automobile manufacturing in the following areas:
- Autonomous driving
- Predictive maintenance
- Quality control
- Supply chain optimization
- Human-robot collaboration
- Smart factories
AI facilitates collaboration between robots and humans in manufacturing and assembling of vehicles. Collaborative robots have turned into self-aware machines so much that they can use AI to detect and sense what human workers are doing and adjust their motions to avoid injuring their human co-workers. Robots are deployed for painting and welding. These can not only do the programmed task efficiently but also take corrective steps where needed. AI empowered robots can address defects and assist in quality control. This interaction between robots and humans has opened up immense possibilities for designing generations of robots that would be far more human-like in the future, thanks to AI driven machine learning.
Digital Twin is another smart technology that has provided an immense boost to automobile manufacturing processes. According to ibm.com, a digital twin is a virtual model designed to accurately reflect a physical object. The object being studied, for example, a wind turbine, is outfitted with various sensors related to vital areas of functionality. These sensors produce data about different aspects of the physical object’s performance, such as energy output, temperature, and weather, etc. This data is then relayed to a processing system and applied to the digital copy. Based on such data, the virtual model can run simulations, study performance issues and generate improvements, all with the goal of generating valuable insights, which can then be applied back to the original physical object.
In auto manufacturing, a digital twin enables planning of the entire manufacturing process in a virtual environment. After due evaluation of this virtual plan, it is given a physical shape. The production lines are built, conveyance systems are fabricated and installed, and robotic work cells are set up for automation and controls. Since the digital twin can work real-time, it can simulate a manufacturing system even when it is operational. This enables real-time monitoring, creates models and changes to the system. This helps optimization and validation of each phase of the production process through predictive and prescriptive analyzes.
The Internet of Things
Since the Internet of Things (IOT) connects the physical world with the virtual world, it plays a big role in smart manufacturing. It enables transfer, process, and exchange of data through sensor networks. Cloud computing and IOT have made inventory management easier, improved customers’ experiences, bettered supply chains, and reduced operational costs.
With IOT and AI working together seamlessly, a whole new generation of smart machines has emerged. We have automated self-aware machines connected digitally, with and within sensor networks making decisions and working without human intervention. We may as well say that IOT and AI make automation work like magic.
Enterprise Resource Planning
Like any other business or industry, smart manufacturing and smart factories need proper organization, planning, budgeting and operational structure. Enterprise resource planning or ERP plays a pivotal role here. It is used in running various day-to-day business or operational activities like finance and risk management, accounting and procurement or inventory management, budgeting, predictive maintenance, supply chain management and, of course, manufacturing. Essentially ERP tracks all aspects of the processes as logistics, finance, and production, and acts as a central hub of these integrated business processes. It provides transparency, as all the data and their flow can be accessed from this hub. Therefore, it is important in industries where a constant level of accuracy and efficiency is required, especially manufacturing. It covers end to end processes, starting from production to payroll.
While ERP ties up various business processes and acts as a central data hub, IOT tracks and monitors the flow and movement of information and provides real time information. Hence, integration of these two has tremendous benefits for businesses. Foremost is the flow of the data feeds into the ERP system. This bolsters business intelligence and improved decision making.
Second, in the world of smart manufacturing, the flow starts from the warehouse or smart factories and ends with the end user. So, manufacturers get access to a much bigger picture and greater amounts of data. This flow of big data helps people employed in the supply management to get right and timely information about when to look for what. It sends out notification to the right personnel, when a machine needs attention, repairs or if it breaks down, which is an enormous support in the manufacturing realm. Thus, it helps in predictive maintenance.
Third, with so many manual tasks being automated, human intervention is reduced to minimal if not done away with completely. This boosts overall and operational efficiency and accuracy.
Finally, this integration establishes a direct link between production and consumption. All this gives us an enormously large pool of data which is not only real time but transparent, making forecasting much easier.
AI tools provide an additional edge or push to ERP’s data processing systems. All data processing problems get significant improvement. Manufacturers want to use more of artificial intelligence and better, smarter technology every day, and more often than not, intend to develop this as a core strategy and a source of sustainable competitive advantage. It enables manufacturers to make much better real-time decisions. whether it is production, procurement or customer needs and demands affecting manufacturing process. While latest emerging technologies, such as AI, IOT and smart manufacturing, are ruling the roost, organizations need to understand the potential of these technologies and harness their benefits to the hilt. Organizations are often not adept at understanding the full potential of emerging technologies and require experts with proven track record to help them offer solutions to use these technologies and steer ahead of competition.
The Future is Here
Smart technologies have revolutionized automobile manufacturing by introducing autonomy, smart car technologies, and AI in several ways in automotive assembly areas and production lines. Using smart technologies has also led to the development of electric vehicles, which are more efficient and environment friendly than traditional gasoline-powered vehicles.
We are entering the era of smart cars, which are equipped with smart dashboards and holographic windshields that project information onto the windshield. These cars are capable of self-parking. They have adaptive cruise-controls that help maintain a safe distance from other cars on the road. They can detect blind spots and alert the drivers accordingly. Indeed, electric driverless cars may well become common in the none-too-distant future.
Today, automobile manufacturing industry has become far more efficient with more dynamic and cost-effective processes than before. Thanks to AI based systems, multiple production units can be integrated on a single platform. Thus, acquisition and use of various components, labor deployment and assembling require far less time and at far less costs. Now, since AI is being used in a big way in designing, setting up supply chains, and in production and post-production activities, the producers can afford to be more consumer-centric. One of the greatest advantages of using AI is that it has become easier to collect and process huge amounts of data on various vehicles. These data can facilitate actionable insights while strengthening privacy and data security. It has now become possible to deploy intelligent systems to evaluate defects in the on-road vehicles and make quality control better.
In conclusion, smart technologies are transforming the auto manufacturing industry by enabling faster time-to-market, flexible and scalable manufacturing, reduced downtime, optimized production processes, and reduced waste. Using sensors, machine learning algorithms, and robots in smart factories has increased efficiency and reduced the risk of injury to workers. The future of auto manufacturing is exciting as trends such as connectivity, mobility-as-a-service, autonomous driving, and e-mobility continue to shape vehicle technologies.
Will today’s “smart technologies” be superseded in future by yet-to-emerge smarter technologies?