Artificial Intelligence (AI) has made a tremendous impact across a number of industries, including manufacturing. Manufacturing, as an industry, has matured over time; with AI in the fold, the industry is set to radically evolve.
From the time the Industrial Revolution started, the focus of the manufacturing industry has been on reducing cost and the manufacturing time (time to market) by increasing operational efficiency and creating a safer work environment. Manufacturers have recently started focusing on improving the customer experience and making supply chains management even more complex. They are using the technology to make significant cuts in unplanned downtime to better design products. AI has the potential to transform manufacturing tasks like, visual inspection, predictive maintenance and even assembly.
AI and its many perks
Manufacturing is a capital-intensive process. Once a plant is a set-up, replacing, removing or renovating is exorbitantly expensive. Monitoring results at each and every phase of the manufacturing process is possible because of AI. AI also allows the organisation to take corrective measures at the initial stage. This allows businesses to save up on a lot, especially on the investments that are usually spent on rectifying damaged products or problems related to any machinery. Plus, it ensures predictive maintenance of machines and optimises usage of assets.
Improvement in the performance can happen with new machines, equipment and processes and thus, reduce redundancies. This improves the overall quality metrics. AI is proving to be an alternative to all of this and the price points are extremely competitive in nature. Manufacturing companies are finding it increasingly challenging to maintain high levels of quality and to comply with quality regulations and standards. This is because time-to-market deadlines are constantly decreasing. This is also because there is a rise in the complexity of products manufactured today.
Keeping product faults at bay
Today, a customer expects to have a product that is faultless. This is pushing manufacturers to use their quality matrices while understanding the damage that high defect rates and product recalls can do to a company and its brand. AI-based algorithms are used to notifying the manufacturing teams about the emerging production faults that are likely to cause product quality issues.
The rise of Quality 4.0
Data can be generated with the help of Quality 4.0. This data can help manufacturers know about the use and performance of their products available in the market. This information is important and crucial to the product development team, helping them make both strategic and tactical engineering decisions.
Making robots more efficient
Robotics, for the past couple of years, has become an integral part the manufacturing sector. There has been a considerable amount of improvement in the finesse, complexity, and sophistication of a task done by a robot because of the advancements AI has made. Tasks which were previously relegated to the human domain due to complexity and labour constraints are now routinely completed by robots.
The human-robot collaboration needs to be efficient and safe as more industrial robots enter the production floor and work alongside a human. As AI advances, industrial robots are going to develop which will enable these robots to handle more cognitive tasks. It will also allow it to make autonomous decisions based on real-time environmental data and will further optimise processes.
Supply chain and AI
Moreover, supply chain is the backbone of the manufacturing industry. With the help of AI-based solutions, it helps in reducing transportation cost, warehouse management, efficient supply chain administration and reducing pilferage. Large and diverse data sets can be processed with the help of machine learning. This can be done on a real-time basis for estimating demand. In a collaborative supply chain model, it is helping in the reduction in freight costs and improving supplier delivery.
AI is changing almost everything one can ever think of, including the way a product is designed. One technique is to enter a comprehensive brief defined by designers and engineers as input into an AI algorithm. The brief includes data describing restrictions and various parameters including information, such as, material types, available production methods and budget limitations. The algorithm explores every possible configuration before it finalises on a set of the best solutions. ML-based solutions recommend designers and manufacturers as to which design works best for a particular product.
In this scenario, AI-based algorithms are completely objective. No assumptions are taken at face value. Every minute detail is tested according to actual performance. This is done against a wide range of manufacturing scenarios and conditions. The core element of the Industry 4.0 revolution is AI and which is not limited to the use cases from the production floor. The manufacturing supply chain can also be optimised with the help of AI algorithms – this helps companies to anticipate how the market is going to change, which becomes a massive advantage for the management, making them move from a reactive mindset to a strategic one.
Where India stands
When it comes to AI in manufacturing, India lags considerably behind. SME manufacturers are still trying to decode the implications of AI and its overall economics of adopting this new-age technology. Upgradation of technology has been slow in India because of two factors – the first is the paucity of funds and the second is the lack of awareness about the importance of this technology and its capability of disrupting the industry.
The government’s role
Not just private organisations, but the government, too, should play an important role by providing provisions for the intensive training of industrial workers on using smart machine and AI-powered tools. The Government of India recently allocated ₹6,000 crores toward the development of tools rooms across the country to support the small manufacturing players by providing support in terms of design and quality. Also, the Samarth Udyog Council, which is created by the Department of Heavy Industry (DHI), part of the Indian Government, in association with CII, promotes digital technologies in manufacturing. The most important initiative by Samarth Udyog Council is AI-ML-analytics in a factory to help improve productivity. AI claims that it is only an evolutionary form of automation, a predictable result of the 4th Industrial Revolution. It may be efficient at improving things and making them cheaper, but it cannot replace human ingenuity in dealing with the unanticipated changes in tastes and demands.
Helping stay ahead
AI is finding its place in manufacturing, whereas it still has a long way to go in India. While AI, as we all know, is a pivotal element of Industry 4.0, it is certainly a game changer for the manufacturing industry, opening up entirely fresh and diverse opportunities for businesses. It promises to augment the capabilities of humans and helps with data-driven decisions, making sure companies stay ahead in the industry.