AI in manufacturing can be applied to prevent quality failures - Dr Pradeep Chatterjee, Part of the Global Delivery Centre of a leading Indian Automobile company
AI is driving a paradigm shift in the manufacturing industry. There is a shift towards a strategic approach with 2-3 years plan laid down to transform a factory into a future factory. Lot of supervision work in accordance to Standard Operating Procedure (SOP) can be taken up by AI engines. AI in products has a lot of potential applications, depending on the category of product manufactured.
AI in manufacturing can be applied to prevent quality failures and detect potential failures, such as, right fitment of parts or identification of cracks/rust/dents, etc. In after sales support, it can greatly help with diagnostics with faster resolution time. It can help in intelligent scheduling or predicting production failures even for external factors, so that corrective actions can be taken in time. Besides, AI can automate lots of processes and make it Zero-Touch, so that payments, settlements lead time, etc can be reduced drastically. AI will build expert knowledge and decision-making capability, reducing dependency on expertise of individuals. This will help improve productivity, cost effectiveness, decisions in accordance to market dynamics, and predict what can go wrong. AI will aid making decisions that might not be humanly possible.
The biggest hinderance, however, would be, acceptance by people that machines can think intelligently and make decisions. Secondly, if one looks for solutions from third parties, vendors come up with an exorbitant price tags even for small solutions, which is unreasonable if one knows the implicit technology. Moreover, the per transaction cost may look small but if one calculates total annual cash out, it will result in large outflow, which does not support a business case. Also, protection of IP in digital solutions should be conceptualised unless you develop it in-house. Business strategy and operations must change catering to the changes in external environment. Indian digital eco-system is still not geared up completely to adopt AI. Basic requirement for AI is data. In many cases we do not have sensors or the means to capture all relevant data. Second is connectivity, so that you have access to data even on the go. Speed of network or even availability of network at places is still an issue.
AI is poised to radically revolutionise the foundation of every industry - Sangram Kadam, Vice President & Head (APAC & META), Birlasoft
In India, AI has just started to establish its foothold in the manufacturing industry, which is trying to decode the implication and overall economics of adopting this new-age technology. The manufacturing industry has always been open towards adopting new technologies. While AI is poised to radically revolutionise the foundation of every industry, the manufacturing industry stands to gain significantly from this technological disruption. With the adoption of AI, companies can keep inventories lean and reduce the cost. There is a high chance that the Indian manufacturing industry will experience an encouraging growth. In the future, Artificial Intelligence will be the key determining factor that will decide the survival of the industry in an increasingly competitive scenario. Not adopting the futuristic technologies will keep costs elevated, inefficiencies in production and ultimately make operations unviable viz-a-viz competition.
Under the ‘Make in India’ initiative, the government aims to increase the share of GDP from the manufacturing sector to 25% by 2022. This will only be possible if timely and effective interventions by the government are implemented to foster growth of the industry through promotion of technology. There’s no doubt that the manufacturing sector is leading the way in the application of AI technology.
The Indian manufacturing industry is growing from strength to strength, developing capabilities around digital verticals and customer segments, expanding global delivery presence across traditional and emerging markets, and increasing focus on high value services. Artificial Intelligence has brought us into a new dimension that extends beyond the walls, opening the sheer scope of possible applications, from real-time maintenance of equipment to virtual design, improved and customised products, smart supply chain and the creation of new business models. There’s no question that Artificial Intelligence holds the key to future growth and success in manufacturing.
The future factories will be driven by robots with the help of data and AI - Feroz Khan, Associate Director, Boston Consulting Group
With Industry 4.0 coming into reality, it leverages to a lot of Artificial Intelligence and machine learning capabilities. The manufacturing industry is poised to transform its way of working. The future factories will be driven by robots with the help of data and AI which will enable running of machineries, equipment and transport unmanned by computer-controlled robotics automation. With the success of technology, there comes some challenges and AI is no different. The most important challenge is the legal and statutory aspect which comes due to erroneous data and algorithm, which leads to incorrect decision making. Other challenges, like technical knowledge and its application in industry domain leads to hyper optimism. In addition to this, lack of strategic importance is another big challenge wherein the organisation gives less importance to AI led automation and does not fit into the overall business plan.
Besides, AI is already bringing lot of disruption in manufacturing operations, especially in supply chain and shop floor execution. The manufacturing industry in India has still not excelled to become an evangelist in AI adoption, but the stage has been set and the pull can be clearly seen with Auto OEM leading this scape. Although the foundation of infrastructure is being laid for AI, ML and IoT, the mindset has still not evolved and most importantly, the change management is not being very effective. Still, there is a fear of human job loss due to which the skills and mindset change will take some more time. Some major applications, like Industry 4.0 and smart maintenance are already in the play, in addition to quality control and decision making process. With AI under the hood, warehousing process with robotics and autonomous transport have become more intelligent. AI will definitely be able to solve internal challenges, like expertise shortage and decision making over a period of time, which comes with the implementation of cognitive computing, which is more and more dependent upon the data collected over a period of time. This will bring in productivity, cost control and will improve market dynamics.