The Impact of Artificial Intelligence on the Future of Manufacturing

HOW AI WILL IMPACT THE FUTURE OF MANUFACTURING

With robots attaining greater degrees of sensitivity in their touch capabilities, savvy manufacturers are embracing robotics in greater volume to increase efficiency and work rates on production, picking and packaging lines. AI and robotics will take over many assembling and movement-dependent activities in down the line, and reduce costs. Simultaneously, it will improve sensor and vision technology to create smarter, lighter and friendlier co-bots that are safe for humans. For example- automobile maker BMW’S self driving Smart Transport Robot travels the floor and sends out communication on any critical situation it sees.

Along with these improvements in different spheres , AI in the manufacturing will deliver more personalized and customized manufacturing which will capture the retail space. For example, A retail chain could locate their manufacturing robot or 3D printer in each store to produce apparel on demand of customer preferences. In addition to automating the process, it relocates the manufacturing process to a distributed but still centrally controllable model that bridges the gap between raw materials and end consumers. Ober a half of all manufacturers (56%) will prioritize developing new products and services when AI technology over the next three years, and with one of the top benefits of AI in manufacturing being efficiency in experience and produce, this is a positive step forward for the sector.

The automation of manufacturing will also support the notion of mass customization and on-demand production of products. However, AI brings challenges as well. 37% of manufacturers believe that training will be a significant issue while deploying AI. They will have to ensure thorough training across departments, providing them with essential information. 32% of manufacturers admit to a lack of knowledge about where AI can assist in the industry.The rapid evolution and convergence of multiple disruptive technologies that are part of AI make this a continuous challenge.

There is another dimension to this reskilling that is important to consider. With several roles becoming the domain of smart machines, people skills must evolve to meet the mandate of the fluid, new, and somewhat unpredictable roles that machines cannot fulfil, such as deeply understand product personalization needs, finding new needs of consumers and even evangelizing adoption of new kinds of consumption. Ultimately this means embedding “learnability” in employees through a systematic process of lifelong learning .