Sustained R&D in multiple aspects (related to productivity, precision and reliability) of machine tools and their tooling technologies are required to achieve substantial improvement that provides a competitive edge for the machine tools manufactured in India, globally. Among these machine tools, the development of so-called “Mother Machines'' (The Japanese call them “mother machines'' because they make other machines possible) is currently limited to Germany and Japan. Recently countries like Korea and Taiwan, that have a strong history of machine tool development, and an equally strong R&D mechanism with deep and long collaboration with universities, are also into this development of mother machine tools. The development of such machine tools in India must likewise be oriented towards a collaborative mechanism which brings key stakeholders such as industry, academia and government to address the major technological gaps. Thus there is a need for an eco-system that fosters innovation in multi-disciplinary domains to achieve this combination of software, hardware, and precision manufacturing.

Production facilities developed and maintained by several public sector enterprises are neither completely utilised nor scaled up to leverage the needs of growing demands in our country. There is a huge potential to leverage such facilities for missions with national cause. Apart from the public sector enterprises, many private sector organisations, as well as a good number of SMEs, can join together in enabling the concept of shared manufacturing under Smart Manufacturing Technology-driven approach to cross utilise and effectively plan their services to their capabilities in the production process. The realization of shared manufacturing related services necessitates the development of a networking platform.

Manufacturing industries are witnessing significant technological advances aimed at enhancing their efficiency and productivity. The Internet of Things (IoT) enables information from all related participating systems in the right perspectives/context to be collected/monitored/used to have close collaboration, coordination, synchronisation between the different factory/plant systems and computational space. This collaboration, at multiple levels (machines, cells, production lines, production floor, plant, enterprise, eco-system), enables the manufacturing industries to transform into Industry 4.0. and necessitates the following:Self-organisation through learning from history and collaborations.
To improve human - machine collaboration and enable machines to learn from explicit and implicit data. Technologies such as machine learning and deep learning already allow the production systems to move away from making fixed decisions to exhibiting context-aware strategy executions. However, a key challenge with the learning technologies is to enable their learning by providing them with the training data, so that they guarantee the required reliability and safety, demanded by manufacturing plants which implement them.