In this VUCA (Volatility, Uncertainty, Complexity and Ambiguity) world, industries face many hurdles like shortages of skilled workers, supply chain disruption, productivity issues, etc. Hence, manufacturers need to adopt data driven value-creation approach for developing quality and reliable products to stay ahead of their competitors. In this interview, Sandeep Shukla, Practise Head - Manufacturing Engineering, Tata Technologies, explains the concepts of digital manufacturing and its advantages to overcome challenges presented by market uncertainties.

What is digital manufacturing? Has Covid pandemic changed the dynamics of manufacturing with respect to usage of technologies & automation?
Digital manufacturing is an integrated approach leveraging digital tool & technologies for connecting physical and virtual world for the advancement of manufacturing processes and operation including manufacturing simulation, connecting machines & processes, collecting shop floor operational data and perform analytics for the effective, efficient & quality output.

Manufacturing has gone through the tough time during Covid 19, which forced industries to look for automated and intelligent system for resilient supply chain and de-risking by embracing data driven approach for strategic, tactical and operational decisions.

India aims to become a manufacturing superpower of the world. How important will be the adoption of modern technologies (like automation, robotics, AI, IoT, etc) for increasing India's competitiveness?
Although India’s work force is at peak among the rest of the world, it is very important that resources need to be rightfully utilised in effective manner and provide economical, quality & reliable products to the rest of the world, leading towards superpower.

Industry has many pain points like shortages of skilled workers, supply chain disruption, productivity, new product introduction, time to market, inventory management, talent gap, etc. It becomes difficult to address these challenges with innovative, futuristic, adaptable and robust integrated holistic approach to make sure business decision are adapting right strategy, at right time, with right cost-benefit analysis and with right technological solution. In present situation of VUCA world, embracing new-age technological solutions is the only way to overcome challenges in a short and longer run.

As challenges are increasing multi-dimension, opportunities are also expanding multi fold for those who are adapting modern technologies. By embracing technology-based data driven approach, they are able to differentiate themselves from others and provide innovative and value driven solution with less efforts.

What are the key hurdles in the adoption of digital manufacturing? Any tips for making adoption hassle-free?
Key hurdles to embark upon digital manufacturing journey are around people, process, and technology. It is imperative that such hurdles need meticulous planning, long-term vision, and concrete plan. It is also evident that hurdles can be converted into opportunities by leveraging on technologies.

Think big, start small and scale fast are the keys to implement digital manufacturing. Fail first, learn first, correct first and achieve first are some of the thumb rules to embark on digital manufacturing journey.

Alvin Toffler is credited with saying: “The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.” The statement is very much true from the perspective of digital manufacturing adoption as penetration of technology, scaling and adaption are taking place at high pace.

Small & medium enterprises (SMEs) are part of the supply chain of big manufacturing companies. Can these SMEs leverage on “Digital manufacturing” to increase their efficiency? Are there low-cost entry routes into automation for them?
SMEs are the key player in digital manufacturing journey, even though few of the OEMs are yet to embrace it. To bring transparency and connected value supply chain, SMEs need to be agile and proactive to increase their wallet share.

Resilient supply chain largely depends on SMEs agility and keenness towards technology adoption. It has been observed that SMEs usually take first mover advantage and bring the best to big manufacturing companies.

As industry is moving from mass production to mass customisation, it can be achieved ideally by incorporating full scalable technology-based solution, aiming for efficient and highly productive operation to gain competitive advantage.

To make the machine communicable with low-cost option, various edge gateway devices are readily available in industry and can be deployed to fetch the machine data for further artificial intelligence (AI) & machine learning (ML).

‘Smart’ is a buzzword for everything in the industry - right from factory to products to components/parts. What does ‘smart manufacturing’ mean to you?
SMART usually stands for specific, measurable, achievable, relevant and time bound; however, smart manufacturing is synonymous with Industry 4.0.

Smart manufacturing precisely tie together various functions of industry - like product design, manufacturing engineering, manufacturing operation management, supply chain and customer relationship management - under the umbrella of data analytics layers to perform descriptive analysis for business insights, predictive analysis using ML model and prescriptive analysis by implementing AI engine.

Smart manufacturing is a holistic approach towards creating digital image of all physical asset, manufacturing processes, operations and resources used to manufacture the product to optimise the input cost and maximise the revenue output.

What are the emerging trends in the manufacturing industry?
Emerging trends change based on industry segments and their growth patterns. But, the common trends for discrete manufacturing industries are manufacturing processes digitization; mass customisation and modularity; advanced predictive analytics; machine health & condition monitoring; resilient supply chain; sustainable manufacturing; and adoption of AI/ML.