Industrial Automation Magazine India

The nature of work is set to change with the adoption of digital technologies

Published on : Wednesday 08-06-2022

Prashant Rao, Head of Application Engineering, MathWorks India.

Between the leading MNCs with operations in India and the average SME, what is the status of the digital transformation (Dx) journey in the Indian manufacturing industry? How wide is the gap?
There are several elements that push organisations to adopt digital transformation. Market and customer demands, competition, evolution of products are some of the factors. However, what we have seen in the last two years is that many organisations who were not adopting digital transformation were forced to take that path owing to the pandemic. Given this scenario, it would be surprising to see any SME in India not having initiated this journey. However, we will see organisations at various levels of digital transformation. They will range from companies who have adopted digital way of operations in one department or a few projects to organisations where transformation is pervasive and, in the design, rather than an afterthought. In these organisations, digital transformation is driven from top and is customer centric. There is also a factor of getting your people skilled and ready to lead this transformation. You will find organisations at all levels. It is not just limited to India. Hence it may be difficult to quantify the gap.
 
It is heartening to note that Indian SMEs are also adopting digital transformation in an accelerated way. One advantage that India should continue to leverage is a more digital savvy workforce. The transformation has also been accelerated with mainstreaming of many technologies around AI, Industry 4.0, IoT, etc.
 
What are the common mistakes most enterprises make while implementing Industry 4.0 technologies?

Transformation tends to go wrong when organisations think digital transformation is only about technology. We believe organisations should give importance to all the three pillars that enable transformation, viz., People, Process and Technology. Unfortunately, most of the literature available in the public domain is about the technologies that enable the transformation. There are organisations that have invested heavily into technologies but failed to optimise the processes or build the talent to drive the intended transformation. Technology is just one piece. The outcomes from technology investment will not be realised if we don’t look at processes that help adapt to the new situations and upskill and reskill people to adopt the change.
 
Another pitfall happens when organisations think of digital transformation as a project. We see it as a journey rather than just one project. Some of them think of transformation as buying a few devices, getting a website up and incorporating digital payment. However, digital transformation is about continuous innovation, rapid response to change and even capturing the opportunities that come your way. This will not happen if you look at this as a single project.
 
To effect transformation or change, some organisations begin with proof-of-concept and pilot projects. They soon find themselves mired in a ‘pilot purgatory’; unable to scale up by formalising the piloted approaches and making them part of the company’s standard workflows and practices. Other organisations start with large infrastructure development efforts that are difficult to execute and fail to meet the requirements of the actual projects, workflows, or products that emerge from the transformation strategies.
 
Smart manufacturing is viewed as too expensive a solution for a labour surplus economy. How justified is this argument?
Adoption of smart manufacturing should be seen as an opportunity by countries like India to be competitive and to bring resiliency in supply chains. A digital enterprise will improve the quality of the products, reduce costs of production, increase time to market and be more agile in responding to customer demands. With more transparency in the processes and communication, organisations can address risks associated much quickly. All these factors will have a positive impact on the top and the bottom lines of the company and hence should improve the employee earnings too.
 
Yes, the nature of work is set to change with the adoption of digital technologies. While automation tends to displace some types of jobs, it will create newer types of jobs. This will require organisations to continuously reskill their employees. MathWorks understands this need of our customers. Our tools are designed to help engineers with domain knowledge to adopt technologies like artificial intelligence into their work areas without spending huge chunks of time to learn new programming languages. This ensures the engineers leverage and build on their existing knowledge.
 
What is the extent of implementation of predictive maintenance and other process optimisation technologies?

Implementing predictive maintenance helps reduce downtime, optimise spare parts inventory, and maximise equipment lifetime. To get started, first you need to develop an algorithm that will predict a time window, typically some number of days, when your machine will fail and you need to perform maintenance. Algorithm development starts with data that describes your system in a range of healthy and faulty conditions. The raw data is pre-processed to bring it to a form from which you can extract features that help distinguish healthy conditions from faulty (conditional indicators). Then you need to use these conditional indicators to train a model that helps you detect anomalies, classify different types of faults and estimate the remaining useful life of the product. Once you have that you need to deploy the algorithm and integrate it with other parts of your machine maintenance and monitoring system. We see companies at various stages of this workflow of predictive maintenance.
 
How does MathWorks work with companies in overcoming their fears and convincing them about the advantages of Dx?
Almost every organisation seems to include digital transformation in its vision and strategy, but most struggle with executing digital transformation initiatives. There are myriad reasons: the challenges of introducing new technologies and providing the workforce with relevant skills, ensuring that the company’s culture and organisational structures are conducive to change, and anticipating correctly which processes need to change and how, to name a few.
 
We have observed that organisations are often most successful with digital transformation when they adopt a pragmatic approach. MathWorks encourages our customers to adopt this pragmatic approach by looking at transformation as a journey. We work with senior management in organisations to help them understand the impact on people, process and technology rather than just looking at the technology.
 
Pragmatic digital transformation does not require starting from the ground up or completely overhauling existing processes and assets. Just the reverse; its fundamental principle is reuse: In pragmatic digital transformation, data, and models—and the engineering teams’ associated skills in developing analytics, models, and simulations—are applied systematically to workflows throughout the life cycle of the product or service.
 
The systematic use of data can start with analytics developed specifically to get insights from experimental and research data. But it also means scaling and extending those analytics to huge, heterogeneous sets of live and archived data, acquired from manufacturing, maintenance records, and other business processes, to enable data-driven decisions not only during research and design but also in production, operations, and maintenance.
 
Digital transformation begins when the accumulated knowledge and transformative potential of this data can be uncovered and applied systematically throughout the product life cycle. The core tasks are, first, to integrate data from multiple repositories; second, to develop analytics that are easy to use and access; and third, to integrate those analytics into the workflow at the right time to enable groups throughout the organisation (engineering, business-unit management, analysts, service teams, and more) to apply insights from the data to improve processes or designs.
 
Are the incentives offered by various government schemes enough to tip the scales?
The Indian government is focusing on boosting India's industrial strength through several programmes. The most important is the 'Make in India' initiative, which aims to create a conducive climate for innovation and skill development. Intellectual property development and the creation of world-class manufacturing infrastructure will be among the outcomes. The programme aims to assist native enterprises in developing high-quality products through the adoption of new technology, rather than only inviting foreign companies. This will encourage Industry 4.0 technology adoption along with facilitating talent development. Educational and technical institutions would also be developing course content to help the reskilling and upskilling young minds.
 
The Ministry of Electronics and Information technology has announced the Design Linked Incentive (DLI) Scheme to offset the disabilities in the domestic industry involved in semiconductor design. This would encourage the industry not only to move up in value-chain but also strengthen the semiconductor chip design ecosystem in the country. It is also heartening to see the focus on building skills and thereby generating IPs. The Chips to Start-up (C2S) Programme aims to train 85,000 numbers of high-quality and qualified engineers in the area of Very large-scale integration (VLSI) and Embedded System Design.
 
Prashant Rao heads the Application Engineering team at MathWorks India. Prashant is a regular contributor at industry forums, sharing his views around megatrends in technology and how Artificial Intelligence (AI) is getting adopted across industries and other technologies. He works closely with the academic community to help develop analytical and AI-related skills that make them industry-ready.