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Date: December 22, 2023

A key challenge with digital manufacturing lies in the initial high investment

A key challenge with digital manufacturing lies in the initial high investment
Outlines the numerous benefits that digital manufacturing offers in optimising various aspects of manufacturing operations. He also guides manufacturers through key challenges and emphasises the necessity for meticulous planning when investing in these cutting-edge technologies.

What is digital manufacturing and what use cases deliver maximum benefits?

Digital manufacturing, also known as Industry 4.0 or smart manufacturing, refers to the use of digital technologies and data-driven processes to optimise and streamline various aspects of manufacturing operations. It represents a transformative shift from traditional manufacturing methods to more automated, connected, and data- centric approaches, while also tapping into new technologies like AI, VR, and AR.

The current landscape is being transformed by rapid advancements and increasing complexity in manufacturing technologies. Digital manufacturing has enhanced business outcomes, with improvements of up to 88 per cent in productivity, 74 per cent in profitability, and 48 per cent in quality. The use cases of digital manufacturing that can deliver maximum benefits vary depending on the industry, which includes predictive maintenance, robotics, automation, and smart factory optimisation using tools such as digital twins to optimise production.

What sort of investments are needed to integrate IoT in digital manufacturing?

Digital manufacturing is the next step in industrial IT and software. With IoT, digital manufacturing can yield significant benefits, but it also requires careful planning for the investments to be successful.

Just like every industry, the specific investments re- quired will depend on the scope and scale of the digital manufacturing initiative. Largely, OEMs would require an updated inclusive strategy to introduce connectivity to legacy machines, robust cloud and connectivity infrastructure, ro- botics, secure data storage manage- ment, analytics tools with AI/ML, and device management and main- tenance. Upskilling of employees, maintenance of equipment, scala- bility, and future expansions are also factors that would require an investment, especially in the long run.

Additionally, investing in advanced sensors, edge computing technology, and regulatory compliance will go a long way.

Another area which is overlooked is the right partnership with system integrators for run management, which is critical for a flawless Industry 4.0 implementation.

What is the impact of digital twins for design for manufacturing (DFM) and how is it transforming manufacturing operations?

A digital twin is a virtual representation of a physical object or system, and in the context of manufacturing, it refers to a virtual model that mirrors a physical product, process, or facility. Digital twins have a lot of potential, and its use has a profound impact on Design for Manufacturing (DFM) and can transform manufacturing operations.

The way we run digital twins is going to be run on simulation, which is easier said than done. Digital twins have a significant impact on the DFM process in various ways. For instance, designers can use it to optimise the geometry of a product and even customise it, ensuring that it can be produced efficiently and cost-effectively. It can also help in virtual prototyping, reducing the need for physical prototypes, continuous improvement, better design collaboration and thus reducing the overall cost. It also enhances efficiency and improves the overall product quality.

What are the roadblocks while implementing digital manufacturing and how to overcome them?

Every implementation is a transformative process, which comes with its set of challenges and rewards. As far as digital manufacturing is concerned, one of the most prominent challenges is the high investment initially. Companies can consider phased investment and run a cost-benefit analysis to secure investment. With the rise in security challenges, implementing digital manufacturing raises safety and privacy concerns. Interoperability and scalability are also among the challenges that one faces with digital manufacturing. Like any other implementation, transformation to digital manufacturing will also have issues with management change which can be mitigated with a well laid roadmap and right stakeholder involvement at every stage.

How predictive frameworks can facilitate sustainable manufacturing?

Sustainability is the keyword right now and predictive frameworks can play a crucial role in facilitating sustainable manufacturing by enabling more informed decision-making. There will be great visibility of performance metrics, production and operational KPIs and live status of the overall manufacturing facility with such frameworks. In the long run, predictive frameworks can ensure sustainability by helping reduce waste, optimising resource usage, and minimising the impact on the environment. For instance, it can help with predictive maintenance by analysing equipment failures to schedule maintenance activities for a more energy-efficient downtime.

Optimising production processes by forecasting demand and production requirements accurately can be achieved, allowing manufacturers to adjust production timelines without resources going to waste. Predictive frameworks can also help in lifecycle assessment, right from raw material extraction to disposal, helping in assessing the environmental impact of a product. Resource recovery, waste management, and overall cost reduction are some of the ways predictive frameworks can facilitate sustainable manufacturing.

How immersive technologies can help in upskilling employees?

Immersive technologies, such as virtual reality (VR) and augmented reality (AR), are powerful tools for upskilling employees in various industries. These technologies create immersive, interactive, and realistic learning experiences that can enhance training, improve retention, and accelerate skills development. The “learning by doing” method is significant as employees are no longer passive participants with immersive technologies.

For one, VR simulations allow employees to practice and learn in a virtual environment replicating realistic, real-world scenarios. This is not restricted to operations training but also to soft skills, maintenance, and safety.

Moreover, such tools offer a safer learning environment as there’s minimal risk, given one can control the environment. A PWC report claims that 42 per cent of companies are using immersive technologies to provide their employees with better onboarding and training experiences.

Since the emphasis is on application or “learning by doing,” employees are no longer passive participants in online training sessions. Referring to Edgar Dale’s Cone of Learning (also called the Cone of Experience), people remember 90 per cent of what they do versus only 10 per cent of what they read or 30 per cent of what they see.

What is the future of digital manufacturing?

The future of digital manufacturing is characterised by rapid advancements in technology and transformative changes in how products are designed, produced, and distributed. The next stage in digital manufacturing is to emphasise its significance in the business landscape. However, it’s essential to acknowledge that this evolution is technology-driven. There are several technologies like 5G, Blockchain, AI, Machine Learning, Industrial Metaverse, Computer Vision, Drones, etc which will play a vital role. For example, 5G is poised to offer low latency, particularly beneficial for controlling autonomous AGVs. This development is anticipated within the next five years.

Author: Viven Chityala, Strategy Lead - IoT & Industry 4.0, Tata Elxsi