Industrial Automation Magazine India

Platform and cloud driven IIoT approach will provide necessary scale

Published on : Sunday 05-03-2023

Prabhakar Shetty, Chief Digital Officer, Cyient.

Which are the three new technologies which would be interesting for factories to acquire and adopt? Why would it be attractive?
Manufacturing sector and factories cover a broad range of industries like automotive, industrial, energy, CPG, pharma, etc. Depending on the nature of the end product, adoption happens for technologies which provide acceptable RoI. Also, there is a technology architecture shift that started almost 3-4 years back, which brought OT technologies at centerstage, and will continue to remain foundation brick in next 2-3 years. With that in mind, we see the following technologies to be more promising in a factory scenario which will increase efficiency and EBITDA.
1. Industrial Internet of Things (IIoT) – Adoption of IIoT will happen beyond device or machine connectivity to connected processes, sustainability and health and safety. 
2. Cloud computing and 5G – With proliferation of 5G, we expect higher cloud adoption to increase the speed of digital adoption across factories with improved safety and security of data. 
3. Artificial Intelligence (AI) – AI use cases are more mature now and we see much focused investments on AI in specific factory areas like predictive maintenance, quality analytics, work instruction control, health and safety, etc.
 
Are there any factories where this IIoT movement will take longer to reach? What can be the reasons for this? What needs to be done to accelerate their journey?
IIoT movement or adoption depends on industry and geography. Industries like CPG, pharma, automotive, medical devices, hitech, etc., are faster in adopting IIoT in US and Europe. Higher probability of monetisation of efficiency improvement, manpower cost reduction and compliance drive faster adoption of IIoT. Whereas for other industries and geographies, defining a roadmap with clear RoI points will continue to take time therefore adoption will be slower. However, platform and cloud driven IIoT approach will provide necessary scale to business case proliferation, hence can accelerate the journey.
 
There are two work areas – bringing raw materials into the factory, and movement of work-in-progress inside the factory – where there is much scope for automation. Which technologies are relevant in this area for different types of factories?
These are very different topics and technology needs are widely different. Efficiency of bringing raw material into the factory broadly depends on purchase, logistics and inventory process, where traditional technologies like ERP or WMS will continue to dominate. However, technologies like RFID, RPA will automate repetitive and/or manual intensive tasks.
 
When it comes to movement of WIP or finished goods, we see an increasing need of energy efficient conveyors, MHE robots, AGVs depending on type of movement and products.
 
Inspection and quality is a very important topic. It is no longer just good enough to execute these functions rigorously, now it is a necessity to show off that it is being done. In other words customers might wish to view that inspection and quality check are being executed.
Most of the established enterprises follow rigorous Inspection and Quality control. However, we see an increasing need for vision, camera, AI based methods to improve first pass yield and compliances. Especially, for high speed factories technology reliance will boost overall quality control. This will provide easy access to view the quality process in execution.
 
Robots are going to be a presence in the factory. But importantly, which functions are going to get robotised? For instance, would cleaning the shopfloor be an application to use a mobile robot?
Robots are present for decades now and will continue to evolve in various forms and factors like Cobots, etc. Robots usage will remain high for tasks which are high speed, repetitive, precision oriented and heavy in nature. So, material handling and precision tasks are primary functions. There are areas like shop floor cleaning or hard to reach tasks where robots may come up but it depends on RoI. Another interesting segment to watch out for is application of humanoid robots with prominence of AI. It may take time, but humanoid robots can participate in core manufacturing functions like production and quality.
 
Robotic Process Automation – RPA is an exciting productivity tool. How many factories use this? Why don't others use it?
Factories have started adopting RPA for various activities like OCR, legacy HMI integration, CAD transfer to work instructions, cyber threat detection, etc. So, adoption is there but based on use cases. A structured change management and awareness of RPA tools will certainly increase usage of RPA at the shop floor.
 
(The views expressed in interviews are personal, not necessarily of the organisations represented)
 
Prabhakar Shetty is a seasoned executive with extensive experience in building and nurturing successful consulting and technology businesses. He has over 30 years of international work experience across industry verticals with repeated success guiding multimillion-dollar portfolios with P&L responsibility.
 
Prabhakar is responsible for the Digital engineering business leveraging new age technologies like IoT, Digital Twins, AR/VR, AI & Digital Transformation to help customers in their Industry 4.0 execution journey. Prabhakar leads multiple units like PLM, Manufacturing Automation, Asset Management, Engineering Content Management and Managed Services unified by a global consulting team to drive transformation services. This group leads all the digital initiatives across verticals including covering Product Design, Manufacturing, EPC, after market, Smart Cities, etc.
 
Prabhakar also leads the Products & Platforms units where he has initiated multiple solution streams to leverage LTTS pedigree in core engineering and align it with new age applications and technologies. Solutions for Building management (BIM), OEE, Golden Batch, APM, Manufacturing intelligence, Configurators across Design & Manufacturing, Energy & Sustainability Management are built by this team.