Cost and implementation time are two major IIoT challenges
Published on : Sunday 05-03-2023
Dr Damodar Sahu, Head New Age SaaS, Strategic Partnerships and Sales at Wipro Limited, USA.
Which are the three new technologies which would be interesting for factories to acquire and adopt? Why would it be attractive?
3 New Technologies in 2023 are: Computing Power, Smarter Devices, and Datafication. Few others are: IIoT and AI & ML.
Manufacturers globally were making some progress to digitally transform their factories during pre-pandemic. Proof of concepts and scaling-up of emerging technologies were underway to build smarter, increasingly automated, and more cost-effective factories. But, the disruption caused by Covid-19 has put them temporarily on hold. Now, it’s all accelerated and manufacturers’ digital plans drive progress toward the ‘factory of the future’.
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?
Cost and implementation time are two major IIoT challenges. Firstly, connecting devices and operations takes time, lots of it, and it's a very common hurdle to overcome. But implementing the Industrial Internet of things (IIoT) in business is a wonderful and worthwhile adventure.
IIoT is gaining a lot of traction within the manufacturing industry. According to Market Watch, the global IoT market within the manufacturing sector is expected to reach $88.4 billion by 2026. Three ways IIoT benefits the manufacturing industry. It makes it possible for manufacturers to reduce operational costs and create new sources of revenue by optimising asset management and inventory management, reducing machine downtime, and enabling more agile operations and more efficient energy use.
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?
Shop Floor Control (SFC) Software is an identifier used to track a material throughout production: Tool Management, Work Center Management, Shop Operations Management and Capacity Management. Build, test, and deploy custom solutions in minutes.
Inspection and quality are 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.
It’s important to have visual inspection software for manufacturing which helps reuse existing machine vision cameras to detect any visual defects, eliminate human error in manufacturing processes, and identify flaws in finished goods, missed robotic welds, pitting, and more.
Manufacturing Quality Control Best Practices are: Automate, Inspect, and Trace.
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?
Today most robots are used in manufacturing operations: 1. Material handling, 2. Processing operations, and 3. Assembly and inspection.
The future of ‘Robotics’ would be: Improved sensor technology and more remarkable advances in Machine Learning and Artificial Intelligence, robots will keep moving from mere rote machines to collaborators with cognitive functions.
Robotic Process Automation – RPA is an exciting productivity tool. How many factories use this? Why don't others use it?
RPA is a key enabler for digital transformation initiatives within the manufacturing industry, i.e., accounts payable process automation, invoice processing automation, and supply chain automation. There are a few of the areas where RPA can optimise the core operations for improved agility, speed, and quality. RPA helps bring agility in the process and long-term cost savings. It facilitates collaboration between man and machine, reducing errors and wastage, among many other benefits. McKinsey reveals that at least 87% of manual and routine jobs carried out by manufacturing workers are automatable.
When businesses do not test and optimise processes thoroughly before automating them, there is a risk of automated processes having problems. This leads to errors in succession. The failure of such a system will amplify the RPA’s mistakes and make them more difficult to control. More importantly, it affects work productivity, and aggregated data will not be accurate. In addition, the carelessness of businesses will cost them a great deal to remedy the consequences. We see the lack of creativity in RPA. It can only understand programming languages, not humans. Therefore, in some jobs, RPA will be somewhat limited compared to other technologies. But overall, Robotic Process Automation is still doing its job well. To scale up for RPA, we should combine it with other technologies such as process mining, BPM, etc. We should use some more technology to scratch our automation process. Because that combination will help RPA work more effectively, avoiding unnecessary risks.
(The views expressed in interviews are personal, not necessarily of the organisations represented)
Dr Damodar Sahu is the Head New Age SaaS | Strategic Partnerships and Sales at Wipro Limited, USA.
Award-winning, consistently rewarded, inspiring, highly collaborative, cross-functional Compassionate Leader in Alliances and Partnerships influences a variety of stakeholders and finds ways to create value through unique business relationships, enabling Partnerships Globally in Cloud, SaaS, Data, and Engineering credited with combining Sales, Marketing and Business Development.
Currently, Damodar is responsible for building Wipro's New Age SaaS Products Partnerships and GTM on Human Capital, Supply Chain and Procurement.
He graduated with a Bachelor of Technology degree in Electronics & Telecommunication Engineering, PGDBM in Operations Management from Amity University, MDP on Leadership in the age of Digital Transformation from IIM Calcutta, PhD in CS & IT from SunRise University, India,and Conferred with Honoris Causa Doctorate (Ph.D.) in Social Services with reference to World Peace and Philanthropy, Conferred with Doctor of Letters (D.Litt., USA) for Social Services and IT and Doctor of Technology (D.Tech) and Doctor of Philosophy (D.Hum) in Humanities from few International Universities.
Startup Mentor at Startup India, Startup Odisha and Centre for Innovation and Incubation (CII), Utkal University; Co-Founder & Lead – Odisha Healthcare AI @ Odias in Machine Learning; World Peace Ambassador – India by World Peace Tracts; Ranked as the #1 Global Social Seller for Wipro – by LinkedIn; Thinkers360 Thought Leader; Habits Champion at Wipro.
Damodar is also a Philanthropist supporting on Education to the underprivileged students of his village in Odisha, India.
You may refer more on Damodar Sahu @ https://www.linkedin.com/in/damodarsahu/
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