Industrial Automation Magazine India

Most companies are still on evaluation stage or infant stage of implementation

Published on : Sunday 05-03-2023

Ramnath S Mani, Managing Director, Automation Excellence.

Which are the three new technologies which would be interesting for factories to acquire and adopt? Why would it be attractive?
While Digitisation, Digitalisation, Industry 4.0 and IIoT are being talked about freely, only a few companies worldwide have employed these technologies in their entirety and got the benefit. This is because figuring out what best suits the needs of the company has been a great challenge due to cost of implementation and the return on that investment. More and more companies are looking at it seriously.
 
However, as of now, the 3 technologies that would be interesting to adopt are:
1. Integrating Digital Technologies to physical products like the Field Devices, PLCs, Drives, etc., for conversion to IT based protocols, integrating all the information into a single Platform and connecting it to Analytical tools. The basic step towards adopting Industry 4.0 or Internet of Things for Automation would be to connect Machines and Devices allowing for controlling Industrial Process and Remote Monitoring. 
 
2. Robotics, Machine Learning and Artificial Intelligence will be used for Process Optimisation, Quality Control, and Predictive Maintenance to adapt to a changing world order with local and distant manufacturing facilities. Artificial intelligence can better understand and perform more complex tasks using this technology. It is estimated that 5G will also revolutionise the way we live and work in the future.
 
3. Secure Cloud adoption will unlock expanded access to analytics, driving a revolution in smarter decision support to manufacturers. Till now, some have been using analytics for quality inspection and security use cases, but it will increasingly be used across key areas of operations, such as overall production performance, customer experience, product traceability, cyber security and safety programs.
 
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?
While most large companies with multiple locations and high manufacturing capacity are adopting the new technologies in their IIoT movement, most companies are still in the evaluation stage or at the infant stage of implementation. 
 
There are several reasons why there is a delay in adopting IIoT in manufacturing. These include:
1. If not thought out properly, implementing IIoT technology can be expensive, and many manufacturers may not have the budget to invest in it or may not find a favourable Return on Investment.
2. IIoT technology can be vulnerable to cyber-attacks, and manufacturers may be hesitant to adopt it until they can ensure that their systems are secure.
3. The perceived complexity in adopting IIoT technologies is also a reason for postponing decisions for its implementation.
 
The best way for adoption of IIoT technologies is to take a holistic view of what needs to be done for a given manufacturing organisation and then choose the right platform and vendors to ensure that one can seamlessly implement in stages and see the benefit at each stage before jumping to the next. This needs complete focus at the highest level of the management, a dedicated and committed implementation team and a complete viable strategy of implementation. 
 
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?
Bringing raw materials into the factory from vendors would fall under the umbrella of Supply Chain Management which could include IT technologies that link manufacturers with their various vendors through a common software link through a Hub & Spoke model. The use of Data Analytics and Machine Learning algorithms to analyse historical data helps in demand planning and forecasting which in turn optimises their inventory levels and reduces wastes. Furthermore, Blockchain Technology creates a transparent and secure supply chain network that can improve traceability, and enhance data sharing and collaboration.
 
The use of robotics and automation technology including Automated Guided Vehicles (AGV) can be used to move materials from one point to another. Typically used in warehouses and factories are Automated Storage and Retrieval Systems (AS/RS) that can store and retrieve materials from a warehouse. The use of GPS Tracking, Telematics and other technologies also reduce transportation costs, improve delivery times and increase visibility and transparency in the supply chain. Drones are also expected to be used for transporting materials within factories.
 
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.
Several advancements have taken place in Automation of Inspection and Quality in manufacturing that are transforming and helping to improve accuracy, speed and efficiency of quality control processes while reducing costs and improving overall product quality. Some of the latest trends and technologies in this area are:
 
1. Machine Vision (MV) using high resolution cameras and software to automatically inspect products and identify defects. Advances in Machine Learning algorithms have enabled these systems to detect and classify defects with high accuracy, reducing the need for human intervention.
2. Artificial Intelligence (AI) is used to analyse large amounts of data from sensors and other sources to detect defects in products, thus removing human errors and improving quality control processes.
3. Augmented Reality (AR) overlaying digital information into physical objects to help workers identify and fix issues during the inspection process.
4. Collaborative Robots (Cobots) designed to work alongside humans to perform repetitive and hazardous tasks including inspection and quality control. They can be programmed to perform a range of tasks from simple visual inspection to more complex analysis using AI and Machine Vision.
 
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?
While cleaning the shop floor could surely be a potential application for mobile robots, there are many critical areas of application for robots in manufacturing and factory floor settings.
1. Material handling for moving raw materials and finished products from one workstation to another including loading and unloading materials from machines, transporting and packaging finished products.
2. In Assembly Shops, robots can be used to perform repetitive tasks to improve efficiency and consistency and reduce human fatigue. 
3. In Quality Control and Inspection, robots can be used to inspect products for defects using machine vision and other sensing and AI technologies. 4. In Painting and Finishing Lines, robots can be used for precise and consistent quality.
5. Robots can be used efficiently in Packaging of Finished products. 
 
Overall, employing robots will improve efficiency, consistency and safety in manufacturing and factory floor settings by automation tasks that are repetitive, hazardous, and require a high degree of precision.
 
Robotic Process Automation – RPA is an exciting productivity tool. How many factories use this? Why don't others use it?
Gartner defines Robotic Process Automation (RPA) as the software to automate tasks within business and IT processes via software scripts that emulate human interaction with the application user interface. With RPA, software users create software robots or “bots” that can learn, mimic and execute rule-based business processes. They can be used to perform tasks such as addressing simple queries, data entry, and form filling, report generation, etc.
 
The use of RPA as a productive tool in manufacturing is insignificant now and may increase in time to come. Industry, particularly manufacturing, is grappling with many technologies that need to be implemented to improve efficiency and productivity and RPA may not be its priority now. As per Deloitte report, the main reason why factories don't use RPA is because of the cost associated with implementation as RPA requires significant upfront investment in software and hardware. 
 
Ramnath S Mani is a 1969 B.Tech (Hons) graduate in Electronics & ElectricalCommunication Engineering from IIT Kharagpur and a pioneer in the field of Industrial Automation in India. He was part of the initial team that set up Allen Bradley India (now Rockwell Automation) and was its Vice President from 1985 to 1990. He was the Founder Managing Director of Emerson Control Techniques India, for offering Digital Drives and Automation systems for the manufacturing industry. He has been Chairman of Emergys Software India and Managing Director of Automation Excellence. 
 
Mr Mani has been past President of IIT Kharagpur Alumni Foundation India and past Chairman of Pan IIT Alumni India from 2018-20.  He is the Founder Managing Trustee of Dharaneeswarar Educational Trust, a NGO, which runs a school Sankara Matriculation School, for underprivileged and first generation school going children at Thandalam Village in Tiruvallur District, Tamilnadu.