The Changing Face of Manufacturing
Published on : Saturday 04-03-2023
Experts debate how Digital Transformation is redefining manufacturing in the IIoT era.

From partially automated manual workstations to automated single machines and now automated production lines – Factory Automation is redefining manufacturing in the IIoT era, reducing the human element and adding efficiencies like never before, freeing human workers from the mundane tasks to concentrate on more productive roles.
The technologies available for a Factory-Architect are many, and put so many capabilities into the hands of the planner. But any technology is limited in achievements by the imagination of the designer. The combination of IIoT and Artificial Intelligence can bring to reality many things which used to be stuff of science fiction just a few years ago. So which are the three new technologies which would be interesting for factories to acquire and adopt? Why would it be attractive?

“If one must consider just three, these would be Computing Power, Smarter Devices, and Datafication; also a couple of others like 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’,” says Dr Damodar Sahu, Head – New Age SaaS, Strategic Partnerships and Sales at Wipro Limited, USA.
For Sameer Gandhi, Managing Director, OMRON Automation India, the three most interesting technologies from the viewpoint of impact and lack of adoption in Indian manufacturing are – data visualisation, robotics and machine vision inspection. “While large amounts of data are available on the shopfloor – especially in automation systems – traditionally not much has been done to visualise and make this data actionable. To achieve this it requires not just software to visualise, but also a complete integrated architecture to gather the data and push it to the cloud layer in real time,” he says.
“There are many new technologies that could be interesting for factories to adopt, but in my personal opinion three that stand out,” says Nicola Accialini, Freelancer, Consultant, Trainer and Author, Accialini Consulting. These are:
1. Industrial Internet of Things (IIoT) – not only IIoT can connect factory machines and devices to collect data in real-time, but can be use as solutions to track personnel and batches. Some of them are called Real-Time Locating Systems and represent a very affordable and effective solution. IIoT can help optimise factory logistic, improve OEE, reduce downtime, and enhance predictive maintenance.

2 Big Data Analytics (BDA) – sometimes called Machine Learning (ML) or Artificial Intelligence (AI), BDA overall can help factories optimise production processes, reduce costs, and improve quality control. BDA can analyse large amounts of data to identify patterns, detect anomalies, and make predictions. This can help factories make better decisions and improve their bottom line.
3. Additive Manufacturing (AM) – it can be used in several ways. It’s important to acknowledge that we can identify up to 7 different additive technologies and many different materials, therefore engineers should identify the best technology for their applications. AM can be used not only to produce final products, but also to reduce the industrialisation phase by developing AM fixtures and tooling.
The fact that IIoT is a common thread running through all the expert views is no surprise. It is the fulcrum that helps enterprises leverage the collective attributes of digital technologies to deal with the complexities of modern manufacturing with relative ease. Now 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?

“Except for process industries, in most places it will take a longer time to reach, especially smaller MSMEs, where mostly the management is concerned about the investment which needs to be made in these technologies rather than the gains which can be realised due to the same,” says Monish Shete, CEO, Elscint India Pvt Ltd.

For Prabhakar Shetty, Chief Digital Officer, Cyient, the 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,” he explains.

Taking this further, Ramnath S Mani, Managing Director, Automation Excellence, opines there are several reasons why there is a delay in adopting IIoT in manufacturing. These, according to him, 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.


“Business leaders are taking a wait-and-see approach towards adopting the Industrial Internet of Things (IIoT), lacking the necessary understanding of the benefits and failing to embrace these transformative technologies and fear cybersecurity threats as technology is integrated into manufacturing operations. They are looking for proven case studies before the adoption,” expresses Sureshbabu Chigurupalli, Board Member-Director, Balasore Alloys Ltd, who believes the manufacturing sector's challenges are resistance to change and fear of migrating from traditional processes to new transformative technology. An ageing workforce and diversified skill pool also become a challenge to implement. “The best way to accelerate the journey is to start small – and think big. Pilot projects in small pockets are to be considered by engaging employees and showing results like remote monitoring of energy parameters, troubleshooting, etc. The tiny successful results will inspire and engage to move forward for large-scale adoption,” he adds.
Speaking about the scope for automation, 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,” says Dr Damodar Sahu.
“Yes, logistics movement on the shop floor is becoming more and more critical especially as manufacturers look for more flexibility in their operations,” says Sameer Gandhi, to whom flexible manufacturing implies that material movement – whether raw or in-progress – will be non-linear as the selection of which machine requires what material is dictated by varying demand. “This is where AMRs are a perfect technology. These can move goods to manufacturing cells in real time based on what the cell requires thus eliminating production bottlenecks and inventory build-up. And since AMRs are natural feature navigation enabled, they require zero or minimal guidance. Built-in safety features enable these to work in a collaborative mode with the humans and other moving obstacles on the shop floor. Additionally, fleet management software guides multiple AMRs to work as a team to fulfil the changing needs on the shopfloor,” he elaborates at length.
Nicola Accialini, draws attention to various technologies that are relevant for automating the movement of raw materials and work-in-progress within different types of factories, and quotes a few examples:
a. Automated Guided Vehicles (AGVs) – self-guided vehicles that can transport materials and products within a factory. AGVs can be particularly useful in factories with a high volume of repetitive material movement, such as automotive or food production.
b. Conveyor systems – Conveyor systems can be used to move raw materials and products along a production line. This technology is particularly useful for factories that have a continuous production process, such as those in the packaging or logistics industry.
c. Robotics – Robots can be used for a wide variety of tasks, from loading and unloading raw materials, pick and place operations to assembling products. This technology is particularly relevant for factories with complex manufacturing processes, such as those in the aerospace or electronics industry.
“Overall, the choice of technology will depend on the specific needs and requirements of each factory, as well as the available budget and resources. It is important for factory managers to carefully evaluate the available options and choose the technology that will provide the most significant benefits in terms of cost savings, efficiency, and quality,” says Nicola.
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. What are the perspectives on this front?
“Yes. That is correct and vision cameras are the best solution for this. This is another neglected area but is finding a lot of heft in the present day. Presently, inspection and quality is assumed to be the job of a quality inspector who checks the same parts day in and day out. This results in monotony creeping into the job. The only solution for this is to automate the inspection and quality process. Automating the same with the help of vision cameras or some fixturing needs to be definitely implemented on a large case,” says Monish Shete, who is in fact engaged in designing such systems. “Further, it also requires handling of the parts automatically, which gets us to the earlier question of the requirement of feeding of the finished goods. Again, the earlier mentioned feeding systems like vibratory bowl feeders and centrifugal feeders can definitely aid in this too,” he adds.
According to Prabhakar Shetty, most of the established enterprises follow rigorous Inspection and Quality control. “However, we see an increasing need for vision, camera, and 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,” he says.
“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,” says Ramnath S Mani, and highlights some of the latest trends and technologies in this area:
1. Machine Vision (MV) using high resolution cameras and software to automatically inspect products and identify defects.
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.
Niju Vijayan shares that quality being a vital parameter is no longer confined to the producer’s database but today travels across the value chain to provide data and inspire confidence across the elements in the chain. “Quality practices followed are getting increasingly digitised and available through traceability solutions, designed as part of the system. It is in the interest of the producer and user to have access to process quality data in order to correct anomalies and minimise defects. Regulatory requirements in pharmaceuticals and food demand digitised records pertaining to quality. Transparency in practices acts as a confidence boosting measure in long term relationships. Large number of recalls in the automotive industry in recent years sticks out as sore examples of process compromises being made,” he elaborates.
“Poor quality is the primary cause of product defects that impacts business relationships and your brand image. The sooner issues are identified the sooner the process can be adjusted,” says Sureshbabu Chigurupalli. According to him, manual inspection forms are not real-time analytics; one should analyse the gathered data to conclude. This could take hours and days. Manual quality control checks could be more inefficient and prone to errors. Changes in a parameter can affect the entire production process and the product lifecycle. “Digitalising the workflows and processes will lead to automated checks and help the rate of rejected products, rework, and customer claims due to quality issues. Improves traceability of information and reduces waste and cost,” he adds.
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,” says Dr Damodar Sahu. To him, 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.
Sameer Gandhi, who heads the operations of OMRON in India, says the company believes in creating the best harmonious relationship between people and machines at the shop floor. “The robots are supposed to bring in ingenuity and creativity by taking care of repetitive and hazardous activities so that the employees are able to climb up the skills ladder to focus more on higher-level tasks demanding more complex skills. For example OMRON mobile robots (AMRs) have been used for a variety of applications including for UV sanitation of hospitals, delivering hospital supplies, besides the traditional material movement on the shopfloor,” he emphasises.
Gandhi also draws attention to some other functions that are being robotised:
Pick & Place: Simple activities like picking and placing in a matrix or palletising, but also complex ones like identifying randomly oriented objects and placing in precise matrices.
Goods Movement: Autonomous Mobile Robots (AMRs) and Automated Guided Vehicles (AGVs) have an important and greater role to play here.
Quality Inspection & Precision: especially for the tasks which require a very high level of precision where makers do not wish to depend on manual intervention.
Flexible manufacturing: utilising AMRs and cobotsas one of the solutions in the material handling segment owing to their close harmonious communication interface with human beings creating oneness on the floor by working together.
“Robots are already being used in many different functions within factories, and their use is likely to continue to expand in the coming years. The functions that are most likely to be robotised are those that are repetitive, dangerous, or require a high level of precision,” says Nicola Accialini, and lists out tasks such as: assembly, material handling, painting, quality control and cleaning that are increasingly handled by robots.”Overall, the decision to robotise a particular function will depend on a range of factors, including the cost of implementation, the potential benefits in terms of efficiency and quality, and the availability of suitable technology. However, as robotics technology continues to improve and become more affordable, we are likely to see more and more functions within factories being performed by robots,” he adds.
Monish Shete believes functions like the following should get robotised very soon: automatic machine loading, machine unloading, segregation, transport, handling, and assembly. “As you rightly said, robotic automation can be used in all functions right from cleaning of the shopfloor to the final assembly and testing of parts. This has a lot of scope, especially in the machine loading and unloading. This is something which all factories should explore in order to improve their productivity as well as to improve the quality of their products,” he adds.
“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,” says Prabhakar Shetty.
“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,” says Ramnath S Mani. He too agrees with the opinions expressed by other experts with respect to robotic applications in the fields of material handling, assembly shops, painting and finishing lines, efficient packaging of finished products and in quality control and inspection. “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,” he points out.
Robots, according to Niju Vijayan, have become popular on account of 3 reasons – substitution of human workforce engaged in repetitive/non value added activities, jobs which are considered unsafe and where human precision falls short. “Considering the above, the areas where robots are expected to dominate are material handling, quality inspection and process functions. Load movement between points and within the manufacturing line comprises heavy loads and delicate components, ruling out human intervention. If they are driven by precision or process safety in industries like electronics, pharma and food while hazardous applications involving workforce safety demand robotic usage,” he notes. Commenting on collaborative robots, he is of the opinion that cobots provide the best of both attributes – human skills and precision handling – in the desired proportion. Cobots are emerging as a preferred mode of automation across manufacturing as they align well with the need to reskill existing workforce while achieving automation.
“Manufacturing robots create efficiencies from raw material handling to finished product packing. They can be programmed to operate 24/7 for continuous production. They are highly flexible and can perform complex functions. They are cost-effective even in small manufacturing facilities,” says Sureshbabu Chigurupalli.
The discussion on factory automation would not be complete without touching upon 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,” says Dr Damodar Sahu.
Concurring with these views, Nicola Accialini agrees that RPA is indeed an exciting tool for improving productivity in various industries, including manufacturing. “It is estimated that a significant number of factories have already adopted RPA, particularly in sectors such as automotive, electronics, and pharmaceuticals. However, the exact number of factories using RPA is difficult to estimate as it is not centrally tracked,” he observes.
“Presently, only a few large factories use this. However, this is definitely the way where the future is headed. The present mindset is that RPA is a very costly thing and not applicable for a country like India. However, this is not so and using RPA can help in reducing various supply chain processes, including data entry,” says Monish Shete.
“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,” notes Prabhakar Shetty.
According to Ramnath S Mani, the use of RPA as a productive tool in manufacturing is insignificant now and may increase in time to come. “As per a 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,” he says.
“RPA today is prominent in the service sector but has tremendous potential in manufacturing. Areas like logistics with a multitude of destinations, carriers, transportation modes, compliances and protection are hugely benefited. Similarly supply chain complexity can be efficiently managed through RPA where a plethora of vendors, variants, geographies, fitment, cost and compatibility challenge the manufacturers regularly,” says Niju Vijayan.
Summing up, Sureshbabu Chigurupalli opines that traditional organisations are reluctant to use RPAs as they are still deciding on optimising the workforce and the threat of disruption in industrial harmony as it will eliminate the crew. Scaleup is another issue to get the full advantage of RPAs. “Implementing RPA with a well-strategised plan will result in matched expectations and can ensure the success of automation is maintained. If the processes change frequently, it will be challenging to keep the RPAs.The selection of wrong automation may lead to the defeat of the objective,” he concludes.
Note: The responses of various experts featured in this story are their personal views and not necessarily of the companies or organisations they represent. The full interviews are hosted online at https://www.iedcommunications.com/interviews)