IT Leadership

IoT Boosts Quality, Safety, Productivity for Smart Manufacturing: Sumit Chowdhury, CEO, Gaia Smart Cities

Sumit Chowdhury of Gaia Smart Cities speaks to Dynamiccio's Muqbil Ahmar

Smart manufacturing, which is aided by technology, is the only way forward if we have to envision Industry 4.0. DynamicCIO’s Muqbil Ahmar (MA) spoke with Sumit Chowdhury (SC) of Gaia Smart Cities, which is involved in the Smart Cities Mission, about what it takes to establish smart manufacturing in the country. He tells us about how cutting-edge smart technologies and the Internet of Things (IoT) can together create the ground for the latest wave of technology which will connect man and machine globally.

MA: This is the age of connected devices. The numbers being predicted for the future are astronomical. What challenges do CIOs face as they try to weave in the new technology not only at the city but also at the national level?

SC: The important problem within a company is how to reduce the entropy, by which I mean the number of various elements required such as the machines, software, vendors, etc. We are all the time exposed to a lot of technology. Most of the CIOs are worried that there is no single platform which can stitch everything together. This means that they all have to rely on vendors for small parts of a solution. If they have outsourced their IT to one master integrator who can integrate but don’t have an internal IT team which can stitch together elements from multiple sources, then they will have a problem with the proliferation of technologies that are required today.

Technology today is for both how you interface with industrial machines and how you communicate with the devices back to the central server or an intranet or the internet. What is also important is how you analyze the data and integrate everything together for meaningful insights. So, the skills required are on the electronics side such as Electronic Communication Technology, backend data management of these devices and the data that is coming from the devices. Finally, we have the analytics. So there are five skills required. Sometimes, companies find it difficult to understand the depth that is required.

MA: How can IoT be utilized by the manufacturing sector?

SC: It is already being utilized across the entire world in the manufacturing sector in a very big way. What we call IoT today was always available to the manufacturing sector in terms of machines which used to control machines by being a logic controller. All of these were on the intranet or a dedicated network. What is happening now is that this intranet or dedicated technology is becoming more open and is available through the internet. Essentially, now we can have centralized control over a much wider variety of machines and we are able to bring the data back.

The other problem that the manufacturing sector faced in the past was that the data was not available at a centralized location for analytics. It was available in the machine but it was not being able to be integrated. That is where IoT comes in. Now, I can pull the data from processes in the manufacturing sector on to a centralized server, bring data from non-process parameters as well as find meaning in the analytics and take corrective action. We can also bring data back from humans who are operating the machines, including what is happening to the machine itself. This is an integration of human Intelligence and machine intelligence. This is where I see a lot of potential of IoT coming in and doing a lot of benefit to the manufacturing sector. That is what we do at GAIA.

MA: What potential use cases of IoT devices do you see in the manufacturing sector?

SC: IoT devices are able to integrate multiple sensors and bring the data back to a centralized location, either on the internet or the intranet. If we take this as the primary purpose, then IoT devices should be able to connect multiple sensors or to have a very complicated sensor array to bring the data back. We can have them in machines to look at power consumption, energy, vibrations and come up with predictive models. A machine always gives a lot of indications before it breaks down. IoT devices are being used to monitor the health of machines in the manufacturing sector. They are also being used to look at the throughput of the machines and measure the productivity of humans operating the machines. So, there are multiple use cases of IoT devices in the manufacturing sector. There is a logistics part also. IoT devices are also being used to track raw material or finished goods inventory or the assets in the factory itself.

MA: How can Industrial IoT become a truly transformative force for the manufacturing sector and help improve quality, safety and productivity in the industry?

SC: Quality is all about measurements, finding defects and corrective actions undertaken to make sure that a completely perfect product goes out into the market. In the manufacturing sector, we need to look at visual analytics, auditory on vibration analytics,\ and surface dynamics in terms of manufacturing tolerances. All of these are today possible using multiple technologies, both audio visual as well as measurement technologies to capture every product going out. Earlier, quality was being measured using sampling but IoT enables a sampling of 100%. If you look at the quality processes, they check every third or the fifth product. Now, they can check every product. It used to take a lot of time to do the analytics of quality. Now we are able to do analytics of quality faster because the machines have captured the data and sent it back to a centralized cloud environment, which allows us to process.

People are doing quality checks as well. If you are able to capture the information that people are giving for quality checks and bring it back and tag it to what is being produced, who produced it and do all kinds of correlations, immediately you are able to take a faster turnaround time. You will instead be doing the analytics then and there rather than finding it out after a month or two, as used to happen before. IoT allows a faster turnaround time for corrective actions.

Let’s look at safety. This begins with tracking the people and workforce: whether they are in safe zones or in hazardous zones. Today, it is not possible to track a lot of people, but IoT has enabled us to track people in zones as well as track the health parameters of critical workers employed in such zones. We are able to measure a lot of parameters that enable the management to better identify troubled spots. Earlier, it was done on paper and used to take a lot of analysis. With real-time data, analysis of troubled spots happens much faster.

Productivity is the most useful part of IoT. Productivity is all about doing the same thing faster and producing more with the same resources. We are improving machine productivity by reducing downtimes using IoT. We are improving people productivity by giving them information so that they can react faster to failures in the field or are able to take predictive action before the failure happens in the process. Measuring somebody’s productivity also helps you set targets for others as well as the ways and means to improve it. IoT allows continuous measurement of productivity of workers and machines. Both are assets of the company. We need to ensure that we are working within the tolerances of those assets. People have a tolerance and we are able to monitor the tolerance in real-time. Earlier, we could only monitor the tolerance after a catastrophe has happened. We are, therefore, able to reduce the downtimes and thereby increase productivity. Thus, IoT allows us to make improvements in productivity.

MA: What is your vision of smart manufacturing for the future?

SC: Smart manufacturing is being looked at by people who want to improve the productivity, safety, health, etc. of industries. IoT helps you keep track at every turn: amount of material, products produced, etc. Such information in a real-time mode gives access to better turnaround. Second is the effort to completely automate manufacturing. That is where robotics comes into the picture. This involves a host of other technologies such as artificial intelligence, IoT, machine vision, etc. A lot of people are working in this field and I see it growing. Robots can do the work of several people and more efficiently. There can be simple robots or complex ones. There are also those which assist human beings in carrying out jobs at a much larger scale. For example, you allow a person to lift a much higher weight. These are the kinds of things that I see happening in manufacturing.

MA: Is India ready for a smart manufacturing revolution, infrastructure-wise?

SC: We are trying to increase manufacturing in India with the Make in India initiative. India is ready for newer plants, which are fully instrumented. If you go to the Ford plant in Chennai, you will find that only 700 people produce more vehicles than some of the other production houses produce in a whole month. It is a phenomenally different kind of plant. India is already doing smart manufacturing in the newer plants. The question now is how do you bring efficiency in the older plants? How do they produce faster and better? How to instrument them and bring them in tune with the times? The opportunity is there. I see a lot of interest in CIOs and COOs and plant managers who are asking for all kinds of solutions. We have solutions for many of these problems. However, one needs to look at each plant, each company and its strategy separately. And you need to come up with a set of methods to bring in automation.

For smart manufacturing to take place in India, we need to start with a strategy which allows multiple types of technologies to be used and integrated. CIOs need to bring in people who understand the area of smart manufacturing and can help with automation. IoT is a combination of operational technologies and information technology. And when the two meet, there are certain types of people who understand the correlation between the two. This is an important aspect. I think India is quite well poised to exploit smart manufacturing.

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