Communications & Networks
Industry 4.0 & Smart Manufacturing
Q&A with Bassam Zarkout on IIoT solutions and their role in the manufacturing space
November 25, 2022 by Sukanya Ray Ghosh
The Canadian manufacturing industry is facing unprecedented challenges. IIoT solutions can prove to be of great help in speeding up the recovery process and equipping manufacturers with the tools to grow further.
In a recent episode of MA’s podcast Machine Language, Bassam Zarkout, chair of the digital transformation working group at the Industry IoT Consortium discusses how IIoT solutions can help Canadian manufacturers stay competitive even in trying times.
An edited transcript is below. Listen to the full conversation here.
Manufacturing AUTOMATION: What does the Industry IoT Consortium do? What is your role at Industry IOT Consortium?
Bassam Zarkout: The IIC or industry IoT consortium is a Boston-based consortium of IoT technology providers and practitioners. It is a global consortium with member organizations from the US, Canada, Germany, Japan, Korea, China, and so on. It is focused on defining solutions and accelerating the adoption of IoT solutions in industry in general and in manufacturing in particular.
Within the IIC, I’m an independent consultant. I focus on IoT strategies and AI strategies for enterprises. I am Ottawa-based as well. At the IIC, I chair the digital transformation working group. And I was also the chief editor of the industrial AI framework. I’m also active in security and trustworthiness and digital twins subjects as well.
MA: The Canadian manufacturing industry has just been through the onslaught of a global pandemic. Currently, the demand for goods is increasing and an ongoing worker shortage is making it difficult to keep up. Any thoughts on this?
BZ: The impact has affected everybody, all manufacturers. Rhere are problems with the supply chains. There are problems with demand prediction. So, on the supply chain side, organizations are looking closely at implementing technologies to optimize it. They say that supply chains have three things, flow of goods, money and data, and data is the most difficult part. The manufacturers are on the receiving end of the supply chain problem. So, they need to be integrated with the supply chain infrastructure that’s being implemented globally. On demand prediction, they need to apply analytics and AI to predict demand and plan accordingly. They need to implement technologies to help them scale down and deal with elastic demand so that they can act operate profitably at low capacity as well as high capacity. And once they deal with these issues, they need to look at a more strategic perspective which is digital transformation. They need to have a multiyear horizon, understand the pressures in the market and digitize, digitalize and transform their factory operations to deal with future fluctuation.
MA: Given the current context, how can IIoT solutions help manufacturers speed up their recovery journey? What would you tell the manufacturers who are maybe thinking about adopting these solutions?
BZ: IIoT solutions will help in the recovery process by giving manufacturers a better vision into their operation so that they can track the condition of their equipment. They can do predictive maintenance, they can eliminate headwinds in their operation. IIoT solutions along with other types of technologies, such as digital twins, artificial intelligence and blockchain can help organizations deal better with the [impact of the] pandemic. Obviously, every manufacturer has a unique situation and they need to select the solutions based on their needs and requirements.
MA: What are the different IIoT solutions available to manufacturers today?
BZ: A typical solution is quality inspection for produced goods. So, you want to be able to inspect and monitor the quality of the produced goods. For example, Toshiba has a steel manufacturing inspection solution that captures images of produced steel and sends it back to Toshiba for analysis with AI and grade the steel that’s being produced. So, a quality inspection of produced goods is very important. The other one is implementing solutions for predictive and preventive maintenance. Unplanned shutdowns are perhaps the most expensive and the most damaging to the financial health of an organization. For demand prediction, you need to have a good idea about upcoming demand in the marketplace and adjust your supply chain and production capacity to deal with the situation. And real assets condition monitoring systems, you need to have monitoring of your core pieces of equipment. Again, that becomes part of the predictive maintenance. We talked about supply chain production line optimization. There are techniques now, automation tools and IIoT capabilities that can help automate the production capacity. All of this will also contribute to the reduction of line changeover time well.
MA: In the era of connected factories, how do the IIoT solutions help contribute to the bottom line for manufacturers?
BZ: All these solutions will lead to significant benefits to the bottom line of the organization, by implementing technologies that allow you to address the headwinds, by reducing unplanned shutdowns, by optimizing production, by improving safety, by adapting to rising and lowering demands and so on and so forth. All of these solutions will directly benefit the bottom line of the organization and will have indirect benefits as well. Improving safety has an indirect benefit as well.
MA: Rising demand is keeping manufacturers very busy today. How essential is it to optimize workflows in this situation?
BZ: By workflow you referring to the core processes in the organization. Optimizing the code workflows that are key to the bottom line of the organization is important. And we call this digitalization. Essentially manufacturing is still heavily “undigitized”. There is a lot of paper-based content that has to flow through the production line. So, one of the steps is to digitize that content and integrate it into the core process. And once you’ve done that, you can look at optimizing the core process. We call that digitalization. Once you’ve done that, you can integrate multiple core processes together. So, this acts as a building block. Eventually, you become a digital factory.
MA: Training is an essential aspect of keeping the manufacturing workforce up to date on all the advanced technologies. Do IIoT solutions help in reducing the training time for new operators?
BZ: We should not only look at training as training on technology. If you are transforming the factory into a digital factory and ultimately into a smart factory, there is training required at multiple levels. How to cooperate and work closely with automated autonomous robots, for example. That requires training. How to train your workforce and upskill them to deal with the changed and optimized production environments. So, this is not only about training on particular technology. It touches on a general strategy for upskilling the workforce and dealing with a higher level of automation that is going to be implemented and how you can take best advantage of that.
MA: Predictive maintenance on equipment is crucial in cutting down repair costs, which can be very expensive later. How do IIoT solutions help?
BZ: Well, IIoT solutions will allow you to have a more connected view of the condition of the equipment. Through sensors you are capturing operational data about that piece of equipment such as temperature, speed, vibration level, and so on and so forth. And all of this data is analyzed and compared with steady state data or data that corresponds to a healthy piece of equipment. You can derive from that indications about future issues and you can schedule maintenance during these scheduled maintenance windows. So, this is a very important application in manufacturing and it’s a no-brainer.
MA: Real-time asset monitoring is another tool for manufacturers. How does it help them?
BZ: With real time asset monitoring, you’re monitoring the operational conditions of the equipment. You’re tracking the location of the equipment, because that equipment may be mobile. It maybe a tool that is misplaced somewhere within the factory. There are factories that are equipping every major tool in the hands of the worker with sensors, even screwdrivers, for example. All of this will help you have a much better view of the condition of your equipment, especially if you combine the IoT implementation with a digital twin implementation. The digital twin will allow you to almost simulate and visualize in a digital way the operation of your factory and you can visualize things and anticipate things in a much better way.
MA: The entire connected factory, digital factory helps optimize the processes. How does it help in reducing manufacturing line-changeover time? And what is the significance of doing this?
BZ: Obviously, it is important to reduce the line changeover time in a factory production line. And efforts to digitize and digitalize the process go a long way towards being able to very quickly reconfigure the production line for a new batch based on new configuration requirements. So, digitization and digitalization are critical here. Ultimately, if you digitalize all your core processes, you’re going to have a digital factory. And if you include AI and analytics throughout the production and operation of the factory, you end up with a smart digital factory. So, the fast line changeover times will be by-products of this.
MA: For manufacturers thinking about embarking on their digital transformation journey, where do you think they should begin?
BZ: First of all, digital transformation is not about implementing a piece of technology. You need to assess your requirements and situation and understand why you need to transform, what needs to be transformed, why do I need to transform now, what’s the level of urgency, who are the stakeholders, what are the requirements for ROI and what are the requirements for the outputs.
There is an assessment that you need to go through to understand all of these. There has to also be an executive sponsor who will own and mandate and drive the transformation requirements. And there has to be a program set up led by a senior person who will receive instructions from the executive sponsor and will execute the project. Underlying all of this is a need to clearly understand the IT/OT divide.
When you have IIoT systems you have a new situation that maybe organizations have not faced before. You have technology now on the operational side and you have technology on the business side. Those need to converge and integrate and talk to each other. So that’s the assessment.
Once you have clarity about that, you go into the definition of the business strategy – think big, start small. After that, you start assessing technologies, defining the contexts and what technologies [you need] – IoT AI, digital twins, etc. All of that leads to the definition of the program for digital transformation. Then the journey can start. This doesn’t have to take a lot of time. But it’s important to have clarity about all these things before you start working.
MA: Manufacturers often face obstacles when they begin their digital transformation journey. What are the common obstacles they should expect and how should they tackle this?
BZ: The obstacles, McKinsey calls them headwinds. You have organizational headwinds, you have cultural headwinds. The organization itself may not be structured to take advantage of the transformation. The differences in culture between IT and OT is important to address. You have the costs and the ROI headwinds. These projects need to have clear ROI guidelines. You also have headwinds related to “brownfield situation.” In most cases you have brownfield implementations and you need to make sure that you understand the difficulties of dealing with brownfield systems in the transformation context. And you have to define success. What does success look like? How do I measure it? How do I track it? What are the KPIs and so on so forth.
MA: How does IIC help manufacturers with their digital transformation journeys?
BZ: In the digital transformation working group, we are working on a digital transformation framework. And that framework acts like “Google Maps” that describes the lay of the land for an organization thinking about undergoing digital transformation in an industrial context. It doesn’t necessarily give you a specific roadmap because every manufacturer is going to be different. But it highlights the important issues and considerations and how to deal with them and points to other documents within the IIC community and beyond about how to use that.
We also have another line of activity. We call them digital transformation enablers. These are focused more downstream of the digital transformation framework. They take a particular technology and dive a little bit deeper into the issues involved in implementing them in an industrial context and how this technology can help enable digital transformation. These are some examples.
That are also detailed frameworks about specific technologies – artificial intelligence, digital twins, etc. And there are many consultants within the IIC community who can help manufacturers with this very rich library of content and expertise.
MA: When you think about digital transformation, cybersecurity is an aspect that has to be considered. It is a crucial part of the conversation.
BZ: Well, it’s amazing that we haven’t mentioned cybersecurity yet, because it’s a very critical requirement. Obviously, with ransomware attacks can impact and create significant damage within a manufacturing organization. It’s an active subject in the IIC. We take a holistic view at security as part of a wider concept that we call trustworthiness. And in trustworthiness, we include on the IT side security and privacy. And on the operational technology side, we include safety, reliability and resilience. We try to understand the relationship between these characteristics because you cannot simply think of security and only security. You have to think about security within the context of safety, reliability and resilience.
For example, the security team cannot stop production because they want to apply a security patch on the systems. It’s not their decision. They will not be allowed to do that because it can impact safety. I’ll give an example – the Colonial Pipeline attack that took place in 2021. There was a ransomware attack on the business side, on the IT side of Colonial Pipeline. It was not a very significant attack. But the CIO reached out to his counterpart on the OT side and they were worried that this may have been a decoy; that the real attack was on the operational technology side. And that would have had a very, very significant impact. So, they disconnected the two environments because they were collecting production data for billing purposes. They disconnected the two environments just to do a general inspection. And that disconnection was enough to cause long lineups at gas stations in Florida. So, this highlighted the need for industries to pay very close attention to cybersecurity.
Another point that is very related to the news we hear today about Ukraine. There is a discussion now in the insurance space, whether a cyberattack on an infrastructure is an act of war, because according to the U.S. military doctrine, it is an “act of war”. And if it is an “act of war” should insurance companies pay or is it covered by the “act of war” clauses in the insurance contract. Now, think of this at the understanding of a manufacturing facility where you have very significant capital-intensive equipment at stake. So, these are not trivial matters and they need to be addressed very, very carefully.
MA: Is scalability an important factor to consider for manufacturers implementing IIOT solutions?
BZ: Scalability is part of a wider context of architecture. Scalability, obviously, is important. With the exception of video-feed in IIoT environments, IIoT doesn’t necessarily involve huge amount of data. But increasingly because more and more audio and video content is part of the IoT data set, the volumes are increasing.
You also have other things. Latency is much more critical in IoT than it is in IT. It is measured in milliseconds, not in seconds or minutes or days. Temporal correlation is very important because you may want to be capturing data from multiple sensors. The sequence of capturing this data and when you capture this data is important. You need to decide where you do your analytics and AI. You can do them at the edge. You can do them in cloud. You can do them in your data centre. All of these carry different weights in terms of performance, in terms of cost, in terms of latency and so on. So, it is not only about scalability. And we should not try to reinvent IT best practices for IoT. We should adapt, we should start with IT best practices which are well established and see how they can be applied to the IoT space.
MA: Data is one of the most powerful assets a manufacturer can have. How should they connect their requirement for data that they need the most to the IIOT solutions that they are implementing?
BZ: You need to take the position that this is not about systems and infrastructure only. Data is the most critical piece in all this. And you need to understand what data are you dealing with in your IoT infrastructure. Well, you have supply chain data. You have production data. You have equipment configuration data. You have equipment condition data. And you have parts data – the parts that are being used to build the products that you have. So, you need to understand the scope of data that you have and deal with their requirements from traceability, provenance, scale [perspective]. So, there has to be a data architecture design for the overall factory. And a clear understanding of these different types of data in terms of volume in qualitative, quantitative and the flow.
You need to look at data in motion, data at rest and data in use.
MA: Is there anything that you would like to add on this subject?
BZ: IoT is not a novelty anymore. More and more organizations. are realizing that they have more IoT systems within their infrastructure and they need to deal with them. You know, insurance companies have IoT systems, banks have IoT systems. So, there’s no magic about IoT. It’s a new animal that needs to be dealt with and understood. There are cultural differences that need to be addressed as well. And IoT is part of a wider range of several technologies that are finding their place in organizations – digital twins, artificial intelligence, blockchain, etc. All of these technologies, in addition to IoT are becoming very critical to manufacturing, as well as other types of organizations.