About The Speaker:-
Mr.Vijay Gunti conducted this session on “Smart Manufacturing”. He has 10+ years of experience in the field of smart and digital transformations. He has successfully completed certification in Energy innovation and Emerging Technologies.
His broad areas of expertise include Product and services, program management and Consulting. Mr. Vijay Gunti is an astute professional and thought leader with proven success in the areas of Digital, Enterprise Service Transformation i.e., IoT, IIoT, Big Data, ML, DL,AI.
He is an eloquent speaker, author, podcaster, blogger, at multiple forums,Tech Talks,Chapters and conferences &has written blogs on various Digital Transformation approaches and technology innovations in the areas of IoT, IIoT, Industry 4.0,Big Data, ML, DL,AI, Cognitive, AR, VR, 3D Blockchain, DevOps etc.
What Is Smart Manufacturing:-
Technology-driven smart manufacturing involves monitoring production processes with Internet-connected machinery, and the goal is to identify opportunities for automation and to use data analytics to improve performance.The term "smart manufacturing" refers to fully integrated, collaborative manufacturing systems that react in real time to changing demands and conditions in the smart factory, the supply network, and customer requirements.
Importance Of Smart Manufacturing?
Currently, smart manufacturing is highly beneficial and crucial across a range of industries and sectors. Following are the significant benefits of smart manufacturing:
1. Automated Data
- Managers can measure key performance indicators more efficiently and accurately with smart manufacturing.
2. Predictive Maintenance
- Maintenance issues can be predicted and resolved faster and more efficiently by smart factory managers.
- Predictive maintenance aims to reduce costly, unexpected breakdowns by allowing manufacturers to arrange maintenance around their own production schedule.
3. Significant Cost Reductions
- With proper demand management, forecast accuracy increases and waste is reduced, helping reduce costs.
1. It gives managers seamless insight into machine maintenance, bottlenecks, and inefficiencies, which helps them increase productivity.
2. Smart manufacturing techniques give you more data access across your whole supply chain.
3. Real-time data describes what the manufacturer need and when it is required, allowing suppliers to make quick changes to orders.
4. They only provide what is required, not more or less, resulting in less waste and downtime due to missing parts.
Innovation and Higher Quality Products:
1. It gives managers seamless insight into machine maintenance, bottlenecks, and inefficiencies, which helps them increase productivity.
2. When productivity is increased, money is saved, which can then be used to develop new products.
3. Smart manufacturing data, once examined, reveals where customers' demands are, allowing managers to identify potential for new goods or higher-quality reimagined products.
1. All manufacturers may reduce their carbon footprint by decreasing waste, but energy-intensive industries stand to benefit the most in terms of energy savings, which will not only reduce energy waste but also lower product prices.
2. Smart manufacturing projects must be pursued by manufacturers of all sizes to stay competitive.
3. The leadership of a company must embrace smart manufacturing. The first stage is to invest in equipment with the goal of integrating smart manufacturing apps.
4. These improvements will enhance the process, save money, and boost sales over time
How Data Is Driven?
Data will inform us "what to do" and "when to do it," which is at the heart of smart manufacturing. Because smart factories are based on data, cyber security will play a critical role in the smart manufacturing ecosystem. When adopting these enablers, data security is a major concern. All the stakeholders of smart manufacturing may be characterized typically in three types of companies which can broadly be called “product and control solution providers,” “IT solution providers or enablers,” and “connectivity solution providers.”
Product and control solution providers:
- It includes all the companies involved in the development of automation products and services.
IT solution providers or enablers:
- Powers the whole concept of IIoT and asset management and through this they help in building control, monitoring and analytics infrastructures effectively.
Connectivity solution providers:
- They are telecom service providers that facilitate the smooth flow of data for asset management
The Implementation of IIOT:-
1. Industrial internet of things (IIoT) is nothing but an ecosystem where every device, machine and/or process is connected through data communication systems. Each machine and piece of industrial equipment is embedded or connected with sensors which typically generate the relevant data. This is further transferred to the cloud/software systems through data communication systems. This huge amount of data has lots of insight which if analyzed may help in identifying certain dark areas within the production process. After the analysis of the data, it is sent as feedback to the production systems for any corrective action.
2. There is huge potential for IIoT in smart manufacturing. You cannot increase production beyond certain limits, so what do you do to increase your profits? You can’t increase production because there is no demand for that. So, you try to look at the backend process and make it efficient. Now this is possible only when you have the precise details about your production process. This is where IIoT comes into the picture. Sensor generating data can be implemented at each process of production so that you can get the data, analyze it and take corrective action to increase the efficiency, thus increasing profitability.
3. However, it is not so easy to implement IIoT in current and/or old organizations, but you can implement it in newly established manufacturing facilities. This is because results can only be achieved if the implementation of smart manufacturing concept is there right from the start of design process for a manufacturing facility.
4. Smart manufacturing is not widely implemented; however, it’s there in bits and pieces in some organizations. You can’t change the basic design of machines or a factory system to implement all those sensors and other related technology. This makes the implementation of IoT in current or old manufacturing facility a bit difficult and in some cases impossible.
5. Major forces driving IoT in manufacturing market are the growing need for centralized monitoring and predictive maintenance of manufacturing infrastructure. The increasing need for agile production, operational efficiency, and control, and demand-driven supply chain and connected logistics are also expected to drive the market.
The Rise of Artificial Intelligence in Manufacturing:-
1. The concept of artificial intelligence is old, but it is now finding applications in manufacturing ecosystems. In the last 5-6 years, there has been a tremendous increase in interest and investment regarding AI in manufacturing. This is mainly due to a few reasons, as AI will work only if the data is available, and it has only recently been possible to build the needed capability to:
- Generate huge amount of data with low-cost sensors
- Store data in low-cost systems
- Process data at affordable rates
2. These have collectively made it possible for AI to be implemented in manufacturing shop floors. Earlier manufacturing was being done by low-cost countries where it is very difficult to justify the high cost of implementation of AI in their manufacturing ecosystems. But due to a rise in wages, now it is possible to implement AI even in countries such as China, which is considered the factory of everything. China is now making a significant number of investments in artificial intelligence especially for manufacturing and other related applications.
3. The growing usage big data technology, industrial IoT in manufacturing, extensive usage of robotics in manufacturing, computer vision technology in manufacturing, cross-industry partnerships and collaborations, and significant increase in venture capital investments will propel the growth of the AI in manufacturing market.
The Future of Blockchain in Manufacturing:-
1. Blockchain in manufacturing is still at a very nascent stage; however, it is a much-discussed new technology in manufacturing ecosystems. Currently, it is being implemented in financial systems, but companies are exploring its application in manufacturing.
2. Looking at the capabilities of blockchain, aviation, food & beverage, and medical are some of the industries which could greatly benefit from this technology. These industries, due to some stringent rules and regulations, require full scrutiny of all their suppliers across the value chain. Blockchain could help in maintaining quality control right from the development of raw materials. Currently, most of the attention is on the development of blockchain for supply chain function across the manufacturing ecosystems.
3. Some of the industries that are actively developing blockchain include apparel, solar energy, mining, fishing, food & beverage, shipping (cargo transportation), fertilizer, healthcare, and aviation. The list is not exhaustive, and as the technology matures, more and more industries may get involved in implementing blockchain. Companies such as IBM, Microsoft, GE, Samsung, and Moog are involved in developing and implementing the blockchain in manufacturing ecosystems.
4. The blockchain market in manufacturing has yet to conceptualize fully, and thus we are expecting the market to start generating significant revenue from 2020 onwards. However, many organizations have already started investing and exploring the benefit from blockchain technology in manufacturing ecosystems.
The Importance of Industrial Robotics:-
1. The next thing that makes a typical manufacturing plant a smart manufacturing facility is the implementation of industrial robots. Industrial robots is not a new concept, it has been in the systems for the last 40-50 years. The only thing that has changed with respect to industrial robots is that they have now become intelligent. Earlier the robots were programmed to do one single task at a time. If you want to do other type of tasks, then you must change the codes.
2. Now robots are well connected with the sensor network implemented within the manufacturing shop floor, and they get the data from sensors and change their action accordingly. Artificial intelligence is also being slowly implemented in robotics systems, and thus it makes systems autonomous. Through AI, robotics systems are expected to change their actions according to the situation on a real-time basis.
3. Currently, most industrial robots are implemented in the Asia-Pacific region. Industrial robots play a major role in the automotive industry. Government initiative is considered as one of the important drivers for the development and growth of robotics. The US and China are actively providing all the necessary impetus to drive the demand for robotics further.
4. Apart from industrial robots, there is new type of robot which is rising and is called collaborative robots. These machines will work alongside humans to support all the work done by humans. For example, a collaborative robot can observe what a human operator at an assembly line is doing, learn the human’s task, and autonomously start performing that same task with the exact same kind of precision. Further, the development in collaborative robots has reached such an extent that it would be difficult to differentiate it from industrial robots with regards to its application. Now, collaborative robots that were supposed to do only light work are now capable enough to complete heavier jobs which were generally done only by industrial robots.
The Benefits of Digital Twins:-
1. Digital twin is another concept in the ecosystems of smart manufacturing. It creates the virtual model of an asset, process, or system by using the data obtained from sensors in the systems or asset and algorithms for making reasonable projections about the process. Predictive maintenance is one of the important systems which will use digital twins. The benefits of digital twins include potential reduction in time and cost of product development and elimination of unplanned downtime. The rising adoption of IoT and cloud platforms, and 3D printing and 3D simulation software are boosting the adoption of digital twin.
2. Aerospace & defense, automotive & transportation, electronics & electrical/machine manufacturing, and energy & utility are the major adopter of digital twins. Once the concept of digital twins develops and matures, then we may see its increasing application in non-manufacturing sectors such as retail & the consumer goods market.
How SM differs from traditional approaches:-
1. Traditional manufacturing methods, developed during the age of mass production, focus on economy of scale and machine utilization. The thinking was that if a machine was idle, it was losing money, so companies kept them running continuously.
2. Now To achieve customer satisfaction, traditional manufacturing companies keep large inventories on hand so they can fulfill potential orders. Consequently, these companies must keep their machines running with specific setups for as long as they can to reduce the costs of making the parts.
3. This is known as batch-and-queue processing – a mass production approach to operations where the parts are processed and moved to the next process, whether they're needed or not, and wait in a line (queue).
4. However, this approach isn't very efficient for several reasons, including:A longer machine set-up time means more lost production time because nothing isproduced while a machine is down.The quality of the product suffers because if parts in a batch aren't made correctly, no one will likely notice the problem until the next operation. This means the work must be done again, which is expensive and ties up valuable resources.
5. Smart manufacturing, on the other hand, is a collaborative, fully integrated manufacturing system that responds in real-time to meet changing the conditions and demands in the factory, in the supply network, and in the needs of the customers.
6. The goal of smart manufacturing is to optimize the manufacturing process using a technology-driven approach that utilizes Internet-connected machinery to monitor the production process. Smart manufacturing enables organizations to identify opportunities for automating operations and use data analytics to improve manufacturing performance.
Pros and cons of smart manufacturing:-
1. Smart manufacturing offers several benefits, including improved efficiency, increased productivity and long-term cost savings. In a smart factory, productivity is continuously enhanced. If a machine is slowing down production, for example, the data will highlight it, and the artificial intelligence systems will work to resolve the issue. These extremely adaptable systems enable greater flexibility.
2. In terms of efficiency, one of the main savings comes from the reduction in production downtime. Modern machines are often equipped with remote sensors and diagnostics to alert operators to problems as they happen. Predictive AI technology can highlight problems before they occur and take steps to mitigate the financial costs. A well-designed smart factory includes automation as well as human-machine collaboration, features that enable operational efficiency.
3. A big downside to smart manufacturing is the upfront cost of implementation. As such, many small to midsize companies won't be able to afford the considerable expense of the technology, particularly if they adopt a short-term philosophy.
4. However, since savings over the long term will outweigh the startup costs, organizations must plan even if they can't implement smart factories immediately.
Above report is written by Mr.Rohit Kokitkarthe first-year student of Operations & Supply Chain Management department of ITM Business School, Kharghar, Navi Mumbai.