Introduction
The industrial revolution began to take shape in the mid-18th century. Since then, people have witnessed numerous technological advancements that have transformed the world. The first revolution brought innovations such as mechanical looms. In the second phase, electrically powered mass production took prominence. The third phase revolutionized the manufacturing industry with the help of electronics and IT. Now, we are in the fourth phase of the industrial revolution. In the fourth phase, we are harnessing the power of data. Enterprises nowadays are implementing smart manufacturing techniques to restructure the competitive market. In this article, we explore the concept of smart manufacturing, the components of smart manufacturing, smart factories, the significance of data in smart manufacturing, the advantages and disadvantages of smart manufacturing.
What is smart manufacturing?
Smart manufacturing is a technology-driven mechanism that utilizes the internet for connecting multiple devices and machinery for the production process. It combines different technologies (computation power, sensors with inputs, always-on connectivity, AI, and excellent data analytics) and solutions to harness the best out of a manufacturing ecosystem. All these technological solutions, when used together, unlock new possibilities to stimulate development, reduce waste, and boost supply chain transparency.
People call smart manufacturing a technology "enabler" because it optimizes the manufacturing process to increase the overall revenue. All these bring us to another new term, the Industrial Internet of Things (IIoT). IIoT comprises input devices and sensors to track logistics, environment monitoring systems, cameras, collaborative robots (cobots), etc. It optimizes the overall manufacturing process. According to some reports, by 2025, around 60% of industrial enterprises will start implementing smart manufacturing and IIoT.
Smart manufacturing comprises the following components:
- Smart logistics and supply chain.
- A smart workplace that comprises cobots, robotic arms, and other IoT-based automation systems.
- IIoT (used for handling automated diagnostics).
- Mass production with the help of accurate data analysis.
- Remote asset and production monitoring.
Why implement smart manufacturing?
We are in an industrial era wherein the demands of each industry are increasing at an unparalleled pace. That is why big companies and large manufacturers are switching from traditional manufacturing methods to smart manufacturing methods. The era of robotization and automation demands collaborative robots to work together with humans so that manufacturing industries can address the hurdles of complexity, compliance, global marketing, customization, and consumer expectations without compromising quality. It is essential to adopt smart manufacturing mechanisms to make the manufacturing processes swift and productive.
By analyzing the spectrum of smart technology, you will find that the technologies used in various industries are getting more intelligent because of the advanced AI algorithms (machine learning and deep learning). These technologies are constantly evolving according to our expectations, needs, and behaviours to assist us in a better way. Smart manufacturing has also brought technology-assisted robot arms to cooperate and collaborate with human workers smartly and safely. All these collaborative robots (cobots) have become a vital part of the manufacturing industry.
Industries use robotic arms and cobots because they are incredibly flexible and easy to use, reprogram, and are easily movable across the production facilities. We can easily append more functionalities and programs in robots and cobots to enhance their performances. These days, firms build smart factories based on these latest manufacturing techniques. In fact, in 2017, 76% of manufacturers reported that they use smart factories for manufacturing.
What is the smart manufacturing process?
The smart manufacturing process leverages the system in which the internet, various devices, sensors, etc., are connected to manufacture a product with absolute efficiency. All the machines and other industrial elements have sensors that generate relevant data. These devices then transfer the data to the cloud or another software for further analysis. Industries collect large amounts of such data for getting helpful information about the industrial processes. This information is used for training robotic arms and detecting flaws in the production processes.
The functioning of cobots significantly depends on the quality of communication. Making the collaborative robots work in sync, good-quality signalling, large bandwidth, low latency, and agile decision-making abilities are required. They make the manufacturing process efficient. Though the concept of artificial intelligence is old, manufacturing ecosystems are now integrating AI with industrial machinery to execute manufacturing procedures at a rapid rate. Factories and manufacturing industries leverage AI-based systems and cobots to make perception-based decisions. Most manufacturing units are shifting their production paradigm to smart manufacturing.
Industrial robots are not new to the manufacturing sector. They have been in the industry for the last 40 years. Now, they have become more intelligent. Artificial Intelligence, in conjunction with robotic arms and other collaborative robots, can enhance automation in manufacturing. Robots and automation reduce time-to-market by up to 60% and reduce developmental costs by around 25%. It also empowers companies to produce top-quality products.
How collected data drives smart manufacturing?
Smart manufacturing uses collected data and acts accordingly. Manufacturing companies use the data extracted from the sensors, logistics monitoring systems, collaborative robots, cameras, and other IIoT equipment to make vital decisions. Smart factories and manufacturing units primarily utilize data that revolves around cybersecurity, market trends, and supply chain demands. This data also helps in teaching machines how to work and making them more intelligent. There are three major stakeholders involved in smart manufacturing:
- IT solution providers leverage the concept of IIoT and asset management through data analytics. They assist manufacturers by providing useful software to manage and monitor the production processes. Some well-known IT solution providers include SAS, HP, Microsoft, and Intel.
- Product and control solution providers deal with the construction of the products and services involved in smart manufacturing. Some well-known firms providing product solutions are Honeywell, ABB, Siemens, and Schneider.
- Connectivity solution providers are responsible for ensuring a sleek flow of data across different machines. Some firms that provide connectivity solutions are Cisco, Jio, Huawei, and AT&T.
Data-driven manufacturing helps manufacturers make significant decisions based on the data accumulated from different industrial sensors and statistical analysis. Firms and industries use this data to cut costs and implement new-age sales techniques and production procedures. Hence, we can say that data-driven manufacturing is the next wave of manufacturing that can smartly drive responsive production units and significantly increase their efficiency.
Advantages of smart manufacturing
Smart manufacturing is the key driver of the fourth industrial revolution. It utilizes effective technologies like cloud computing (for storing the bulk amount of data and performing other computations), sensors, IoT devices for remotely handling different equipment, and data analytics for efficient performance. There are several benefits that smart manufacturing provides to industries. Some of them are:
- Better management: Technologies like AI can generate a wide variety of helpful insights. Manufacturers can use these insights to understand market demands, detect flaws in the production processes and develop better strategies. Smart manufacturing also allows better management of all the processes involved in the production by increasing transparency.
- Increases efficiency at a lower cost: The use of technology and data and collaborative robots allows manufacturers to visualize the supply chain demand, make better decisions, implement on-premise automation, and upgrade systems at a low cost. Also, it diminishes the inefficiencies in the production processes and reduces the time taken to complete the processes. It eventually minimizes wastage of resources and saves a considerable amount of capital in the long run.
- Energy efficiency: Most industries wish to minimize their carbon footprint by eliminating wastes and reducing the time taken for the production of each unit. Smart manufacturing allows industries to save energy and produce products at a more affordable cost. As the time taken for each process reduces, the amount of harmful waste generated from each production process decreases.
- Automation: Smart manufacturing enhances automation with acute smartness. Modern factories compete globally with their interconnected, highly effective, data-enabled automated systems. This interconnectedness can generate more data for getting helpful insights. Innovative manufacturing processes automate calculations and general functions. These automated systems can make prompt decisions with the available data, speeding up the production processes.
Disadvantages of smart manufacturing
- Greater initial cost: Manufacturers are fascinated by the cost-reduction benefits that smart manufacturing brings into a manufacturing facility. In the long run, there is a significant cost reduction. But the initial cost associated with the setup of such an advanced manufacturing system is very high. For this reason, many manufacturing owners refuse to implement it.
- Limited creativity: Smart manufacturing and technology-based implementation restrict creativity due to the profusion of automation, collaborative robots, and machines. The inclusion of automation and robots eventually reduces human workload, and hence employees become more dependent on devices than their intellect.
- Contribution to environmental issues: The cause of global warming is an international concern. Smart manufacturing can help eliminate wastes generated from the production processes. But if not implemented correctly, its mechanical operations can increase the release of heat and debris that cause massive damage to the environment.
Conclusion
Engineers and researchers are trying to make smart manufacturing an optimized cluster of tools that promise maximum efficiency at a low cost. Amid all the industrial advancements, manufacturing firms should start thinking about long-term survival. Smart manufacturing will continue to thrive because of its versatile operations, efficiency, automation, and data-driven approach.
Frequently Asked Questions
- What are the fundamental principles of a smart factory?
Some essential principles that drive a smart factory are:
- Detailed planning in real-time: Thorough planning of core processes and production is necessary for operational efficiency. A smart factory demands functionalities to facilitate precise planning in real-time.
- Modularity: A smart factory should be easy to assemble and disassemble. It should allow easy recombination of system components as per requirement. It will ultimately help reallocate and rearrange different parts with a minimum effort and in less time.
- Interoperability: A smart factory needs interoperability where each component and equipment can share data across the connected devices. Such a collaborative system can bring synchronization and help to carry out efficient manufacturing.
2. What are the characteristics of a smart manufacturing process?
Some prominent features of a smart manufacturing process are:
- Distributed Intelligence: Automated systems within the manufacturing premise should perform their tasks independently.
- Innovative equipment: A smart manufacturing ecosystem contains equipment that can be integrated and configured easily.
- Management: A smart manufacturing premise has a centralized digital life-cycle management driven by data and statistical analysis.
