Know How Smart Manufacturing Enhances the Production through Various Technologies
Smart manufacturing means utilizing various technical aspects to enhance the yield of the industries. Some of the commonly used smart manufacturing technologies are industrial robotics, digital twins, internet of things (IoT), and blockchain. This system of manufacturing is preferred because of several merits like cost effectiveness, repairing defects, and predictive maintenance.
Many industries want to develop goods and provide top rated services to all the consumers in the market. Therefore, they are constantly on their toes to generate tangible manufacturing process. The smart manufacturing sector is one such field where the entire process is tracked by using high tech devices and software. The application of innovative technology has escalated the efficiency and saved the workforce from mundane manufacturing processes.
What is Smart Manufacturing?
This is a comprehensive subject because smart manufacturing deals with computers, technology, and certain technical devices that improve the productivity of goods and services. The technology used by the smart manufacturing sector cannot be directly implemented in the production process. However, this technology is used at stages where the process might go wrong and may require extra attention.
The technologies that are popular amongst the smart manufacturing sectors are as follows:
- Artificial Intelligence
- Internet of things (IoT)
- Blockchain
- Robotics
- Cyber security
The smart manufacturing sector creates and accepts accurate data; thus regulating decisions taken by the managers. These decisions shoot up the profits and improve optimization levels of the manufacturing sector.
The market dynamics of the smart manufacturing industry reveals several notable aspects. According to a report published by Research Dive, the global smart manufacturing sector will flourish with a CAGR of 6.4% by 2026.
How Digital Twins Influence the Production Unit?
This technology is known to create virtual model of the systems, assets, and manufacturing processes from the data generated by the sensors. The digital twins’ technology saves time, reduces production cost, and disposes unplanned downtime. This technology is extensively used in the aerospace and defense sector, automotive industry, electronics sector, and energy industry.
Apart from this, digital twins’ has managed to take the non-manufacturing sectors like consumer good market and retail under its wing. This technology is rising due to the usage of 3D printing, IoT, 3D simulation software, and cloud computing.
How Internet of Things (IoT) has helped the Manufacturing Units?
The entire manufacturing process along with the machines, equipment, and the software are connected with the data communication systems. This system comprises of sensors that generate data of the entire manufacturing unit. This data is later on sent to the cloud software from the data communication system. This data assists in repairing numerous harmful defects as it provides all the information related to the production process.
The IoT sensors are implemented at each and every production stage as this improves efficiency, enriches data analysis, and garner huge profits. The resourcefulness of the internet of things is witnessed in the design of fresh and newly built manufacturing plants. This ascertains quicker and better results of the production processes. On the other hand, the IoT technology remains ineffective for the old industries as the manufacturing units of such industries are difficult to change.
The driving forces for internet of things are centralized monitoring, predictive maintenance, manufacturing infrastructure, and operation efficiency. Apart from this, an increase in the demand and supply chain, improved logistics, and nimble production too makes IoT an ideal choice for the industries.
Invention of Industrial Robotics Changed the Manufacturing Hubs:
The industrial robotics has ruled the market since a very long time, thus, this technology is considered as old-fashioned by the manufacturing hubs. However, the invention of intelligent robots changed the dynamics for robotics as such robots are capable of performing multiple tasks. These robots are built with sensors that control the situations with earmark actions.
Apart from this, the novel type of collaborative robots is designed to work with the humans. They have the ability to mimic work precisely, thus, improving the manufacturing process.
Use of Artificial Intelligence in the Industries:
The smart manufacturing sector repeatedly uses the AI technology for acquiring data from the sensors. This data is stored in the systems that process it at reasonable prices.
Artificial intelligence is mainly incorporated in robotics because they have the ability to make decisions based on perceptions, unlike regular robots that follow algorithms.
In this case, the predictive maintenance determines the performance, breakdown, and operating conditions of the machine. The smart manufacturing sector prefers artificial intelligence because it has computer vision technology, can be used in big data analysis, displays robotics compatibility, and can lead to partnerships that can harvest investments.
Role of Blockchain Technology in the Industries:
At present the blockchain technology is used in the financial department as this is still in the initial level. If the blockchain technology is implemented in the manufacturing unit then it has the potential to control the quality of the products from the commencement stage. This improves the product’s worth in the market by a huge margin. The blockchain technology is popularly used by the following sectors:
- Healthcare sector
- Food and beverage
- Aviation industry
- Shipping industry
- Solar energy
- Mining fields
- Fishing
- Apparel manufacturing
Benefits of Using Smart Manufacturing:
The smart manufacturing imparts various advantages on the industries, factories, and workplaces that use it for product manufacturing. Some of the pros are stated as follows:
- This ensures automated data collection that leads to production analysis before the final goods generation. This helps in making timely decisions to avoid damages in the product.
- Predictive maintenance ensures improvised visibility that aid in solving manufacturing problems and prevents downtime or product quality issues. Devices used for predictive maintenance are sensors as they can easily identify and rectify the glitches in the production units.
- This assures major cost reductions by identifying waste in the manufacturing units.
- The accuracy levels are enhanced if the operation and the enterprise systems are interconnected.
- The inventory costs are reduced as smart manufacturing provides better insights in the delivery statuses, demand and supply chain, and inventory status. This maximizes the production levels to a greater extent.
- The challenges related to workforce are minimized as new projects can be launched by a smaller group. Moreover, the workers can access data on real-time basis on multiple platforms; thus they can focus on core responsibilities like creating novel inventions.
- The productivity is augmented due to monitoring the machine performance, countering operation inefficiencies, and connected systems.
How has Covid-19 affected the Smart Manufacturing Sector?
China is considered as the manufacturing hub of the raw materials but the raw material shipments from China have halted as the coronavirus infection started spreading from here. This entire situation has affected the industrial manufacturing processes at a global level as many countries depend on these raw materials for manufacturing purposes.
Apart from this, nationwide lockdown in all the countries has declined the production rate, which in turn, has hampered the smart manufacturing sector as well. The Covid-19 pandemic has majorly affected the automotive and small and medium scale enterprises (SMEs).
Nevertheless, the post Covid-19 period will open up several opportunities for the smart manufacturing sector as the industries will restart the production at full scale.
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