Smart Manufacturing in the Era of the Industrial Internet of Things
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Smart Manufacturing in the Era of the Industrial Internet of Things

To enhance competitiveness, manufacturers are driving a shift from a reactive problem-solving model to a more proactive device, process, product, and plant management model.
Published: Oct 12, 2022
Smart Manufacturing in the Era of the Industrial Internet of Things

Industry Problems Facing the Manufacturing Industry?

  • Internal pressure: Highly dependent on labor, the problem of low birthrate is expanding year by year, which is not conducive to industrial development.
    Export products are still labor-intensive industries. Among them, the manufacturing chain processes such as mechanical metal processing, textile, and electronic product production are the most labor-intensive and time-consuming. The highest error rate and the worst efficiency. There are many small and medium-sized enterprises in Taiwan, and lack of funds and knowledge to introduce digital technology. The low birthrate and aging population will make it increasingly difficult to recruit traditional workers, and the quality of work and living space will be even more unfavorable.
  • External pressure: The international program has matured, and the domestic technical level needs to catch up urgently
    It has become a trend for major international manufacturers to propose smart solutions, and they have started from the Industrial Internet of Things to accelerate meeting the needs of smart manufacturing and achieve the goals of correct, labor-saving, labor-saving, and rapid manufacturing, and shipments. In Taiwan, however, there are still many manual operations, and there is a lack of a technical demonstration environment.
    To increase competitiveness, manufacturing-related activities are bound to be digitized and automated. If there is no integrated domestic solution, only foreign solutions can be used in the future, which will not only make it difficult to exert unique competitive advantages but also lack the opportunity to create the output of whole plant solutions.

What is Smart Manufacturing?

Smart manufacturing is based on precision machinery, combined with various smart technologies, such as artificial intelligence, IoT big data, cloud computing, robots, and high-speed networks, to meet the needs of smart equipment and systems. Therefore, the implementation of smart manufacturing demands is to produce applications in the factory environment to improve the technical level or reduce production costs, thereby enhancing the competitiveness of modern factories.

It closely integrates all aspects of the production process of smart machinery with the Internet of Things, cloud computing, big data, and AI artificial intelligence applications, and integrates end-to-end data streams through the network so that machines can communicate with each other, and between machines and people. , Quantitative and transparent management replaces the traditional factory manufacturing operation management mode and assists the digital transformation of the manufacturing industry.

Application of smart manufacturing:

Smart manufacturing has many impacts on demand forecasting, raw material price forecasting, process optimization, quality forecasting, scheduling optimization, equipment prevention, automatic optical inspection, inventory management, and transportation optimization.

Four Elements of Smart Manufacturing

  • Import automation equipment:
    Although automation equipment is one of the foundations of smart manufacturing and can replace some labor-based jobs, the most important thing is to match and optimize each link of design, production, and service to have a high-efficiency and low-cost process. It's just an ignorant introduction to automation equipment, or it may just spend a lot of money without getting any benefits.
  • Device connection and data integration:
    After the automation equipment is imported, the next step is to connect the equipment. Through the technology of the Internet of Things, the data of each piece of equipment can be integrated and the manufacturing process can be optimized.
  • Remote monitoring:
    Although smart manufacturing has replaced some labor work, people can therefore carry out more decision-making and technical work, and through remote monitoring to help operators grasp the status of equipment at any time. Adjust manufacturing schedules in real-time, reduce equipment without warning downtime, increase productivity and extend equipment life.
  • Combined with AI technology:
    The goal of smart manufacturing is to combine artificial intelligence, which is one of the most important trends at present. AI can allow equipment to be upgraded, and through self-learning, it can collect various information to continuously optimize the process.

Future Smart Manufacturing Trends and Market Trends

  • Expand 5G applications:
    The three major features of 5G (URLLC, mMTC, eMBB) are expected to provide secure, fast, and highly reliable communications, driving the transformation, and upgrading of the manufacturing industry to smart factories. It is necessary to develop the surrounding supply chain and ecosystem together with telecom operators, system integrators, and Netcom operators. In the future 5G+AI innovation scenario, one million edge devices within one square kilometer may be connected in series within one second to make the overall best decision.
  • Import AI interpretability:
    Humans and machines must cooperate, and they must rely on interpretability to persuade people and assist in analysis and decision-making. When it comes to the optimization of a specific process and the selection of important features, the model judgment results may be difficult to convince process engineers with many years of experience. In addition to the high cost of the process, whether the interpretability can be proposed at this time plays a role in whether the application can be implemented. key role.
  • Federated Learning Model:
    It is mainly aimed at when training AI models, because the data set may have considerations such as privacy, regulations, geographical regions, and competition in the industry, it is impossible to carry out traditional centralized learning, so model sharing is used instead of data sharing to break the data barriers and realize the application. End-to-end differentiation and knowledge sharing. In terms of local smart manufacturing, consideration can be given to introducing them into industrial clusters dominated by small and medium-sized enterprises that have common AI requirements but require product differentiation.
  • Information security protection:
    The most common security threats in Taiwanese manufacturing are ransomware, malware attacks, and phishing attacks. In the future, enterprise defense will move to a new architecture that integrates IT and OT, so that the OT side can be included in information security protection, and a unified solution will be established to alleviate the challenges of digital transformation.

The Benefits of Smart Manufacturing:

The benefits of smart manufacturing are numerous, including the ability to proactively detect and respond to events, improve quality and yield, reduce downtime, and improve overall equipment effectiveness (OEE). Through the digital clone of the factory, it is possible to simulate new processes in advance and understand where the bottlenecks are. Smart manufacturing allows proactive changes to supply chains and smart inventory, optimizing other factory logistics, including packaging and shipping. Smart manufacturing can also uncover new business opportunities, revenue streams, and asset monetization to gain a sustainable competitive advantage. It can automate, coordinate, and predict the likelihood of product failure for preventive maintenance to prevent downtime. Smart manufacturing can process and analyze data in real-time near the point where it is generated, to quickly respond to abnormalities in the process.

In sales and marketing, smart manufacturing allows organizations to understand the market and predict and cater to customer preferences. Smart manufacturing can help forecast demand, optimize inventory, and monitor suppliers in terms of supply chain optimization. Supply chain organizations have used analytics for forecasting and inventory management for years, but in the age of IoT, where we now know where almost everything is, more on-the-fly capabilities are needed. 5G networks can support ultra-high connection densities of tens of thousands of endpoints, thus enabling real large-scale use of industrial data, taking factories to another new level.

Smart manufacturing can improve the quality of products and processes through smart statistical process control, yield management, and reliability analysis. The ability to understand and demonstrate that a process is in control is a core element of programs such as Quality by Design (QbD) and Good Manufacturing/Documentation/Safety Practice (GxP). Smart manufacturing can help to comply with regulations to standardize, automate and monitor QbD and GxP schemes, thereby being able to demonstrate to regulators that all processes are being watched and controlled and that even the most sophisticated institutions cannot avoid tax evasion. Analytics technology can be used for automated and validated regulatory reporting, full audit trails, version control, and electronic signatures to document changes to analytical processes, procedures, and reports, and to monitor and automate workflows and audits.

Objectives that AI Scheduling Technology can Assist with:

  • AI assists net-zero carbon emissions and develops green business opportunities:
    AI scheduling uses digital carbon reduction technology to reduce carbon emissions in industries that require high carbon emissions, which will help products develop green business opportunities. At the same time, it ensures the proper allocation and maximization of resources and reduces the waste of energy.
  • AI responds quickly to supply chain changes and quickly assesses delivery dates:
    Since the outbreak of the epidemic, the supply chain has been unable to stabilize the raw material supply chain due to the limited transportation energy. Through AI scheduling technology, various influencing factors can be input, and the delivery date can be calculated in a short time, allowing the business to take orders and promise to deliver. The period is more accurate, and the company's goodwill can be maintained.
  • AI reduces complex rule setting and stabilizes production capacity planning:
    In the era of high customization, a small number of diverse orders cannot be set using simple rules, and planning that can stabilize production capacity is important. Scheduling technology helps people make decisions that are not good at considering multiple goals in life. Using AI scheduling can achieve better results, and can achieve digital carbon reduction, and protect the earth by using scheduling.

Smart manufacturing is an important trend in the development of the manufacturing industry and a direction to enhance competitiveness. Many enterprises are prone to rush to transform without understanding them. Before transforming, they may first understand the basics and what difficulties they may encounter, and then plan suitable solutions for the enterprise. The transformation plan can maximize the benefits.

Published by Oct 12, 2022 Source :udn, Source :tibco

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