What is Smart Manufacturing: Meaning & Examples

Smart manufacturing (SM) revolutionizes production by employing machinery connected to the Internet to monitor and enhance manufacturing. At its core, SM aims to boost operational efficiency and productivity by identifying opportunities for automation and harnessing real-time data insights.

Smart manufacturing also optimizes supply chain functions by integrating physical and digital processes in factories and across the supply chain. It enhances decision-making by transforming how people, processes, and technology operate, ensuring efficiency and agility. According to the Gartner Report, despite the prioritization of digitizing manufacturing operations by 91% of supply chain leaders, challenges persist, such as technology security, commercial availability, data integrity, and aligning ROI expectations between the supply chain and factories.

Leveraging the Industrial Internet of Things (IIoT), smart manufacturing systems thrive on the synergistic relationship between sensor data and artificial intelligence (AI). Densely deployed sensors capture real-time performance metrics from machinery, enabling proactive maintenance, identification of process inefficiencies, and data-driven decision-making.

AI then takes center stage, analyzing this vast data stream to optimize production processes, guarantee high-quality output, and even predict equipment failures for preventive maintenance. This powerful interplay between IIoT and AI constitutes the cornerstone of the smart manufacturing revolution.

Despite its potential, the widespread adoption of SM faces challenges such as the lack of standardized technical protocols, hindering seamless communication and interoperability among manufacturing systems. Moreover, high upfront costs, complex technology, and limited accessibility can create hurdles for smaller players.

However, as smart manufacturing evolves, expect further integration of automation, AI, and advancements like digital twins for a future of hyper-connected and smart manufacturing.

It all began over two centuries ago with the original Industrial Revolution, Industry 1.0, where the introduction of steam power and machines marked a significant shift in manufacturing.

Fast forward to Industry 2.0, where the crackle of electricity replaced the roar of steam, and mass production became the hallmark of innovation. Think assembly lines churning out goods at unprecedented speeds, forever altering the landscape of the industry.

Then came Industry 3.0, a period characterized by the integration of automation and early computing technologies. Imagine computers and robots working alongside humans, transforming how we work and produce.

And now, at the peak of industrial evolution stands Industry 4.0, the era of smart manufacturing. It's not about getting rid of old factories; it's about taking them to the next level with cutting-edge technologies. Picture a world where machines communicate seamlessly, where data drives decisions, and where efficiency and effectiveness reign supreme.

Right now, the EU has proposed a new concept of Industry 5.0, prioritizing sustainability, human-centricity, and operational resilience. Key strategies include leveraging digital technologies for optimized operations and supply chains, transitioning to a circular economy, enhancing digital literacy among employees, and boosting research and development capabilities for competitive advantage.

From the clatter of steam engines to the cyber-physical systems, each revolution has pushed us forward, expanding the possibilities and ushering in a future full of promise and potential.

If you're a manufacturer looking to embrace Industry 4.0 and optimize your production processes, explore Advantech's solutions and see how a system integrator partner can help you tailor them to your specific needs.

Smart manufacturing is revolutionizing production by leveraging data and intelligent technologies. Here are 8 key benefits that are driving its adoption:

Improved Efficiency and Productivity: By optimizing processes, identifying bottlenecks, and automating tasks, smart factories can significantly increase production output while minimizing waste.

Predictive Maintenance: Sensors and real-time data analysis enable manufacturers to predict equipment failures before they happen. This allows for proactive maintenance, minimizing downtime and associated costs.

Enhanced Quality Control: Smart systems with machine vision and AI can inspect products with unmatched accuracy and speed, ensuring consistent quality, reducing risks for product recalls, and higher customer satisfaction.

Data-Driven Decision-Making: The abundance of real-time data from sensors and machines allows for data-driven decision-making throughout the production process. This leads to better resource allocation, improved forecasting, and agile responses to market changes.

Increased Flexibility and Agility: Production lines can be easily adjusted to accommodate changes in product design, customer demand, or market trends. This allows manufacturers to respond quickly to opportunities and stay ahead of the competition.

Improved Worker Safety: Smart technologies can automate dangerous tasks, reducing the risk of workplace injuries. Additionally, real-time monitoring can identify potential safety hazards before incidents occur.

Reduced Environmental Impact: Smart systems can optimize energy consumption and minimize waste generation. Additionally, data-driven insights can help manufacturers identify opportunities for using sustainable materials and processes.

End-to-End Savings: Digital integration across the supply chain improves forecasting, inventory management, and logistics, resulting in fewer risks, reduced spending, and increased customer satisfaction.

These are just a few examples of the many benefits smart manufacturing offers. As technology continues to evolve, we can expect even more exciting innovations and applications that will further transform the manufacturing landscape.

Now let's focus on the fundamental and related technologies that form the basis of smart manufacturing practices.

IoT & IIoT

The Internet of Things (IoT) involves connecting various devices, sensors, assets, and machines into a network to collect and exchange data. IIoT signifies the incorporation of IoT devices into production processes. In smart manufacturing, an IIoT network is at the core as it enables real-time monitoring of equipment, predictive maintenance, and data-driven decision-making. Predictive maintenance utilizes advanced analytics and machine learning algorithms to anticipate equipment failures before they occur, enabling proactive maintenance to prevent costly downtime and optimize production efficiency.

Incorporating various latest technologies like edge computing, TSN, and, M2M, both IoT and IIoT are crucial in smart manufacturing because they facilitate the integration of digital technologies into physical machinery, fostering greater automation, connectivity, and control over manufacturing operations.

AI/Machine Learning at the Edge

AI refers to technologies designed to mimic human intelligence, while ML is a subset of AI focused on building systems that improve performance based on data input. Algorithms enable machines to analyze data at a much faster speed, learn from it, adapt, and make decisions without human intervention.

In smart manufacturing, AI and ML allow these systems to become predictive powerhouses. By analyzing data, they can anticipate equipment failures before they happen, optimize production schedules for maximum efficiency, avoid expensive downtimes, and identify areas for improved quality control. In short, AI and ML turn data into insights, empowering smart factories to become more efficient, cost-effective, and proactive.

Gain insight into Edge AI and Industrial AIoT solutions.

Augmented Reality/Virtual Reality

Augmented Reality (AR) and Virtual Reality (VR) are transforming manufacturing by enabling immersive, interactive experiences that improve various processes such as on-the-job training, remote guidance, product design, and maintenance with devices like smart galsses. These technologies allow manufacturers to visualize complex systems, simulate real-world operations, and conduct remote troubleshooting with enhanced accuracy. By integrating AR and VR, companies can boost efficiency, reduce errors, and streamline production.

Autonomation/Robotics

Autonomation, also called automation with human intelligence, means using robots and automated systems that can work by themselves while also working with humans. This means robots can change what they do based on real-time information, work together with people (called cobots), and improve over time by learning.

The benefits are substantial: autonomous robots tackle repetitive tasks with precision, boosting efficiency and reducing errors. This frees up human workers for higher-value activities, while the system's flexibility allows factories to adapt to changing demands while enhancing production efficiency, quality, and safety.

Learn more about Advantech’s cobot and AGV(Automated Guided Vehicle) for automation applications.

Big Data

Big Data in smart manufacturing refers to the massive volumes of structured and unstructured data generated by various sources within manufacturing processes. Analytics tools are essential for processing this extensive data, extracting valuable insights that empower manufacturers to enhance production processes, anticipate equipment malfunctions, and make informed decisions regarding logistics, risk assessment, cost management, and quality control in real time.

Read More: The Next Leap of Digital Transformation in Manufacturing

CNC Machining

Computer Numerical Control (CNC) machining involves the use of computer-controlled machines to precisely shape and cut materials according to digital designs. In smart manufacturing, it offers unparalleled precision, repeatability, and efficiency in producing complex components and parts. CNC machines can also be integrated with IoT sensors and AI algorithms to monitor performance, optimize toolpaths, and minimize material waste.

Read More: Ensure Stable Production with CNC Spindle and Tool Health Assessment System and Advantech’s CNC Networking Software

Anomaly Detection

Anomaly detection involves the identification of abnormal patterns or deviations from expected behavior within datasets. In smart manufacturing, anomaly detection algorithms are deployed to detect equipment malfunctions, process inconsistencies, and quality defects in real time. By proactively identifying anomalies, manufacturers can prevent costly downtime, minimize product defects, and optimize production efficiency.

Read More: Advantech’s iFactory solutions can enhance your workstations by enabling real-time tracking of production anomalies, assistance requests, and material needs and our AI AOI solutions.

5G Connectivity

5G is the fifth generation of wireless technology, offering faster data speeds, lower latency, and greater connectivity than its predecessors. In smart manufacturing, deploying 5G enables high-speed, reliable communication between IoT devices, robots, and production systems. With 5G networks, manufacturers can deploy real-time monitoring and control applications, enabling agile and responsive operations.

Read More:

Private 5G Networks for Industrial IoT

5G Edge Servers for the Open RAN

Discover our 5G Powerful Edge Computing Gateways

Blockchain

Blockchain technology is revolutionizing the manufacturing industry by enhancing transparency, traceability, and efficiency throughout the supply chain. It enables manufacturers to track products from raw material sourcing to final delivery, ensuring authenticity and quality at every step. Additionally, blockchain supports secure and immutable record-keeping, smart contracts, and real-time monitoring, which are critical for improving supply chain operations, preventing counterfeits, and ensuring regulatory compliance in smart manufacturing​.

Cloud Computing

Cloud computing is revolutionizing manufacturing by providing scalable, cost-effective solutions that enhance efficiency and innovation. It enables real-time data processing, improves supply chain management, and supports predictive maintenance. By integrating with Industry 4.0 tools like IoT and AI, cloud connectivity offers on-demand access to resources such as IIoT data and process automation across wireless channels like Wi-Fi or 5G, making it a cornerstone of modern smart manufacturing.

Edge Computing

Edge computing involves processing data near the source of generation, rather than relying on centralized data centers. In smart manufacturing, edge computing brings computation and analytics closer to IoT devices and production equipment, enabling faster response times and reducing latency. This technology is critical in smart manufacturing because it enables distributed intelligence, resilience, and scalability.

Find out more about the advantages of Advantech’s Industrial Computers!

Digital Twin

A digital twin is a virtual replica of a physical asset, process, or system that simulates its behavior and performance in real time. In smart manufacturing, digital twins enable manufacturers to model, monitor, and optimize production processes and equipment. For products, it can also be used to virtually test different designs, identify potential weaknesses, and optimize performance before physical prototypes are built, which saves resources and costs in advance.

Design for Manufacturing (DFM)

Design for Manufacturing (DFM), or design for manufacturing and assembly (DfMA), is a methodology that focuses on designing products with manufacturing considerations in mind. In smart manufacturing, DFM principles enable designers to optimize product designs for efficient production, assembly, and cost-effectiveness. This technology is crucial in smart manufacturing because it fosters collaboration between design and manufacturing teams, streamlines production processes, and enhances product performance and manufacturability.

Additive Manufacturing/Hybrid Manufacturing

Additive manufacturing, also known as 3D printing, involves building objects layer by layer using digital 3D models. In smart manufacturing, additive manufacturing makes it possible to produce complex components and prototypes with unprecedented flexibility, customization, and efficiency. Hybrid manufacturing combines additive and subtractive processes to leverage the strengths of both techniques. By adopting these technologies, manufacturers can reduce tooling costs, shorten lead times, and produce lightweight and intricate parts with minimal material waste.

In collaboration with various industry leaders, Advantech has played a pivotal role in advancing smart manufacturing through innovative solutions. The following cases highlight how Advantech's technologies have been implemented to enhance manufacturing processes.

TECHPRO

Advantech assisted THACO INDUSTRIES with TECHPRO in transforming their automotive leaf spring manufacturing into a smart factory by integrating IoT sensors, gateways, and edge devices with MES, OEE, and FEMS solutions. This collaboration improved IT and OT connectivity, enabling real-time monitoring, data visualization, and predictive maintenance. The project increased automation from 25% to 82%, boosted productivity, optimized energy management, and streamlined production processes, ultimately enhancing efficiency, quality, and profitability.

Integral

Advantech, in collaboration with Integral System, assists French manufacturers in advancing smart manufacturing by integrating IoT hardware and modular software solutions. Their iFactory/Maintenance and iFactory/PHM platforms enable scheduled, proactive, and predictive maintenance, optimizing equipment reliability and minimizing unplanned downtime. This partnership enhances the maintenance efficiency of critical assets like motors, leading to improved operational efficiency, reduced costs, and extended equipment lifespan, thus empowering factories to transition to proactive management and achieve sustainable industrial information systems.

Nefab

Advantech assisted Canadian packaging company Nefab in smart manufacturing by implementing the iFactory/Andon I.App through their WISE IoT Platform. This solution digitized Nefab's production processes, reducing problem resolution times by 50% and problem frequency by 80%, while increasing productivity by 7%-8%. Advantech’s cloud-based implementation enabled real-time monitoring, improved efficiency, and reduced downtime, showcasing the effectiveness of their IoT subscription-based services in facilitating the transition to smart manufacturing.

Eforel

Advantech, through Eforel, assisted a multinational food corporation in Indonesia by implementing the iFactory/OEE solution to enhance production visibility and efficiency. The solution provided real-time monitoring, reducing downtimes and material waste while increasing ROI. The project integrated multiple machine protocols, enabling seamless data acquisition and analysis, which allowed for improved decision-making and process optimization. This successful implementation is set to expand across other machines in the factory, further optimizing resources and boosting quality control.

More Examples

Advancing Automotive Leaf Spring Manufacturing through Smart Manufacturing

Advantech’s IoT SaaS Platform Empowers Canadian Packaging Factory with Smart Applications

Creating Tailored Applications Across Diverse Manufacturing Scenarios with Advantech iFactory

Embracing the digital era in manufacturing is no longer just an option; it's a necessity for staying competitive in today's market. As the adoption of advanced manufacturing 4.0 technologies continues to surge, the future of smart manufacturing promises a completely different production environment transformed for all factories across industries.

Here are 3 key trends to watch:

AI and Machine Learning Take the Wheel

Expect artificial intelligence to become even more powerful, continuously learning and optimizing processes in real time through machine learning. This could lead to autonomous factories with self-regulating production lines and a whole new level of predictive maintenance.

Sustainability Redefine with Efficient Manufacturing

Smart manufacturing systems lead the charge in revolutionizing traditional manufacturing practices, paving the way for environmentally conscious operations while enhancing efficiency. For instance, AI-powered systems in the food and beverage industry analyze production data to streamline energy consumption and minimize waste.

Find out how Adventech’s iFactory solution helps achieve optimized food production and reduced waste.

Spotlight on Human-Machine Collaboration

While automation will continue to grow, human expertise will remain irreplaceable. The future lies in seamless collaboration between humans and intelligent machines, with AI augmenting human decision-making and workers focusing on higher-level tasks.

Customized Solutions Based on Different Needs

The future of manufacturing is increasingly focused on customer-centric approaches, driven by technological advancements that enable high levels of customization and personalization. Manufacturers are now leveraging mobile solutions with intuitive interfaces and advanced technologies like 3D printing and IoT to efficiently produce tailored products. This shift allows for mass customization at unprecedented scales, meeting growing consumer demands for personalized goods while enhancing market competitiveness.

Innovation in Supply Chain Management

Innovation in supply chain management is transforming product production and delivery, with technologies like blockchain and IoT enhancing transparency, efficiency, and resilience. These advancements allow for real-time tracking, automated transactions, and improved visibility, reducing disruption risks. By digitizing and integrating supply chain elements, manufacturers can optimize operations, minimize waste, and promote sustainability.

Cybersecurity in Manufacturing Process

In smart manufacturing systems, cybersecurity is critical due to the integration of IoT, AI, and cloud technologies, which increase vulnerability to cyber threats. Protecting intellectual property, ensuring operational continuity, and meeting regulatory standards are essential. Key strategies include risk assessment, network segmentation, and real-time threat detection, which safeguard manufacturing processes while enabling the benefits of digital transformation​.

Overall, continuous advancements in AI, IIoT, and data analytics will drive the evolution of smart manufacturing, promising hyper-connected and hyper-efficient factories that redefine the manufacturing landscape.

Transitioning to smart manufacturing introduces several critical challenges that can impact business operations if not effectively managed.

Cybersecurity Concerns

As companies connect more devices through the Internet of Things (IoT) and other smart technologies, the risk of cyber threats increases. This expanded digital landscape requires consistent vigilance and advanced security protocols. Without proper security measures, vulnerabilities in these interconnected systems can lead to costly data breaches and operational disruptions, posing risks to both intellectual property and production integrity.

High Implementation Costs

The investment required to implement smart manufacturing can be a barrier for many companies. Expenses include upgrading legacy systems, purchasing new technology, and potential downtime during setup. While the software itself constitutes about 10% of the total cost of ownership, hidden costs from manual, repetitive tasks can dominate. Companies need to focus on long-term efficiency and scalability to manage these lifecycle costs effectively. Failing to budget for these factors can lead to financial strain, especially if ROI is not achieved as quickly as anticipated.

Skills and Talent Gaps

Smart manufacturing demands specialized skills in areas such as data analysis, cybersecurity, and system integration—skills that traditional manufacturing teams may lack.While hiring software developers is a potential solution, the industry’s demand outstrips supply, making this unsustainable. Empowering existing Operational Technology (OT) and IT teams with low-code tools offers a more practical approach to addressing this gap. Attracting and retaining skilled workers remains a challenge, particularly in competitive tech markets.

Data Management Challenges

Smart factories generate massive data volumes, which can lead to isolated data silos, limiting the effectiveness of smart manufacturing. The core challenge is transforming raw machine data into actionable insights, automation, or predictive analytics. This process requires a structured approach, starting with data collection, transformation, and adding contextual metadata to enable business intelligence. Data overload without proper processing and contextualization may obstruct timely decision-making, creating inefficiencies rather than the expected enhancements.

Integration with Legacy Systems

Incorporating smart technology within existing infrastructure can present compatibility issues, especially if legacy systems cannot communicate with new digital tools. The complexity of integrating legacy machines with varied protocols, multiple cloud and on-premises systems, and fragmented data structures further adds to these challenges. Managing data across segmented networks, diverse vendors, and mixed technology generations requires robust planning to minimize disruption and unlock the full potential of smart manufacturing.

To begin, companies should evaluate existing systems to pinpoint areas where data integration and automation could enhance productivity. A stepwise approach, starting with smaller pilot projects, is ideal—testing technologies like AI, IoT, and predictive analytics on a small scale helps reduce risk and manage costs. Aligning these pilot projects with clear business metrics and securing executive buy-in, particularly from technology leaders, provides the support necessary for a smooth transition.

Digitalizing data is an essential first step, establishing a centralized digital repository to replace analog systems, enabling real-time feedback loops and informed decision-making. With centralized data, manufacturers gain visibility into processes through continuous data collection, which identifies bottlenecks and informs further improvements. To facilitate seamless data sharing, businesses must standardize communication protocols across different machines and software, addressing challenges with proprietary systems and ensuring interoperability across platforms.

As connectivity expands, robust cybersecurity measures become crucial. Smart factories require secure data systems to protect sensitive information and intellectual property. Algorithms and advanced analytics also play a vital role, enabling manufacturers to optimize processes continuously. By analyzing data insights, businesses can refine operations, improving efficiency and reducing waste.

Finally, adopting a resilient, innovation-driven mindset helps organizations remain agile in the face of economic challenges, transforming necessity into a powerful driver of growth. This methodical approach enables companies to reap the benefits of smart manufacturing while staying adaptable and competitive in an evolving industry landscape.

Smart manufacturing is the future of the industry, offering a revolutionary approach to production that leverages cutting-edge technologies to optimize processes and drive innovation. By integrating the Internet of Things (IoT), Artificial Intelligence (AI), automation, and so many more, smart manufacturing promises to transform traditional manufacturing methods, paving the way for increased efficiency, reduced costs, and enhanced quality.

Embracing this transformative trend is essential for businesses looking to stay competitive in today's rapidly evolving market landscape. Experience the future of manufacturing with Advantech's iFactory solutions, and unlock the full potential of smart manufacturing for your business. Also, discover more powerful cases of industrial equipment manufacturing accomplished with Advantech's innovative solutions here!