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Active suspension can take into account the smoothness and handling stability of the car, while in the traditional passive suspension design, smoothness and handling stability are often difficult to take into account, and generally have to take a compromise approach.When the load quality changes or road conditions change, the active suspension can ...
IVI can realize a series of applications including 3D navigation, real-time road conditions, IPTV, assisted driving, fault detection, vehicle information, body control, mobile office, wireless communication, online-based entertainment functions and TSP services, which greatly enhance the level of vehicle electronics, networking and intelligence. Ne...
The power system of a car is the whole process of mechanical arrangement in which the power generated by the engine is transmitted to the wheels through a series of power transmissions. The engine runs, in fact, the crankshaft is rotating, and one end of the crankshaft ...

Top 15 Industrial Automation Companies In 2025
As of 2025, the industrial automation industry continues to evolve rapidly, driven by advancements in AI, robotics, IoT, and smart manufacturing. The top companies in the sector are not only focused on automation hardware (like robotics, sensors, and PLCs) but also on software solutions, AI integration, and end-to-end digital transformation. Here are the top 15 industrial automation companies:
1. Siemens AG
- Headquarters: Germany
- Key Focus: Industrial automation, digitalization, factory automation, smart grids, and automation software.
- Notable Products: SIMATIC PLC, MindSphere (IoT platform), SINAMICS drives, and process automation solutions.
2. Rockwell Automation
- Headquarters: United States
- Key Focus: Industrial automation and information technology solutions, advanced analytics, and cloud integration.
- Notable Products: Allen-Bradley PLCs, FactoryTalk software, and industrial IoT solutions.
3. Schneider Electric
- Headquarters: France
- Key Focus: Energy management, industrial automation, IoT integration, and digital transformation.
- Notable Products: EcoStruxure platform, variable frequency drives, and building automation solutions.
4. ABB Ltd.
- Headquarters: Switzerland
- Key Focus: Robotics, automation, electrification, and digitalization across industries.
- Notable Products: ABB Ability, YuMi collaborative robots, and industrial automation systems.
5. Mitsubishi Electric
- Headquarters: Japan
- Key Focus: Factory automation, robotics, and industrial control systems.
- Notable Products: MELSEC PLCs, industrial robots, and FA (Factory Automation) products.
6. Honeywell International Inc.
- Headquarters: United States
- Key Focus: Process control, industrial automation, and cybersecurity solutions.
- Notable Products: Honeywell Experion PKS, Industrial IoT solutions, and Process Automation products.
7. Emerson Electric Co.
- Headquarters: United States
- Key Focus: Automation for process industries, manufacturing, and data analytics.
- Notable Products: DeltaV control systems, Ovation for power generation, and industrial automation solutions.
8. Yokogawa Electric Corporation
- Headquarters: Japan
- Key Focus: Industrial automation, process control, and IT solutions for industrial operations.
- Notable Products: CENTUM VP, ProSafe-RS, and various process automation solutions.
9. FANUC Corporation
- Headquarters: Japan
- Key Focus: Robotics, CNC systems, and industrial automation solutions for manufacturing.
- Notable Products: Robotic arms (collaborative and industrial), CNC controls, and automation systems for various industries.
10. Siemens Digital Industries Software (formerly Mentor Graphics)
- Headquarters: United States (part of Siemens)
- Key Focus: Digital transformation, automation, and industrial software solutions for design, manufacturing, and operations.
- Notable Products: NX, Teamcenter, and SIMATIC automation software solutions.
11. Keyence Corporation
- Headquarters: Japan
- Keyence is known for its cutting-edge sensing, vision systems, measurement instruments, and automation equipment, widely used in factory and process automation.
12. KUKA Robotics
- Headquarters: Germany
- A leading robotics company, KUKA specializes in automation and robotics solutions for manufacturing, especially in the automotive and electronics sectors.
13. Bosch Rexroth
- Headquarters: Germany
- Bosch Rexroth offers automation solutions in factory automation, mobile applications, and process automation, emphasizing hydraulics, pneumatics, and motion control systems.
14. Bentley Systems
- Headquarters: USA
- Bentley provides digital solutions for the design, construction, and operation of infrastructure, integrating industrial automation with engineering design software.
15. WAGO Kontakttechnik
- Headquarters: Germany
- WAGO offers automation products including programmable controllers, connectors, and communication technology, with a focus on industrial communication and control solutions.
These companies are at the forefront of industrial automation, driving technological advancements such as Industry 4.0, digital twins, AI-driven processes, and intelligent robotics. Their offerings span industries from manufacturing to energy to logistics, providing key tools for efficient, sustainable, and high-performance production systems.
Key Trends Driving the Industry in 2025:
- AI Integration: More advanced AI applications, such as predictive maintenance, anomaly detection, and autonomous robots.
- 5G and IoT: Increased adoption of 5G networks for real-time data communication, enabling more efficient IoT systems.
- Sustainability: Focus on energy efficiency and reducing environmental impact, with automation solutions for cleaner production processes.
- Edge Computing: Edge devices for faster data processing at the source, reducing latency in automation systems.
Jan 09, 2025

What Is The Role of HMI In Smart Manufacturing and Industrial Automation?
In the era of Industry 4.0, the integration of advanced technologies into manufacturing systems is revolutionizing the way industries operate. One of the most crucial components in achieving seamless operations is the Human-Machine Interface (HMI). HMI plays a pivotal role in enabling operators and engineers to interact with machines, systems, and processes in smart manufacturing and industrial automation. But what exactly is HMI, and why is it so important in modern manufacturing?
Defining HMI
The Human-Machine Interface (HMI) is a user interface or dashboard that connects operators or users to machines, devices, and control systems within industrial environments. It serves as a communication bridge between humans and machines, allowing the user to monitor and control the operations of automated systems efficiently.
HMI systems typically consist of graphical displays, touchscreens, and input devices such as buttons or keyboards. These systems can range from basic, standalone units to more sophisticated, networked solutions capable of controlling complex manufacturing processes.
Role of HMI in Smart Manufacturing
Smart manufacturing is characterized by the use of data, sensors, cloud computing, and real-time analytics to enhance production efficiency, flexibility, and decision-making. HMI plays a vital role in this transformation by enabling operators to interact with the vast array of data collected from machines, sensors, and other automated systems.
1. Monitoring and Visualization:
One of the primary functions of HMI is to provide real-time data visualization. It allows operators to observe key performance indicators (KPIs), production metrics, machine statuses, and alarms. Through intuitive graphical representations such as charts, gauges, and maps, operators can quickly identify issues, track progress, and make informed decisions.
2. Control and Interaction:
HMI systems allow users to send commands to machines or automation systems. Operators can adjust settings, start or stop processes, modify variables, and perform diagnostic tasks. This level of control is essential for optimizing production efficiency, ensuring product quality, and reducing downtime.
3. Data Integration and Decision-Making:
In smart manufacturing, data is generated at every stage of production. HMI serves as the interface for operators to access and interpret this data in real-time. The integration of HMI with advanced technologies such as the Industrial Internet of Things (IIoT) enables operators to make proactive, data-driven decisions based on insights from production data.
4. Enhanced Operator Efficiency:
With advanced HMIs, operators can access relevant information with greater ease. Modern HMI solutions are designed to be user-friendly and highly customizable, offering touch interfaces, alarms, and remote access options that increase the operator’s effectiveness and reduce human error.
5. Remote Monitoring and Maintenance:
Remote access is a growing trend in smart manufacturing, enabling operators and technicians to monitor and control machines from virtually anywhere. HMI systems often feature cloud connectivity, allowing for real-time diagnostics, troubleshooting, and predictive maintenance. This reduces the need for on-site interventions and ensures that issues can be addressed before they lead to major disruptions.
HMI in Industrial Automation
Industrial automation refers to the use of control systems such as computers, robots, and information technologies to handle various industrial processes and machinery. HMI is integral to industrial automation as it allows for seamless communication between operators and automated systems.
1. Integration with SCADA Systems:
HMI is often used in conjunction with Supervisory Control and Data Acquisition (SCADA) systems to monitor and control industrial processes. SCADA systems gather real-time data from sensors and equipment, and the HMI provides operators with a visual interface to interpret and manage that data. The integration of these systems enables centralized control of complex automated processes, increasing operational efficiency and safety.
2. Safety and Compliance:
In industrial automation, safety is paramount. HMI systems help ensure compliance with safety standards by providing operators with the necessary tools to manage alarms, emergency stops, and fault detection. Additionally, many HMIs include features like role-based access controls, which limit access to certain functions, helping prevent accidental or malicious interference with critical processes.
3. Customization and Scalability:
As manufacturing processes vary across industries, HMI systems can be customized to meet the specific needs of each application. Whether it's a small manufacturing line or a large-scale industrial plant, HMI systems can scale and adapt to different types of automation, offering flexible control for diverse environments.
The Future of HMI in Smart Manufacturing
As Industry 4.0 continues to evolve, so too will the role of HMI. The future of HMI in smart manufacturing is closely tied to emerging technologies such as Artificial Intelligence (AI), augmented reality (AR), and machine learning.
1. AI and Machine Learning Integration:
AI-powered HMI systems will be capable of making real-time decisions based on large volumes of data. These systems will be able to predict potential failures, suggest optimizations, and even autonomously adjust machine parameters to improve performance.
2. Augmented Reality:
Augmented Reality (AR) is set to revolutionize how operators interact with machines. By overlaying digital information over the physical world, AR-enabled HMIs could provide real-time troubleshooting assistance, step-by-step maintenance guides, and intuitive visual controls.
3. Increased Automation and IoT:
As the Internet of Things (IoT) connects more devices in the industrial ecosystem, HMI systems will need to handle an exponentially growing amount of data. Advanced HMIs will offer seamless integration with IoT networks, allowing operators to manage multiple machines and processes simultaneously with greater ease.
4. Voice and Gesture Control:
The use of voice commands and gesture recognition technology will further enhance HMI systems, allowing for hands-free operation and greater flexibility. This is especially useful in environments where operators need to maintain focus on physical tasks while still managing complex systems.
Conclusion
In summary, HMI is a critical element in the landscape of smart manufacturing and industrial automation. It serves as the vital interface between human operators and machines, providing real-time data visualization, control, and decision-making capabilities. As manufacturing continues to advance, HMI systems will evolve to accommodate new technologies, ensuring that industries remain efficient, safe, and competitive in the era of smart manufacturing. With the integration of AI, AR, and IoT, the future of HMI promises even more powerful and intuitive tools for managing automated systems and driving industry forward.
Jan 09, 2025

What Is A Multi-Chip Module (MCM)?
A Multi-Chip Module (MCM) is an advanced electronic packaging technology that integrates multiple bare chips, semiconductor wafers, and other discrete components within a single package. This technology allows an MCM to function as a larger integrated circuit when in use.
Features and Advantages
High-Density Assembly Technology
MCM technology achieves high-density assembly by placing multiple bare IC chips and other miniature electronic components on the same substrate. By eliminating materials and processes required in traditional integrated circuit packaging, it reduces raw material usage and simplifies production steps, significantly minimizing the size and weight of systems or components.
Enhanced Signal Transmission Speed
The technology achieves faster signal transmission due to significantly shortened interconnection lengths, enhancing overall system performance.
High Reliability
Compared to traditional surface-mount technology (SMT), MCM packaging offers superior reliability, especially in high-density and high-performance application scenarios.
Multi-Functional Integration
MCM technology integrates chips with various functionalities to create more complex system capabilities, making it suitable for diverse electronic devices and system architectures.
Classification of MCM
When exploring what MCM means, it's useful to understand its classifications, which are based on the type of multilayer wiring substrate used:
1. MCM-L (Laminated MCM):
· Uses multilayer thin printed circuit boards (PCBs) as substrates.
· Features low cost and mature manufacturing techniques.
· However, it has low thermal conductivity and poor thermal stability.
2. MCM-C (Ceramic-Based MCM):
· Uses ceramic substrates as interconnection substrates.
· Offers good thermal stability and low cost for single-layer substrates.
· However, it is challenging to fabricate multi-layer structures.
3. MCM-D (Deposited MCM):
· Employs stacked substrates made using thin-film technologies.
· One of the most actively researched and developed technologies in the electronic packaging industry.
· Provides high interconnect density and excellent performance.
4. Hybrid MCM (MCM-C/D):
· Combines features from both ceramic-based and deposited MCM technologies to achieve improved performance.
Application Examples
Since its inception, MCM technology has been widely applied across numerous fields. Key examples include:
1970s: IBM introduced bubble memory using MCM technology.
2001: IBM's Power4 dual-core processor supported configurations with up to 8 cores, utilizing 4 dual-core Power4 chips and additional L3 cache dies in an MCM design.
2000s: Intel introduced Pentium D (codenamedPresler) and Xeon processors (codenamedDempsey and Clovertown) based on MCM technology.
Sony Memory Stick: Implemented MCM technology for high-density storage.
Xbox 360 Graphics Processor Xenos: Leveraged MCM to significantly enhance graphical performance.
AMD Ryzen (codenamed Matisse) and EPYC Processors: High-performance computing processors built on the Zen 2 architecture with MCM technology.
Key Technologies
Several critical domains underpin MCM technology:
High-Density Multilayer Substrates
A core component of MCMs, the design and manufacture of substrates directly influence the volume, weight, reliability, and electrical performance of the module.
Low-Temperature Co-Fired Ceramic (LTCC)
An ideal substrate material for MCMs, offering high wiring density, low dielectric constant, small conductor sheet resistance, thermal expansion coefficient matching silicon devices, fast signal transmission speed, and low transmission loss.
Known Good Die (KGD) Technology
Ensures that bare chips meet the performance and reliability standards of packaged products. Achieved through functional testing, parameter testing, aging screening, and reliability experiments.
Assembly and Interconnection Technologies
Techniques such as wire bonding, tape-automated bonding (TAB), and controlled-collapse chip connection (C4) are used to connect multiple IC chips to the substrate, forming functional modules.
Future Development
As technology progresses, MCM technology continues to evolve. Currently, 2D MCM assembly efficiency has reached over 85%, nearing the density limits of two-dimensional assembly. To further increase assembly density, reduce size, and integrate more functionalities, 3D MCM technology has become a focus of research. Using three-dimensional structures (X, Y, Z axes) to integrate IC chips and components, 3D MCM achieves assembly efficiency of up to 200%. However, the high integration, structural complexity, material diversity, and power density of MCMs pose increasing challenges in terms of reliability, particularly concerning thermal and stress-induced failures.
Standards
Internationally, several standards related to MCM technology have been established, primarily focusing on substrates and KGD technology:
Substrate Standards:
Standards from organizations such as ASTM, IPC, and NEMA, including IPC-6012: Qualification and Performance Specification for Rigid Printed Boards.
KGD Standards:
NASA's Jet Propulsion Laboratory (JPL) developed KGD assurance guidelines, and EIA issued the EIA/JESD49: Procurement Standard for Known Good Die in 1996.
In summary, for those seeking what does MCM stand for, its definition lie in its role as a packaging solution that integrates multiple chips to create compact, reliable, and high-performance modules.
Dec 09, 2024

What Are The Main Differences Between Radar And Lidar?
Lidar, short for light detection and ranging, works by sending out laser pulses and measuring how long it takes for those pulses to hit an object and return.
Radar, or radio detection and ranging, sends out radio waves that bounce off an object and return to a sensor. By measuring how long it takes for those waves to bounce back after hitting an object, radar can determine the presence, distance, direction, speed, and other information of a target object.
Lidar and Radar play pivotal roles across industries such as autonomous vehicles, aviation, environmental monitoring, and more. Though both technologies are designed to detect and measure objects, they do so in fundamentally different ways. So, what are the key differences between Lidar and Radar?
1. Wavelength and Detection Mechanism
The primary distinction between Lidar and Radar is the type of electromagnetic wave each system uses:
Lidar: Utilizes laser light in the near-infrared range, which enables it to capture highly detailed 3D images of its surroundings. This precision makes it ideal for applications where a detailed understanding of the environment is crucial, such as in autonomous vehicles and mapping.
Radar: Uses radio waves, which have a much longer wavelength than Lidar’s light waves. This allows Radar to detect objects over greater distances and through obstacles like fog and rain, making it a reliable option for long-range detection in adverse weather conditions
2. Accuracy and Resolution
Lidar: Lidar’s use of laser pulses allows it to capture highly detailed 3D data with centimeter-level precision. This makes it ideal for applications where fine detail and high accuracy are essential, such as in autonomous driving and topographic mapping. Its ability to generate dense point clouds is a major advantage in creating highly accurate models of the environment, including complex surfaces and small objects.
However, the high granularity of Lidar also means that it requires more computational power and data storage to process the rich, detailed information it collects. This makes Lidar systems demanding in terms of both hardware and software infrastructure, particularly when real-time processing is needed, such as in autonomous vehicles.
Radar: Radar provides good accuracy, especially for large-scale object detection and velocity measurement. However, it lacks the fine detail of Lidar because radio waves have longer wavelengths, which result in lower spatial resolution. Radar is better suited for applications that prioritize broad area coverage over fine detail, such as air traffic control or weather monitoring. While Radar can measure distance and velocity accurately, its inability to capture small or intricate objects limits its use in scenarios where precision is critical.
On the positive side, the lower data volume generated by Radar systems makes them easier and cheaper to process, and they require less sophisticated hardware compared to Lidar.
3. Range and Long-Distance Detection
Lidar: Lidar performs exceptionally well in short- to medium-range applications, typically up to a few hundred meters, though some systems can reach several kilometers at higher costs. Its line-of-sight nature, combined with high accuracy, makes it perfect for applications like self-driving cars, where the vehicle needs to detect obstacles, pedestrians, and other vehicles in real time.
However, Lidar’s range can be limited by environmental conditions and it is less effective over long distances. As the range increases, maintaining accuracy becomes more expensive, making it less cost-effective for broad area scanning.
Radar: Radar excels in long-range detection, sometimes reaching distances of tens of kilometers. This capability makes it the preferred choice for applications such as military surveillance, weather forecasting, and aviation, where monitoring large areas from afar is crucial. Radar’s ability to cover such large distances, even through obstacles like rain or fog, gives it a clear advantage in environments where range is more important than detail.
4. Speed Detection and Measurement
Lidar: While Lidar is unmatched in generating detailed 3D spatial data, it is not typically used for speed detection. Its primary function is to measure distances rather than velocity, limiting its use in applications that require real-time tracking of fast-moving objects.
That said, some advanced Lidar systems have begun integrating velocity measurement capabilities using Doppler shift techniques, but these are still in developmental stages and not as widespread as Radar in this domain.
Radar: Radar’s strength lies in its ability to measure the velocity of moving objects using the Doppler effect. This makes it essential for applications like traffic enforcement, aircraft navigation, and missile tracking, where real-time speed data is critical. Radar can detect speed accurately and reliably even at long distances, a capability that is harder for Lidar to achieve.
5. Environmental Adaptability
Lidar: Lidar’s use of light waves makes it vulnerable to weather conditions such as fog, rain, and snow, which can scatter or absorb the laser pulses, reducing its range and accuracy. This sensitivity to environmental interference is a significant limitation, particularly in outdoor applications where visibility might be poor.
To address this, some hybrid systems combine Lidar with other sensors (like Radar or cameras) to mitigate its weaknesses in challenging weather conditions. However, these integrations increase system complexity and cost.
Radar: Radar’s radio waves are far less affected by environmental conditions, allowing it to function in all weather and through obstacles. Radar’s robustness makes it indispensable in fields like aviation, maritime navigation, and meteorology, where consistent performance is essential regardless of weather. Its ability to maintain accuracy in conditions where Lidar struggles gives Radar a distinct advantage in environments with unpredictable weather.
6. Cost and Complexity
Lidar: The high cost of Lidar is driven by the precision lasers, detectors, and mechanical components (such as rotating mirrors) needed for scanning. Additionally, the large volumes of data generated by Lidar require substantial computational resources for processing and analysis. This makes Lidar systems not only expensive to implement but also challenging to maintain(4.LiDAR vs RADAR).
The complexity of Lidar also extends to calibration and maintenance, especially in outdoor settings where environmental factors can quickly degrade the sensors' accuracy. For applications like autonomous vehicles, this can pose significant operational challenges, as frequent calibration may be required.
Radar: Radar systems are generally less expensive and simpler to operate compared to Lidar. The core components—transmitters, receivers, and antennas—are more affordable and require less sophisticated hardware. Furthermore, Radar’s electronic beamforming capabilities eliminate the need for mechanical parts like rotating mirrors, simplifying the system’s design.
Radar systems are also easier to maintain, as they are more resistant to environmental degradation and do not require frequent recalibration. This makes Radar a cost-effective option for large-scale applications, especially in long-range or outdoor environments where simplicity and reliability are key.
7. Use Cases
Lidar Applications
1. Autonomous Vehicles: Lidar is a core technology in self-driving cars. Its ability to generate real-time 3D maps allows vehicles to detect objects, pedestrians, and obstacles with high precision, enabling safe navigation.
2. 3D Mapping and Surveying: Lidar provides accurate topographic maps for urban planning, forestry, and environmental monitoring. Its high-resolution data is also crucial for applications like disaster management and infrastructure assessment.
3. Archaeology and Heritage Preservation: Lidar’s non-invasive mapping capabilities have revolutionized archaeological discoveries, allowing researchers to uncover ancient structures hidden under dense forests.
4. Forestry and Vegetation Analysis: Lidar is widely used for forest health assessment and resource management. By penetrating the tree canopy, Lidar provides detailed data on tree height, crown diameter, and leaf area. This data helps monitor forest health, biomass calculations, and supports conservation efforts. Lidar is also valuable for identifying areas at risk of erosion and natural hazards
Radar Applications
1. Aviation and Air Traffic Control: Radar is the backbone of aviation safety, providing precise tracking of aircraft, even in poor visibility conditions. Ground-based and airborne Radar systems ensure safe navigation by monitoring aircraft positions, altitudes, and speeds.
2. Maritime Navigation: Radar systems help ships detect other vessels, obstacles, and land features, ensuring safe passage in congested waterways or during poor weather.
3. Weather Monitoring: Radar plays a key role in meteorology, tracking storms and precipitation patterns. Doppler radar, in particular, is critical for detecting severe weather conditions like tornadoes and thunderstorms.
4. Military and Defense: Radar has long been integral to military applications, such as surveillance, target detection, and missile guidance. Advanced systems like Synthetic Aperture Radar (SAR) provide high-resolution imaging, supporting reconnaissance and situational awareness. Radar’s robustness makes it essential for air defense and battlefield monitoring.
5. Automotive Safety Systems: In the automotive sector, Radar supports Advanced Driver Assistance Systems (ADAS), improving vehicle safety. Radar enables features like adaptive cruise control, collision avoidance, and lane departure warnings. It enhances driver awareness by detecting nearby vehicles, pedestrians, and obstacles, helping prevent accidents.
Conclusion: Lidar vs Radar, which is better?
Lidar:
· Advantages: High accuracy and resolution, excellent for detailed 3D mapping (e.g., autonomous vehicles, surveying).
· Disadvantages: Sensitive to weather, higher cost.
Radar:
· Advantages: Long-range detection, reliable in all weather conditions (e.g., aviation, maritime, weather monitoring).
· Disadvantages: Lower resolution, less effective for detailed object detection.
How to Choose:
· Use Lidar when precision and detail are critical in controlled environments.
· Use Radar when long-range, all-weather reliability is key.
In many cases, combining both technologies (sensor fusion) offers the best solution, leveraging Lidar's precision and Radar's robustness.
Nov 06, 2024
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