Chairman and CEO Vimal Kapur on February 6 announced the plan to pursue a full separation of Automation and Aerospace Technologies, adding to the previously announced plan to spin-off Advanced Materials,

The move will result in three publicly listed companies with distinct strategies and growth drivers. The company said in a press release that the separation is intended to be completed in the second half of 2026 and will be done in a manner that is tax-free to Honeywell shareholders.

“The formation of three independent, industry-leading companies builds on the powerful foundation we have created, positioning each to pursue tailored growth strategies, and unlock significant value for shareholders and customers,” said Vimal Kapur, Chairman and CEO of Honeywell. “Our simplification of Honeywell has rapidly advanced over the past year, and we will continue to shape our portfolio to create further shareholder value. We have a rich pipeline of strategic bolt-on acquisition targets, and we plan to continue deploying capital to further enhance each business as we prepare them to become leading, independent public companies.”

Honeywell says the planned separations of automation, aerospace and advanced materials will deliver a slew of benefits, including simplified strategic focus and greater financial flexibility to pursue distinct organic growth opportunities through investment.

Honeywell Automation will create the buildings and industrial infrastructure of the future, leveraging process technology, software, and AI-enabled, autonomous solutions, said Kapur. “As a standalone company with a simplified operating structure and enhanced focus, Honeywell Automation will be better able to capitalize on the global megatrends underpinning its business, from energy security and sustainability to digitalization and artificial intelligence.”

Honeywell says it’s aerospace company will see unprecedented demand in the years ahead from commercial and defense markets, making it the right time for the business to operate as a standalone, public company. “Today’s announcement is the culmination of more than a century of innovation and investment in leading technologies from Honeywell Aerospace that have revolutionized the aviation industry several times over. This next step will further enable the business to continue to lead the future of aviation.”

Here’s a look at how each of the three new companies will operate:

Honeywell Automation: Positioned for the industrial world’s transition from automation to autonomy, with a comprehensive portfolio of technologies, solutions, and software to drive customers’ productivity. Honeywell Automation will maintain its global scale, with 2024 revenue of $18 billion. Honeywell Automation will connect assets, people and processes to push digital transformation.

Honeywell Aerospace: Its technology and solutions are used on virtually every commercial and defense aircraft platform worldwide and include aircraft propulsion, cockpit and navigation systems, and auxiliary power systems. With $15 billion in annual revenue in 2024 and a large, global installed base, Honeywell Aerospace will be one of the largest publicly traded, pure play aerospace suppliers.

Advanced Materials: This business will be a sustainability-focused specialty chemicals and materials company with a focus on fluorine products, electronic materials, industrial grade fibers, and healthcare packaging. With nearly $4 billion in revenue last year, Advanced Materials offers leading technologies with premier brands, including its low global warming Solstice hydrofluoro-olefin (HFO) technology.

Honeywell says it remains on pace to exceed its commitment to deploy at least $25 billion toward high-return capital expenditures, dividends, opportunistic share purchases and accretive acquisitions through 2025. The company says it will continue its portfolio transformation efforts during the separation planning process.

Since December 2023, Honeywell has announced a number of strategic actions with about $9 billion of accretive acquisitions, including the Access Solutions business from Carrier Global, Civitanavi Systems, CAES Systems, and the liquefied natural gas (LNG) business from Air Products. Honeywell will continue with its planned divestment of its Personal Protective Equipment business, which is expected to close in the first half of 2025.

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Robot adoption in factories around the world continues soar, according to a new report by the International Federation of Robotics (IFR).

The World Robotics 2024 report shows the new global average robot density reached a record 162 units per 10,000 employees in 2023, more than double the 74 units measured in 2017.

Robot density is a way to track the degree of automation adoption in the global manufacturing industry. Takayuki Ito, president of the International Federation of Robotics, says Korea and Singapore were the leaders in robot adoption, with China, Germany and Japan rounding out the top five.

The report says the European Union has a robot density of 219 units per 10,000 employees, an increase of 5.2%, with Germany, Sweden, Denmark and Slovenia in the global top ten.

North America’s robot density is 197 units per 10,000 employees – up 4.2%.  With a robot density of 295 units, the U.S. ranks eleventh among the most automated countries in the manufacturing sector.

Asia has a robot density of 182 units per 10,000 persons employed in manufacturing – an increase of 7.6%. Korea, Singapore, mainland China and Japan are among the top ten most automated countries.

Top countries for robot density

The Republic of Korea is the world’s number one adopter of industrial robots with 1,012 robots per 10,000 employees. Robot density has increased by 5% on average each year since 2018. With a world-renowned electronics industry and a strong automotive industry, the Korean economy relies on the two largest customers for industrial robots.

Singapore follows with 770 robots per 10,000 employees. Singapore is a small country with a very low number of employees in the manufacturing industry, so it can reach a high Robot density with a relatively small operational stock.

China took third place in 2023, surpassing Germany and Japan. The country’s push for automation technology results in a density of 470 robots per 10,000 employees. China entered the top 10 in 2019 and has doubled its robot density within four years.

Germany ranks fourth with 429 robots per 10,000 employees. The robot density of Europe’s largest economy has grown by 5% CAGR since 2018.

Japan is in fifth place with 419 units. Robot density of the world’s predominant robot manufacturing country grew by 7% on average each year (2018-2023).

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Danish cobot maker Universal Robots has unveiled its AI Accelerator, a ready-to-use hardware and software toolkit created to further enable the development of AI-powered cobot applications.

Designed for commercial and research applications, the UR AI Accelerator provides developers with an extensible platform to build applications, accelerate research and reduce time to market of AI products.

The toolkit brings AI acceleration to Universal Robots’ (UR) next-generation software platform PolyScope X and is powered by NVIDIA Isaac accelerated libraries and AI models, running on the NVIDIA Jetson AGX Orin system-on-module. Specifically, NVIDIA Isaac Manipulator gives developers the ability to bring accelerated performance and state-of-the-art AI technologies to their robotics solutions. The toolkit also includes the high-quality, newly developed Orbbec Gemini 335Lg 3D camera.

Through in-built demo programs, the AI Accelerator leverages UR’s platform to enable features like pose estimation, tracking, object detection, path planning, image classification, quality inspection, state detection and more. Enabled by PolyScope X, the UR AI Accelerator also gives developers the freedom to choose exactly what toolsets, programming languages and libraries they want to use and the flexibility to create their own programs.

UR says AI Accelerator is just the first to market of a series of AI-powered products and capabilities in UR’s pipeline with the goal of making robotics more accessible.

With a small hardware upgrade, the software is compatible with UR’s e-Series cobots and the new-generation cobots UR20 and UR30.

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“By coming together, we recognize that there is an exceptionally bright future as one company, and the name ‘Evolution’ is something that truly represents who we need to be for our customers and who we will be in the future,” explains Matt Oldroyd, CEO of Evolution. “As we leverage our collective experience and deep histories, becoming Evolution is the next step to expanding our platform of technical expertise, capabilities, and growth that will create a significant advantage for our customers and supplier partners moving forward.”

Evolution, built on the rich histories of its predecessor companies, draws from over a century of brand equity, ethos, and customer trust, signifying the company’s commitment to adapting and evolving with its customers. With 20 locations, Evolution serves 31 U.S. states and one Canadian province, providing customers with access to a comprehensive range of solutions designed to improve productivity, reliability, and performance.

“This rebrand marks an exciting milestone in the journey of two outstanding companies,” adds Oldroyd. “By unifying our expertise as Evolution Motion Solutions, we’re positioned to innovate more effectively and deliver even greater value to our customers across a diverse range of industries. We’re excited about the expanded capabilities this rebrand brings as we continue building our legacy as Evolution.”

Though Evolution does not manufacture its customers’ systems and machines, the company plays a vital role in helping them run more efficiently and reliably. This rebrand is a step forward in Evolution’s mission to empower its customers with innovative, future-focused solutions that allow them to achieve more than they ever thought possible.

Evolution Motion Solutions is the new name for the Womack Group of companies, including Womack Machine Supply, Morrell Group, Morrell Industrial, Stegner Controls, LOR Mobile Controls, Womack Systems, Womack Defense, and Stegner Aerospace. Going forward, all legacy company names will be retired, and all operations will be conducted under the Evolution brand.

For more information, visit evolutionmotion.com.

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Industrial robots and their end effectors have demonstrated a remarkable dexterity, matching and often exceeding that of human hands. Combined with vision systems, many industrial robots can combine high-level dexterity with object recognition for pick and place applications, but most industrial systems, the things that robots manipulate are consistent in size and shape.

The food processing industry has a very different problem: individual portions of things like fish fillets are similar, but no two are alike. The technology however is rapidly improving, and modern systems can now handle complex food processing tasks that until recently have resisted automation. 

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Every manufacturing engineer considering an IIoT implementation should put considerable focus into how the systems contribute to data collection, real-time decision-making and automated control within the production environment.

Sensors are the eyes and ears of your operation. These data collection devices continuously monitor various physical or environmental parameters on the shop floor. Sensors have been developed to measure almost any condition on the shop floor. Here are some common types:

Temperature (for controlling furnaces or ovens)

Pressure (for monitoring hydraulic or pneumatic systems)

Vibration (for detecting imbalance in motors or machinery)

Humidity (for ensuring optimal conditions in certain manufacturing processes)

Proximity (for part detection on a conveyor belt or pallet)

Torque and Force (for ensuring precise assembly or machining)

These days, most sensors provide real-time data that are essential for understanding the status of machines, the health of equipment and the quality of products.

Sensors can capture data continuously or at regular intervals, feeding it back to a centralized system or edge devices. This data allows you to monitor machine performance and production quality in real-time. By continuously monitoring conditions such as temperature, vibration and pressure, sensors can help predict equipment failures before they happen—enabling predictive maintenance strategies. This minimizes downtime and unplanned repairs. Sensors can also ensure product quality by tracking parameters such as size, weight or chemical composition, ensuring products are within acceptable tolerances.

The data collected by sensors is sent to centralized cloud systems or edge devices for real-time analysis, enabling manufacturers to make informed decisions on production adjustments and process improvements.

Actuators: The Hands of Your IIoT System

Once sensors collect and transmit data, actuators play the critical role of executing actions based on the data received. Actuators are devices that respond to control signals by performing physical tasks, including:

Opening or closing a valve (to control fluid or gas flow in a pipeline)

Adjusting motor speeds (for conveyor belts or robotic arms)

Turning machines on or off (for automated start/stop of equipment)

Controlling temperature (by activating heating or cooling systems)

Moving robotic arms or equipment (for assembly, material handling or other precision tasks)

In an IIoT system, actuators are responsible for automating responses to specific conditions detected by sensors. This creates the foundation for closed-loop control systems that can operate independently of human intervention. For example, if a temperature sensor detects overheating, the actuator could activate a cooling system without manual intervention. This automation reduces human labor and the chances of errors or inefficiencies in production. It also speeds up response times to deviations, minimizing waste and downtime.

Actuators can also adjust machine settings dynamically. For example, based on real-time data, they can modify the speed or pressure of a machine, ensuring the production process adapts to the changing needs of the workflow.

In more advanced IIoT setups, edge computing and AI-driven algorithms use sensor data to make autonomous decisions, triggering actuators without human oversight. This could be as simple as adjusting a process or as complex as rerouting products based on real-time data streams.

Working together in IIoT

In a typical IIoT system, the interaction between sensors and actuators follows a continuous cycle of data collection and response, which is often referred to as closed-loop control. Here’s an example:

Sensors detect changes: A temperature sensor detects that the temperature in a furnace is rising above the set threshold.

Data is sent: The sensor transmits this information to the controller (either an edge device or cloud platform) in real-time.

Data is analyzed: The controller analyzes the data and determines that corrective action is needed (e.g., the furnace is overheating).

Actuator takes action: Based on the analysis, the controller sends a signal to an actuator that opens a valve to release cooling air or turns on a cooling system.

Process adjustment: The actuator performs the task, and the sensor continues to monitor the process, feeding back data to ensure the temperature returns to safe levels.

Benefits of sensors and actuators in manufacturing

Increased Production Efficiency:

Sensors and actuators enable real-time adjustments to processes, ensuring that machines operate within optimal parameters. This minimizes downtime and keeps production flowing smoothly.

Enhanced Predictive Maintenance:

Continuous data from sensors allows for early detection of wear and tear or impending failures, reducing the need for reactive maintenance and minimizing unexpected breakdowns. Actuators can automatically adjust processes to prevent equipment damage.

Improved Quality Control:

Sensors track key quality metrics, and actuators can adjust the process instantly to ensure product quality remains consistent, reducing waste and scrap.

Operational Flexibility:

Sensors and actuators provide greater control over manufacturing systems, enabling them to respond flexibly to changes in production schedules, environmental factors, or even supply chain disruptions.

Cost Reduction:

Automation through sensors and actuators can lower labor costs and reduce human error. Moreover, optimized processes lead to less material waste, contributing to overall cost savings.

Data-Driven Decision Making:

By integrating sensors and actuators with a central data system (cloud or edge-based), manufacturers can leverage real-time analytics to gain actionable insights and make informed decisions to improve efficiency and productivity.

Common challenges

Let’s face it, maintaining a network of sensors and actuators and similar technology in a manufacturing environment can be tricky. Many environmental and workflow factors can result in degraded performance, even if they aren’t integrated into a broader IIoT implementation.

However, in IIoT manufacturing systems, several challenges are directly related to the integration of sensors and actuators into the broader industrial network. One key issue is communication latency and bandwidth limitations. IIoT systems rely heavily on real-time data transfer between sensors, actuators and control systems. Latency or insufficient bandwidth can delay data transmission or actuator responses, which is particularly troublesome in time-sensitive applications where quick reactions are essential.

Another challenge is connectivity and reliability issues. Since IIoT systems often involve wireless communication (e.g., Wi-Fi, LPWAN, or other IoT protocols), connectivity problems like signal dropouts, weak coverage or protocol incompatibility can disrupt the flow of critical data. In a networked environment, these disruptions can lead to missed sensor readings or commands not reaching actuators, causing downtime or unsafe conditions.

The sheer volume of data generated by IIoT devices can also lead to data overload and management challenges. With sensors constantly transmitting data, storage and processing systems can quickly become overwhelmed, making it difficult to extract actionable insights or react quickly to system needs. This can hinder operational efficiency, slow decision-making, and complicate data analysis.

Security vulnerabilities are another significant concern in IIoT systems. As sensors and actuators become more interconnected, they are exposed to potential cyber threats. Hackers could access the network to manipulate sensor data or control actuators, posing serious risks to both data integrity and physical safety.

Lastly, sensor and actuator compatibility can be an issue when integrating devices from different manufacturers or upgrading legacy systems. IIoT environments require seamless communication between different components, and incompatible sensors, actuators or communication protocols can lead to integration problems, system inefficiencies or even failures in real-time operations.

To address these challenges, best practices include using real-time networking protocols, implementing strong cybersecurity measures, employing edge computing to process data closer to the source, and ensuring that systems are compatible and interoperable across the IIoT network. These steps help ensure that the IIoT infrastructure operates reliably and efficiently.

The post What are the roles of sensors and actuators in IIoT? appeared first on Engineering.com.

Experienced design engineers can certainly estimate cycle times, throughput, quality and uptime. However, the complexity of processes and associated controls leave plenty of room for fine-tuning during engineering and after installation. It should be noted that optimization is not the same as continuous improvement. Optimization is refinement conducted on a current process where continuous improvement generally refers to changes to the process or systems. These can be done concurrently but it is best to optimize first and then concentrate on continuous improvement.

Simulation and modeling

System simulation after initial design can be used quite effectively before the final design is complete. Simulation time and costs should be worked into a project whenever possible as the payback can be quite significant. These tools can be used to test and validated designs. Identifying potential issues at the design stage can reduce the risk of costly mistakes that could delay commissioning or cause problems afterwards. Simulation can be used to evaluated machining and automation processes and serve as a tool to facilitate conversations through the project.

Process Analysis and Mapping: Some simulation can be detailed enough to be considered a “Digital Twin” of the system. Digital Twins allow for even more detailed simulations to take place. System behaviour can be evaluated under very specific conditions and inputs creating a map that enables continuous optimization and testing without disrupting actual operations. As well, a properly designed and updated Digital Twin can then operate simultaneously with an actual system providing some future predictability.

Current State Analysis: Models encourage designers to more thoroughly understand existing processes. Creating an accurate model involves documenting every step, input, output, and resource used within the system. The goal is to have a clear and comprehensive overview of how the system operates. This in turn sets the foundation for identifying areas of improvement.

Once the process is mapped out and simulated, designers can identify points in the process where delays or inefficiencies occur. These could be due to machine limitations, inadequate supply of materials, or other factors that slow down the process. By visualizing the flow of materials and information through the system, designers can enhance and streamline processes and eliminate waste.

Data monitoring and collection

An often-neglected step in the improvement process is proper and accurate data monitoring and collection. A logical and systematic approach is required with emphasis on using the proper tools for the job. If good data is not collected, the subsequent analysis will be flawed. It is extremely important to try and understand what data is needed and how accurate that data must be. A camera system, for example, intended for use as image collection or shape recognition may not be able to measure dimensional attributes for quality purposes.

Sensor Integration: Integrating sensors into machinery and processes allows for real-time data collection of various parameters such as temperature, pressure, speed, and more. This data is crucial for determining system performance and possibly identifying areas for improvement. Forward planning will help reduce costs by designing in connections and associated hardware during equipment build.

Analysis: Once the data is collected, advanced analytics can be used to help identify patterns, trends, and anomalies. Deviations from expected performance metrics may indicate issues that need addressing. Analysis can be performed on-site or even remotely by a third parts that specializes in big data collection and analysis. Modern AI learning algorithms can now proactively predict potential equipment failures before they occur minimizing downtime and even extending the lifespan of machinery. Monitoring robot joint motor performance, for example, can be used to trigger a preventative maintenance activity before a problem leads to a significant breakdown.

PLC systems

Coding: Writing code is not necessarily difficult, however, writing efficient, modular, and well-documented PLC code takes time, planning and experience. Good coding techniques is crucial to make the code easier to maintain and modify, reducing the likelihood of errors and enhancing system reliability.

Error Handling and Debugging: Robust error handling routines are essential for quickly identifying and resolving issues by operator and maintenance personal. This must be specified early as a great deal of time and effort is required. The payback is reduced downtime and smooth systems operation.

Human-Machine Interface (HMI): Designing intuitive and user-friendly interfaces makes it easier for operators to control and monitor systems. This can reduce the likelihood of operator errors and improve overall system efficiency. Providing real-time feedback and alerts to operators allows for quick responses to issues. This can include notifications about performance deviations, maintenance needs, or system faults.

Automation and robotics optimization

Path Optimization: It is important that path creation is done by experts. However, in many robotic systems, there will still be room for improvement. Optimizing the movement paths can significantly reduce cycle times and energy consumption. This involves programming robots to take the most efficient routes. Using joint moves can be faster then calculated linear or curved routes. However, creating intermediate points can sometimes force a robot to behave less erratically.

Cycle Time Reduction: Streamlining operations to reduce the time taken for each cycle of operation increases overall throughput. This can involve optimizing tool changes, reducing setup times, and eliminating redundant steps. The goal is to minimize unnecessary movements and dwells times to reduce non-value added motion.

Continuous improvement and lean methodologies

Many companies follow specific techniques to refine processes. Regardless of the methodology employed, most can be used for both optimization and continuous improvement. It should be noted that these are only tool to effectively create positive change but specific expertise in the specific method is necessary. A culture of improvement is a tremendous benefit and should not be discounted. Some examples are:

Kaizen: Implementing a culture of continuous improvement, known as Kaizen, encourages regular evaluation and enhancement of processes. This approach focuses on making small, incremental changes that collectively lead to significant improvements. The process is allowed to stabilize before moving onto the next development opportunity. Since this approach represents a culture, it does not matter if the target is quality, maintenance, cycle time, operation or some other enhancement.

Six Sigma: Utilizing Six Sigma methodologies helps reduce process variation and eliminate defects. This is a data driven focused process using a statistical approach in decision-making to improve process quality and efficiency. Although this method is mainly targeted to process improvements that effect quality, a thorough analysis of data can lead to discoveries in many areas that can be a benefit.

By advance planning and the careful implementation of some of these strategies, organizations can achieve significant improvements in the performance, efficiency, and reliability of their automation systems and associated processes. A holistic approach, involuting multiple tools and a variety of personnel can enhance productivity and minimize waste.

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According to Stanford University’s Artificial Intelligence Index Report 2023, in 2017, only 2.8% of all newly installed industrial robots were collaborative. By 2021, that number had increased to 7.5%. The global trend toward robots working with humans to support a range of more flexible applications continues to fuel the impressive growth of the cobot industry as part of the digital transformation of the manufacturing industry.

Part of this growth can be attributed to ongoing workforce challenges in the North American manufacturing industries. The 2024 Deloitte and the Manufacturing Institute Talent Study reported that attracting and retaining talent has remained a primary business challenge for manufacturers since before the pandemic, including in skilled positions.

• While traditional industrial robots require complex installation and dedicated, restricted cells separated from workers, cobots offer many flexibility benefits that make them more attractive to manufacturing leaders looking to make smaller, more manageable investments in automation. Some flexibility features of cobots include:
  User-friendly, no-code programming and control interfaces
• Built-in safety features that allow humans to work inside the robot envelope during operation
• Designed to be redeployable, such as being mounted on a cart and moved to different task areas
• Built-in force sensing, making certain tasks simpler without the need to configure third-party sensors
• As cobots typically don’t replace workers, cobots can have a positive effect on employees’ perception of automation and the changes automation may bring in the workplace

With so many benefits for flexible, bite-sized automation, cobots can be an ideal entry point to the world of automation for manufacturers addressing skills gap challenges, or a solution for highly automated, smart factories looking for the next value add in niche applications such as screw assembly or buffing and grinding.

Latest cobot product announcements

Schneider Electric Lexium

Image: Schneider Electric

Unveiled in April 2024 at MODEX, the two new Lexium cobots offer payloads of 3 to 18 kg, with positioning accuracy of +/- 0.02 mm (+/- 0.00079 in.) and operating radius up to 1073mm. The robots use Schneider’s EcoStruxure architecture, which connects smart devices, controls, software and services for collaborative data flow and shop-floor to top-floor machine control.

Doosan Robotics Prime-Series Cobots

Image: Doosan Robotics

The Doosan P-Series is, according to the company, the longest-reaching cobot available, with a reach of 2030mm. The P-series has a payload of 30 kg and is primarily designed for palletizing applications. Features of the P-Series cobot include lower power consumption compared to similar payload cobots by applying its built-in gravity compensation mechanism, inherent wrist-singularity free, and a 5 degree-of-freedom movement with the 4th axis removed and 6th axis speed increased to 360 degrees/second. The P-Series also includes PL (e) and Cat 4 safety ratings.

Kawasaki Robotics CL Series Cobots

Image: Kawasaki Robotics

Kawasaki Robotics’ CL Series are powered with NEURA Robotics’ robot assistance technology and feature speed of 200°/s and repeatability of ± 0.02 mm with payloads and reaches of 3kg/590mm, 5kg/800mm, 8kg/1300mm, and 10 kg/1000mm. They offer free mounting orientations, extremely small footprints and IP66 classification. Applications for the CL Series robots include finishing, parcel sorting and palletizing/depalletizing.

FANUC CRX-10ia/L Paint

Image: Fanuc

The latest addition to FANUC’s CRX line of cobots, the 10ia/L, has a payload of 10kg, reach of 1418mm and is the first collaborative paint robot to comply with explosion-proof safety standards (including IECEx, ATEX, U.S., Canada, Japan, Korea, China, Taiwan and Brazil). Meant for high-mix, low volume paint applications, even for operators with little to no robotics experience. Its “easy-teach” features including drag-and-drop programming and lead-to-teach (which may be considered a standard feature on most cobots.) In addition to painting, the robot can also be deployed for powder and liquid coating applications.

Universal Robots UR30

Image: Universal Robots

Universal Robots developed the very first collaborative robot and continues to expand its product line with the UR30, offering a 30 kg payload and 1300mm reach. According to the company, the design of the UR30 is smaller and more compact than comparable cobots, because of the importance of flexibility in collaborative robot applications. The UR30 is part of the company’s growing portfolio of products, joining the UR3e, UR5e, UR10e, UR16 and UR20

Techman Robot TM30

Image: Techman Robot

Techman Robot’s TM30 has a payload of 35 kg and reach of 1702mm. With this high reach-to-weight ratio, the TM30 is ideal for palletizing applications. According to the announcement, an ideal application is the semiconductor backend process, which includes significant manual labor for lifting and loading wafer boxes up to 35 kg. Techman robots integrate proprietary AI Vision technology, providing a series of add-on software tools for safety, incoming part positioning, barcode reading, dimension measurement and visual inspection.

Delta D-Bot Series

Image: Delta

At Hanover Messe 2024, Delta, a leader in power management and a provider of IoT-based smart green solutions, announced a new line of six collaborative robots, with payloads ranging from 6 to 30 kg and reach ranging from 800 to 1800mm. These six-axis robots offer speeds up to 200 degrees per second and accuracy within ±0.02mm. The robots offer “plug-and play” installation and a user-friendly interface designed for non-technical personnel. Applications include palletizing, pick-and-place and welding.

What’s Next for Cobots?

Robotics-as-a-Service (RaaS), which mimics the popular subscription model transforming the software and cloud service industries, should continue to grow as more small companies dive into automation. Another key technology poised to deeply impact industrial robotics is AI prompt engineering. As robot control software continues to trend away from code and toward user-friendly interfaces, the idea of prompting an AI to teach or program the robot to perform an operation is not far off.

No matter what the future holds, collaborative robots remain a solution for manufacturers looking to automate dull, dirty and dangerous tasks, without taking on a large traditional robotic automation project.

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Executives and decision makers know it’s not easy to automate industrial processes, but what they may not understand is why. The challenges arise from the fact that most facilities are made up of bespoke machines used to make specific parts, products or assemblies. Hence, there is rarely a one-size-fits-all solution.

Obvious examples of this phenomena can be seen with grippers, effectors and tools that physically interact with products or parts. This equipment must be tailored to hold, move and manipulate an object with specific geometry. But specialization doesn’t end there. An often-overlooked piece of customized equipment are industrial automation control panels. Afterall, if the control panel operates custom machinery, it makes sense that it also needs to be customized.

But these modifications aren’t easy. A search of Jameco, a supplier of industrial automation parts, for products only from MEAN WELL, which is just one of their manufacturing partners, comes up with almost 6,400 results. So, how does anyone make sense of it all?

To understand control panels and how one would go about customizing them for a particular application, engineering.com sat down with Gil Orozco, vice president of Product Management at Jameco and Harland Chen, field application engineer at MEAN WELL.

What is an industrial automation control panel?

Industrial automation control panels act as a central hub for all the components and tools used to monitor, instruct and integrate machinery. “Industrial automation control panels are the backbone of automation,” says Chen. “Panels enhance the efficiency, productivity, safety and quality of the system.”

Just like the machines they operate; panel parts need to be uniquely selected to meet particular needs. “The specific components used will depend on the intended function and complexity of the control panel,” confirms Orozco. “Customer applications are endless. [Selecting the right components] depends on what the customer requires.”

Even though contents can vary, control panels typically consist of:

• Circuit breakers and fuses, which cut the power supply in the event of excess current or faults in the system. This is done to protect other circuitry.
• Switches and/or buttons, which make up parts of the human machine interface (HMI) that enables human operators to manually control or preset operations.
• Indicators, which contain LED lights, computer monitors and gauges. These HMI parts are used to keep human operators informed of the status of the facility’s equipment.
• Power supplies, which includes the electrical batteries, generators and/or grid connections needed to ensure components operate.
• Control relays, which help control high-power devices or circuits with low power signals.
• Terminal blocks, which provide access points to connect and secure wires and cables.
• Programmable logic controllers (PLCs), which are advanced automation and control circuits used to manage equipment and systems based on measured inputs and code.

With the rise of Industry 4.0, many of these control panel components have become smarter. They can communicate with digital systems, connect to the Industrial Internet of Things (IIoT) and even digest data, predict performance or make decisions on how to operate. “The components are really in some respect endless,” says Orozco. “In some [instances], you have very smart components [and others] where you have some very basic analog components. So, it really starts with the customer’s application. How we make sense of all that depends on what the customer needs and how can we support them.”

In other words, each of the above parts must be optimized to the task being controlled by the panel. And since there are hundreds, maybe thousands of options for each part, engineering expertise is needed to ensure the panel is optimized to its needs.

What role do control panels play in industrial automation?

Control panels act as the brain and central nervous system of an automated facility. They regulate and manage systems using hardware, software and input data from HMIs, sensors, cameras and more. A control panel need not be fully automated. Some require human interactions, others can be autonomous, and many fall somewhere in between.

Chen explains, “By integrating the programming logic controls, the human machine interface … and various sensors and alternators, the control panels enable the real-time data acquisition and a precise control of the industrial operation.”

So, the benefits of the fully automated systems are that they offer consistent, precise and accurate control. In contrast, systems with human interactions may involve industrial operations that can be more unpredictable, requiring the oversight of human operators who can quickly adapt to a situation.

Automation control panel safety, compliance and regulations

Strict safety, compliance and regulation standards exist to prevent control panels from causing electrical shocks, fires and damage to people or property. “The control panel must adhere to this compliance and regulation to ensure safe operations,” Chen explains. Control panels require “electrical safety, proper grounding and protection against flash cases. Compliance with standards like UL 508A in the U.S., or ‘CE markings’ in Europe and the CSA certification in Canada are essential.”

He also notes the importance of ensuring the electronics operate at safe temperatures, meet environmental safety requirements and have ingress protection (IP) ratings — which measures how well an electrical device is protected from water or dust.

Since so much customization comes into play when finding the right automation control panel, ensuring that it meets safety, compliance and regulation standards is not easy. So once again, engineering expertise is required to guarantee success.

Engineering expertise for industrial control panels

Jameco offers almost 60 different DIN rail terminal blocks from MEAN WELL alone. When other manufacturing partners are included in the search, the number increases by a factor of three.  So, how does anyone know which control panel parts are needed for their particular setup?

Chen and Orozco suggest contacting Jameco and MEAN WELL directly. “It boils down to the customer’s needs,” says Orozco. “Applications and components are endless and there are many different brands and options … We need to understand the [given] application to provide a solution to the customer. And that’s where Jameco and MEAN WELL come in … We take an approach to understanding the customer’s requirements to show what total solutions we can offer them.”

Chen used the example of sizing a power supply. “The power supply we evaluate is based on the necessary functionalities of the [given] control panel. We consider the components, space [and] installation of the power supply.”

With the help of Jameco and MEAN WELL, manufacturers can make sense of all the available options, components and customizations they can add to their control panels. Instead of being lost in a forest of part numbers and compliance documentation, they will see a path to the right solution for a given situation.

“We evaluate based on the region, power and customer,” adds Chen. “If the customer needs to meet a specialized safety standard, our factories in China and Taiwan offer the certification needed for the specific safety and power supply standard.”

For more information on automation control panels solutions, read more about industrial power components.

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(Image: ARM Institute)

When the ARM Institute launched its Robotics Manufacturing Hub about a year ago, it quickly realized that manufacturers weren’t looking at robotics and automation because they weren’t interested in robotics, but rather the barriers to automation loomed so large that it was impossible for small and medium sized firms to know where to start. When the ARM Institute announced its no-cost Robotics Manufacturing Hub for manufacturers in the Pittsburgh region, its pipeline of interested manufacturers rapidly filled. With the ARM Institute offering a pathway to minimize the risks they associate with robotics and automation, manufacturers were, and still are, eager to explore the possibilities.

Larger manufacturing firms can more easily navigate the process of implementing automation. With greater general resources, in-house R&D, financing to invest in the upfront costs, and more time to explore solutions, they’ve more successfully been able to see the process through from start to finish. Small and medium-sized firms have to navigate more risk. They need to spend more time understanding how the changes will impact their operations, they often lack in-house robotics expertise, and they need solutions that will dynamically meet their needs without requiring constant upkeep when, in many cases, their workforce is already strained.

The ARM Institute’s Robotics Manufacturing Hub is a free resource that helps manufacturers navigate these barriers and others by identifying the best business cases for robotic solutions, testing the solutions within the manufacturer’s budget, and offering a path to implementation. Part of this solution includes the ability for small and medium sized manufacturers in the Southwestern Pennsylvania region to work directly with the ARM Institute’s team of robotics engineers and get hands-on with advanced technologies in the institute’s Pittsburgh facility.

Select Case Studies

Since the Robotics Manufacturing Hub’s creation around one year ago, the ARM Institute has worked with several manufacturers in the Pittsburgh region to explore their challenges and help them understand where robotics can address these challenges.

For example, the ARM Institute worked with a manufacturer of castings and forgings to automate its manual quality inspection process. Partnering with FARO and NEFF Automation through the Robotics Manufacturing Hub, the ARM Institute performed a proof-of-concept of a Universal Robot controlling a FARO laser scanner. The manufacturer plans to pursue implementation.

The ARM Institute also worked with a company that needed to package heavy iron and steel parts into shipping containers, creating an ergonomically uncomfortable task for a human worker. In this situation, requirements for the robotic end effector are highly specific and it’s critical to calculate the correct pick place on the parts and speed limitations of the robot to move heavy parts and prevent failure or injury. The ARM Institute is working with its member CapSen Robotics on a solution.

Inside the Physical Robotics Manufacturing Hub Facility

Much of this work is completed using the ARM Institute’s Pittsburgh facility as a neutral ground for exploration and prototyping, giving manufacturers access to equipment before they commit to installing any system.

This facility is modular, adaptable, and multi-use with OEM diversity to directly meet each manufacturer’s individual needs. ARM Institute engineers work directly in the lab and interface between suppliers and manufacturers to act in the manufacturer’s best interest and ensure that the work will address the specific challenges the manufacturer is facing.

Below is a brief overview of the equipment available through the Robotics Manufacturing Hub and application areas that can be addressed using this equipment: 

Collaborative Robots (cobot) Equipment:

• Universal Robots (UR) 5e
• Yaskawa HC10
• Fanuc CRX-10 Ai/L
• Fanuc CRX-20 Ai/L

The collaborative robots can be configured for the following applications:

• Small part handling
• Pick and place
• Vision guided grasping for pick and place applications
• Machine tending
• Process tasks including glueing and dispensing
• Inspection with Faro ARM Quantum with Laser line probe and CMM
• Inspection with Cognex 2D imaging
• Inspection with Cognex 3D imaging

Industrial Robots

• Epson VT6L
• Yaskawa GP-88
• Yaskawa GP-180
• Yaskawa Weld Cell with positioner

The industrial robots can be configured for the following applications

• Large part handling
• Large part palletizing
• Large part pick and place
• Force controlled grinding and polishing
• Welding

How to Get Involved

Small and medium sized manufacturers in the Pittsburgh region can get a free automation assessment and leverage the Robotics Manufacturing Hub at no-cost thanks to funding from the Southwestern Pennsylvania Region’s Build Back Better Regional Challenge Award. Now is a great time to get started with the Robotics Manufacturing Hub as the ARM Institute is looking to work with more manufacturers. In the future, the ARM Institute hopes to expand these services to manufacturers beyond this region and encourages those with interest in using or housing these services to reach out here. Additionally, the ARM Institute’s member organization ecosystem can leverage the Robotics Manufacturing Hub as a benefit of membership.

U.S. manufacturing resiliency is the cornerstone of our national security. The ARM Institute’s Robotics Manufacturing Hub addresses a critical need in helping to provide small and medium sized manufacturers with the resources that they need to explore and implement automation, enhancing their competitiveness and benefiting the full manufacturing ecosystem.

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