Humans Will Not be Replaced by Robots

This past June at the Automate Show in Detroit there were many interesting, impressive, even remarkable demonstrations of how far robots have come to automate manufacturing plants and distribution centers. That said, it remains clear that exacting and precise  manipulation will not be possible with robots for a long time and human cognitive intelligence is still required. 

Perhaps the repetitive motions of fork trucks travelling from a dock to workstation can be easily replicated with Automated Guided Vehicles (of which more than a dozen were on display at the show in Detroit), but the actual nuance of accurate product picking requires both human cognition and picking precision. Based on in-depth data collected over the past three years, we have learned that manual processes still represent seventy percent (70%) of the cost of operating a warehouse.
Humans Will Not be Replaced by Robots
The human being must still do the picking

Since the human being must still do the picking, a paradigm shift to AR solutions represents the only fail-proof methodology to corroborate accurate, immediate, and validated product picking and packing. It has been staggering how billions of dollars in hackneyed technologies, without any AR validation continue to sell with regularity. Even voice picking technology fails to incorporate the much needed AR. 
Best practice product picking technologies reduce the error rate about thirty percent (30%). This is not necessarily because AR Google glasses scan better than other technologies; it is because there is always access to price relevant information on the visual display.

AR powered Google glasses ensure worker confidence, employee engagement, and job retention, all of which are more important as the hourly wage for warehouse workers, has doubled in the past three years. At these wage levels, the cost of a single mis-pick becomes intolerably unsustainable.

Both young and old warehouse workers appreciate AR powered Google glasses. They have traction among Gen Zers and younger warehouse workers because nearly all of them play video games and are accustomed to wearing some kind of AR headset. When work replicates a fun human experience the process is vastly more appealing to the worker.  It has also been widely reported that older workers appreciate AR Google glasses because it enhances confidence and success in proper picking. These older workers are reliable warehouse and distribution center employees. While workers are productive and happy, the bottom line is directly impacted because inventory levels are accurately updated and reported in real-time.
Humans Will Not be Replaced by Robots
Picking proficiency increases dramatically because incentives for rapid and accurate picking can be sources for bonuses and a warehouse success. These warehouse workers can go down the road and get another job that pays a few dollars more per hour; it is the AR technology that keeps them loyal to a particular employer. Young or old if workers like their AR picking job, they tell their friends. They become a commercial for the next new hire.


People are not going to be replaced by robots. Robots are not going to provide the cognition needed for discernment.  Those choosing antiquated technologies are doing so at their own peril. As more AR savvy warehouse operations managers take over, the market is going to see the shift to newer, better, and breakthrough technologies.
About The Author
Carsten Funke is the CEO of Picavi USA.  He is a Global expert in the field of logistics processes using AR (augmented reality) concepts.

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What are the Risks that Manufacturing Face in the Current Times?

Article | December 30, 2021

Risk management in manufacturing has always been a top priority for manufacturers to avoid any unfortunate incidents. As a result, it is possible to create a more secure work environment for employees by conducting risk assessments and implementing remedies. “If you don’t invest in risk management, it doesn’t matter what business you’re in, it’s a risky business.” – Gary Cohn, an American Business Leader. As of 2019, the worldwide risk management market was valued at $7.39 billion, and it is expected to rise at a CAGR of 18.7% from 2020 to 2027, according to allied market research. Why is Risk Assessment Critical in Manufacturing? The manufacturing industry must have a credible risk assessment and management plan to defend itself from any breaches. Risk assessment helps firms understand the dangers they face and their implications if their systems are compromised. Hence, risk assessment is very critical in the manufacturing industry. Five Risk Assessment Principles Identify hazards/risks - Employers must examine their workers' health and safety risks. Therefore, an organization must regularly inspect its employee’s physical, mental, chemical, and biological threats. Identify who may be hurt and in what way – Identifying the personnel both full-time and part-time at-risk. Employers must also examine threats to agency and contract personnel, visitors, clients, and other visitors. Assess the risks and act accordingly - Employers must assess the likelihood of each danger causing injury. This will evaluate and lower the chance at the working space. Even with all safeguards, there is always some danger. Therefore, employers must assess if danger is still high, medium, or low risk. Get the Risks Documented - Employers with five or more employees must record the critical findings of the risk assessment in writing. In addition, register any risks identified in the risk assessment and actions to minimize or eliminate risk. This document confirms the evaluation and is used to examine working practices afterward. The risk assessment is a draft. It should be readable. It shouldn't be hidden away. The risk assessment must account for changes in working techniques, new machinery, or higher work objectives. 5 Manufacturing Risks to Consider in 2022 Accidents at Work Even if official safety policies and programs are designed, followed, and enhanced, manufacturers may endure workplace accidents and injuries. Risk assessment for workplace accidents assists in mitigating the negative impact on both employees and the organization. Environmental Mishaps Manufacturers have distinct issues regarding fuel handling and hazardous waste disposal in facilities. Sudden leaks or spills may be extremely costly to clean up and result in fines from state and federal agencies. Risk assessments for such plant accidents assist businesses in mitigating financial losses. Equipment Breakdowns Essential machinery throughout the production process might fail at any time, incurring significant repair or replacement costs. Therefore, it's critical to recognize that business property insurance may not cover mechanical issues. Risk assessment and prepayment solutions protect against equipment failures without interfering with typical company operations. Supply Chain Disruption Dependence on your supply chain may result in unintended consequences that are beyond your control. For example, if you experience downtime on the manufacturing line due to a supplier's failure to supply materials or parts, you risk losing revenue and profitability. If a disturbance to your supply chain poses a hazard, risk management can assist you in managing it more effectively by quickly identifying the risk and providing a suitable response. Operation Temporarily Suspended Depending on the severity of the weather event, a factory might be severely damaged or perhaps utterly wrecked. While major repairs or rebuilding are being undertaken, recouping lost income might be vital to the business's future profitability. Risk assessment in this area enables your organization to budget for overhead expenditures such as rent, payroll, and tax responsibilities during the period of suspension of operations. Final Words Risk management is critical in manufacturing because it enables manufacturers to comprehend and anticipate scenarios and create a well-planned response that avoids unnecessary overhead costs or delays in delivering the production cycle's final result. Manufacturing risks are undoubtedly not limited to the risks listed above and may vary according to the nature of the business and regional environmental conditions. Therefore, create a well-defined strategy to overcome threats in your business and be productive at all times. FAQ How are manufacturing business risks classified? In most cases, the business risk may be categorized into four types: strategic risk, regulatory compliance risks, operational compliance risks, and reputational risks. Why should a manufacturer conduct a risk assessment? Every manufacturing employment has risks for injury or illness. But risk evaluations can significantly minimize workplace injuries and illnesses. In addition, they assist companies in discovering strategies to reduce health and safety risks and enhance knowledge about dangers.

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New industrial IoT capabilities in 5G pave the way for Industry 4.0

Article | April 21, 2020

As part of Qualcomm’s efforts to further support industry IoT applications, the company provided live over-the-air demonstrations of upcoming 5G industrial IoT capabilities such as Time Sensitive Networking, enhanced ultra-reliable low-latency communication and precise indoor positioning. TSN support delivers precise time synchronization between 5G-connected devices, and in a recent blog post, John Smee, VP of engineering at Qualcomm, wrote that when used in conjunction with enhanced ultra-reliable low-latency communication, can deliver up to 99.9999% reliability with low and deterministic latency.

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ADAPTATION, BUSINESS CONTINUITY & COBOTS: MACHINE TENDING

Article | June 29, 2020

Machine tending is one of those tasks that's ideally suited to collaborative robot-powered automation. Dull, often dirty and sometimes dangerous, it's no surprise that over recent years machine tending has emerged as one of the most popular applications for cobots.And with manufacturers facing unique challenges --from sudden changes to production lines to the introduction of social distancing requirements-- due to COVID-19, cobot's mobility and ease-of-use makes them even more attractive today than during normal circumstances. There are many tasks in a production environment that fall into the category of “machine tending” – where a piece of equipment requires worker intervention in order to complete a task.

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Industrial 4.0, IoT

Harnessing IIoT Power for Device Interconnectivity in Industry 4.0

Article | July 21, 2023

Embracing IIoT & device interconnectivity offers enhanced operational efficiency, predictive maintenance, data-driven insights, improved quality, optimized supply chains, enhanced safety, & security. Contents 1. Introduction to IIoT and Device Interconnectivity in Industry 4.0 2. Advanced Sensing and Data Collection 2.1. Industrial Sensors and IoT-enabled Devices 2.2. Real-time Data Collection and Analysis 2.3. Edge Computing for Faster Decision-Making 3. Connectivity Technologies for Device Interconnectivity 3.1. Wireless Technologies: Wi-Fi, Bluetooth, and Cellular Networks 3.2. Low-Power Wide Area Networks (LPWAN) 3.3. Industrial Ethernet and Fieldbus Protocols 4. Benefits of Efficient Device Interconnectivity 4.1. Enhanced Operational Efficiency 4.2. Real-time Monitoring and Control 4.3. Predictive Maintenance 4.4. Data-driven Insights 4.5. Supply Chain Optimization 5. Embracing IIoT for Device Interconnectivity in Industry 4.0 1. Introduction to IIoT and Device Interconnectivity in Industry 4.0 The Industrial Internet of Things (IIoT) is a network of interconnected devices, sensors, and systems that collect and exchange data in industrial settings. IIoT industry 4.0 enables real-time data monitoring, analysis, and control, leading to improved operational efficiency, reduced costs, and increased productivity in industrial processes. It utilizes technologies such as IoT sensors, embedded systems, cloud computing, big data analytics, and machine learning to facilitate seamless connectivity and data exchange. Device interconnectivity in Industry 4.0 is the integration and communication between different devices, machines, and systems across the industrial value chain. Device interconnectivity enables data sharing and interoperability, facilitating automation, predictive maintenance, optimized resource allocation, and enhanced decision-making in industrial IoT operations. IIoT and device interconnectivity generate vast amounts of data that can be analyzed to gain valuable insights into production processes, supply chains, customer behavior, and market trends. The increased interconnectivity of devices in Industry 4.0 raises concerns about data security and privacy. Robust cybersecurity measures and data protection protocols are necessary to mitigate risks. This creates new business opportunities, including innovative service models, predictive maintenance solutions, remote monitoring, and data-driven decision support systems, with applications in various industries such as smart manufacturing, energy, transportation, agriculture, healthcare, and smart cities. 2. Advanced Sensing and Data Collection 2.1. Industrial Sensors and IoT-enabled Devices Industrial sensors are sophisticated devices that employ cutting-edge technologies to detect and measure various physical parameters in industrial environments. They utilize advanced sensing technologies such as optical, acoustic, thermal, and chemical sensors to capture precise and accurate data. Whereas, IoT-enabled devices, integrated with industrial sensors, leverage the power of connectivity and advanced communication protocols to enable seamless data collection and exchange. These devices have embedded software, wireless connectivity, and data processing capabilities, transforming them into intelligent nodes within the Industrial Internet of Things ecosystem. These empower businesses to capture real-time data at a granular level. This provides organizations to gain comprehensive insights into their assets, processes, and environments' performance, health, and condition. Such data-driven intelligence forms the foundation for advanced analytics, predictive maintenance, and operational optimization. 2.2. Real-time Data Collection and Analysis With integrating IIoT sensors, businesses can collect data in real time from diverse sources within their industrial ecosystem. This includes sensor readings, machine parameters, environmental conditions, production metrics, and supply chain information. This allows businesses to continuously monitor their operations, providing immediate awareness of critical events and performance indicators. By capturing data in real-time, organizations can swiftly identify anomalies, deviations, or opportunities for improvement, for agile decision-making, operational responsiveness, and proactive interventions. Real-time data collected from industrial sensors and IoT-enabled devices can be subjected to advanced analytics and machine learning algorithms. These sophisticated analysis techniques reveal hidden patterns, correlations, and predictive models within the data. The resulting insights enable organizations to uncover optimization opportunities, identify root causes of issues, and develop data-driven strategies for operational excellence. 2.3. Edge Computing for Faster Decision-Making Edge computing is an advanced paradigm that brings data processing, analytics, and decision-making closer to the data source at the network's edge. By decentralizing computational capabilities, edge computing reduces latency, minimizes bandwidth requirements, and enables faster, localized decision-making. It enhances the efficiency and responsiveness of data-driven decision-making in industrial settings. Businesses can achieve near real-time insights and rapid response times by processing and analyzing data locally, at or near the edge IoT devices. This is particularly critical for time-sensitive applications like autonomous systems, predictive maintenance, and adaptive control mechanisms. Edge computing empowers businesses to make faster decisions based on real-time data analysis. Edge computing enables localized processing and immediate responses by reducing the need for data transmission to a centralized cloud or data centers. This allows organizations to take swift actions, optimize processes on the fly, and mitigate risks in real time. 3. Connectivity Technologies for Device Interconnectivity 3.1. Wireless Technologies: Wi-Fi, Bluetooth, and Cellular Networks Wi-Fi, Bluetooth, and cellular networks widely use wireless connectivity technologies that enable device interconnectivity in various industrial settings. Wi-Fi provides high-speed wireless connectivity over short to medium distances. Wi-Fi offers flexibility and compatibility with various devices, making it a popular choice for interconnecting devices within industrial environments. Bluetooth technology is commonly used for short-range wireless connections between devices, for personal area networks (PANs) and device-to-device communication applications. Cellular networks, such as 4G LTE and emerging 5G technology, provide wide-area coverage and reliable connectivity over large distances. They are suitable for IoT applications that require remote monitoring, asset tracking, and connectivity in remote or mobile industrial environments. 3.2. Low-Power Wide Area Networks (LPWAN) LPWAN technologies are designed to provide long-range wireless connectivity while consuming minimal power. These networks are well-suited for applications involving low data rates, long battery life, and cost-effective deployment. NB-IoT (Narrowband IoT) is a cellular-based LPWAN technology that operates on licensed spectrum, providing wide-area coverage with low power consumption, while Long Range Wide Area Network (LoRaWAN ) is a low-power, long-range wireless technology that operates on unlicensed spectrum and enables efficient connectivity for devices spread across large areas, making it suitable for IoT applications such as smart agriculture, logistics, and smart cities. 3.3. Industrial Ethernet and Fieldbus Protocols Industrial Ethernet refers to the use of Ethernet-based communication protocols within industrial environments. It provides high-speed, reliable, and deterministic connectivity for industrial devices, such as programmable logic controllers, human-machine interfaces, and sensors. Industrial Ethernet protocols like Ethernet/IP, PROFINET, and Modbus TCP enable real-time data exchange, control, and monitoring, facilitating efficient device interconnectivity in industrial automation systems. Fieldbus protocols have been widely used in industrial automation for device interconnectivity. It enables data communication between field devices, controllers, and other industrial equipment. These protocols are known for their robustness, determinism, and support for various devices, making them suitable for applications in process control, IIoT manufacturing, and distributed control systems. 4. Benefits of Efficient Device Interconnectivity 4.1. Enhanced Operational Efficiency Efficient device interconnectivity revolutionizes industrial processes by facilitating seamless communication and collaboration among interconnected devices, machines, and systems. This integration optimizes workflows, reduces bottlenecks, and maximizes operational efficiency, ultimately improving productivity and profitability. 4.2. Real-time Monitoring and Control The efficient interconnection of devices gives businesses real-time visibility into their operations. By continuously monitoring and controlling key parameters such as machine performance, energy consumption, and production metrics, organizations can proactively make data-driven decisions to optimize performance, minimize downtime, and ensure optimal resource allocation. 4.3. Predictive Maintenance Efficient device interconnectivity enables the collection and analysis of real-time data from interconnected devices. Businesses can detect patterns and anomalies by leveraging advanced analytics and machine learning algorithms, allowing for predictive maintenance strategies. Proactively addressing maintenance needs and potential equipment failures reduces unplanned downtime, enhances equipment lifespan, and lowers maintenance costs. 4.4. Data-driven Insights Efficient device interconnectivity generates abundant data that holds valuable insights. Organizations can extract actionable insights from the collected data through sophisticated data analytics techniques, including artificial intelligence and big data analytics. These insights empower businesses to optimize processes, uncover hidden patterns, identify market trends, and make informed strategic decisions. 4.5. Supply Chain Optimization Device interconnectivity facilitates seamless data exchange and collaboration across the supply chain. This enables end-to-end visibility, efficient coordination, and streamlined operations. With real-time data on demand, inventory levels, and market demand, businesses can optimize their supply chain processes, minimize lead times, reduce stockouts, and enhance overall supply chain efficiency in IIoT Industry 4.0. 5. Embracing IIoT for Device Interconnectivity in Industry 4.0 In the era of Industry 4.0, businesses are embracing the integration of the IIoT industry 4.0 and device interconnectivity to unlock new levels of efficiency, productivity, and agility. This is made possible through various connectivity technologies, including wireless technologies like Wi-Fi, Bluetooth, and cellular networks, as well as LPWAN and industrial Ethernet and fieldbus protocols. These technologies enable seamless data exchange, real-time monitoring, and intelligent control within the industrial ecosystem. Additionally, embracing IIoT and device interconnectivity offers numerous advantages, such as enhanced operational efficiency, predictive maintenance, data-driven insights, improved product quality, optimized supply chains, enhanced safety, and security. By leveraging these advancements, businesses can drive sustainable growth and gain a competitive edge in the digital age of Industry 4.0.

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Robotics and Automation

Micropsi Industries’ AI Software MIRAI Now Compatible with FANUC Robots, Enabling Increasingly Flexible Automation

FANUC America | December 01, 2022

Micropsi Industries today announced that its artificial intelligence (AI)-based software MIRAI is now compatible with numerous robots produced by FANUC, a leading supplier of robotics and factory automation in Japan, and its U.S. subsidiary FANUC America. With MIRAI, FANUC customers can now add valuable hand-eye coordination to multiple FANUC industrial and collaborative robots (cobots) to handle difficult-to-automate functions such as cable plugging and assembly. Using AI, the MIRAI controller generates robot movements directly and in real-time. Robot skills are trained, not programmed, in a few days through human demonstration, without requiring knowledge of programming or AI. To train a robot, a human repeatedly demonstrates a task by manually guiding the robot by the robot’s wrist. The recorded movements are then transformed into a skill. “MIRAI is a game changer, For the last 20 years I’ve heard companies ask for this kind of dynamic path augmentation technology repeatedly, so seeing it work is really amazing. What’s even more amazing is how affordable it is to add this kind of automation-enabling technology to any of our robots or collaborative cobots. I’ve already showed this technology to large and small manufacturers that are asking us to implement flexible robot automation faster, and unanimously, they are very interested in implementing MIRAI.” -Jerry Perez, executive director of global accounts, FANUC America. That’s because while robots can work tirelessly and precisely with high repeatability, they are limited in their ability to perform complex motorized processes. The required hand-eye coordination is just not present in a robot. If the robot falters due to variances or deviations, employees must intervene, and are sometimes burdened with unergonomic tasks. This inhibits the performance of manufacturing companies who are already struggling with the prevailing shortage of skilled workers. Cable plugging, which can now be automated quickly and intelligently is just one example of MIRAI's further automation potential. Micropsi Industries plans additional automation projects that will expand the range of applications for FANUC’s industrial robots. The medium- and long-term goal: to revolutionize industrial work from the ground up. "Cable plugging applications such as flat ribbon cables for the electronics industry or industrial automotive connectors typically require a high degree of flexibility to accommodate shape instability, making it a difficult task for any robot. MIRAI makes this type of application possible, Grabbing a flexible part, guiding it and placing it accurately into a socket may be a trivial task for humans, but it has been basically impossible to complete for industrial robots.Micropsi Industries working with FANUC’s robots will break new ground by making automation possible where it has never been before, In this strategic relationship, our MIRAI intelligent controller meets the world's largest portfolio of industrial robots. Together, we are tapping into the nearly unlimited possibilities of task-specific machine learning for robotics. In doing so, we are making it accessible to even more industries and users, ensuring greater flexibility under real production conditions." -Prof. Dominik Bösl, chief technology officer, Micropsi Industries. About Micropsi Industries: Micropsi Industries provides artificial intelligence-based software for industrial and collaborative robots (cobots). MIRAI, its flagship product, allows these robotic arms to be controlled in real time, in direct response to sensor information. This is made possible by AI that enables the robots to learn from humans and deal with variances so they can more easily and cost-effectively operate in dynamic environments. With offices in Berlin, San Francisco and Los Angeles, Micropsi Industries is working to make task-specific machine learning a reality in industrial automation. The company’s vision is to reliably automate work processes while reducing the effort required.

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Robotics and Automation

Micropsi Industries’ AI Software MIRAI Now Compatible with FANUC Robots, Enabling Increasingly Flexible Automation

FANUC America | December 01, 2022

Micropsi Industries today announced that its artificial intelligence (AI)-based software MIRAI is now compatible with numerous robots produced by FANUC, a leading supplier of robotics and factory automation in Japan, and its U.S. subsidiary FANUC America. With MIRAI, FANUC customers can now add valuable hand-eye coordination to multiple FANUC industrial and collaborative robots (cobots) to handle difficult-to-automate functions such as cable plugging and assembly. Using AI, the MIRAI controller generates robot movements directly and in real-time. Robot skills are trained, not programmed, in a few days through human demonstration, without requiring knowledge of programming or AI. To train a robot, a human repeatedly demonstrates a task by manually guiding the robot by the robot’s wrist. The recorded movements are then transformed into a skill. “MIRAI is a game changer, For the last 20 years I’ve heard companies ask for this kind of dynamic path augmentation technology repeatedly, so seeing it work is really amazing. What’s even more amazing is how affordable it is to add this kind of automation-enabling technology to any of our robots or collaborative cobots. I’ve already showed this technology to large and small manufacturers that are asking us to implement flexible robot automation faster, and unanimously, they are very interested in implementing MIRAI.” -Jerry Perez, executive director of global accounts, FANUC America. That’s because while robots can work tirelessly and precisely with high repeatability, they are limited in their ability to perform complex motorized processes. The required hand-eye coordination is just not present in a robot. If the robot falters due to variances or deviations, employees must intervene, and are sometimes burdened with unergonomic tasks. This inhibits the performance of manufacturing companies who are already struggling with the prevailing shortage of skilled workers. Cable plugging, which can now be automated quickly and intelligently is just one example of MIRAI's further automation potential. Micropsi Industries plans additional automation projects that will expand the range of applications for FANUC’s industrial robots. The medium- and long-term goal: to revolutionize industrial work from the ground up. "Cable plugging applications such as flat ribbon cables for the electronics industry or industrial automotive connectors typically require a high degree of flexibility to accommodate shape instability, making it a difficult task for any robot. MIRAI makes this type of application possible, Grabbing a flexible part, guiding it and placing it accurately into a socket may be a trivial task for humans, but it has been basically impossible to complete for industrial robots.Micropsi Industries working with FANUC’s robots will break new ground by making automation possible where it has never been before, In this strategic relationship, our MIRAI intelligent controller meets the world's largest portfolio of industrial robots. Together, we are tapping into the nearly unlimited possibilities of task-specific machine learning for robotics. In doing so, we are making it accessible to even more industries and users, ensuring greater flexibility under real production conditions." -Prof. Dominik Bösl, chief technology officer, Micropsi Industries. About Micropsi Industries: Micropsi Industries provides artificial intelligence-based software for industrial and collaborative robots (cobots). MIRAI, its flagship product, allows these robotic arms to be controlled in real time, in direct response to sensor information. This is made possible by AI that enables the robots to learn from humans and deal with variances so they can more easily and cost-effectively operate in dynamic environments. With offices in Berlin, San Francisco and Los Angeles, Micropsi Industries is working to make task-specific machine learning a reality in industrial automation. The company’s vision is to reliably automate work processes while reducing the effort required.

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