Automation is good, so long as you know exactly where to put the machine.

AI Servo Monitor uses artificial intelligence to predict possible failures of the drive systems for FANUC servomotors and spindle motors. AI Servo Monitor, in conjunction with MT-LINKi through machine learning, analyzes the daily performance of machines equipped with FANUC CNCs. Daily data is displayed in intuitive graphs which allows users to easily monitor abnormalities on these machines. Artificial intelligence automatically creates a baseline model of the machine while running in a normal state. An "anomaly score" developed expresses a difference in the baseline model and the daily recorded values.

FANUC's AI Servo Monitor provides machine health data and analysis to maximize uptime. HOFFMAN ESTATES, Ill.–(BUSINESS WIRE)–Downtime is the enemy of profitability in manufacturing, which is why FANUC, a leading global automation solutions provider, has introduced a new Industrial Internet of Things (IIOT) software designed to prevent production problems before they happen. AI Servo Monitor uses artificial intelligence to predict possible failures of the drive systems for FANUC servomotors and spindle motors. AI Servo Monitor, in conjunction with MT-LINKi through machine learning, analyzes the daily performance of machines equipped with FANUC CNCs. Daily data is displayed in intuitive graphs which allows users to easily monitor abnormalities on these machines.

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Many are familiar with the idea of factory automation, but what about'hyperautomation'? And, how about the rise of autonomous factories, with systems that make their own decisions about things like quality control and line speed? Both concepts, driven by artificial intelligence (AI) technologies, are coming soon to manufacturers, and are being closely tracked by many industry watchers. They're also both expected to revolutionize how factories function.

There are some mechanical engineering fields in which AI is about to give a paradigm shift. AI used in Computer-Aided Design (CAD) generally works on knowledge-based systems. Design artefacts, rules, and problems in CAD are stored which later assist CAD designers. Merging of AI and CAD is done through Model-Based Reasoning (MBR). Many new releases of software packages are using knowledge-based systems.

Ongoing standardization in Industry 4.0 supports tool vendor neutral representations of Piping and Instrumentation diagrams as well as 3D pipe routing. However, a complete digital plant model requires combining these two representations. 3D pipe routing information is essential for building any accurate first-principles process simulation model. Piping and instrumentation diagrams are the primary source for control loops. In order to automatically integrate these information sources to a unified digital plant model, it is necessary to develop algorithms for identifying corresponding elements such as tanks and pumps from piping and instrumentation diagrams and 3D CAD models. One approach is to raise these two information sources to a common level of abstraction and to match them at this level of abstraction. Graph matching is a potential technique for this purpose. This article focuses on automatic generation of the graphs as a prerequisite to graph matching. Algorithms for this purpose are proposed and validated with a case study. The paper concludes with a discussion of further research needed to reprocess the generated graphs in order to enable effective matching.

The choice between traditional machine vision and deep learning depends upon the type of application being solved, the amount of data being …

We were promised robots everywhere -- fully autonomous robots that will drive our cars end-to-end, clean our dishes, drive our freight, make our food, pipette and do our lab work, write our legal documents, mow the lawn, balance our books and even clean our houses. And yet instead of Terminator or WALL-E or HAL 9000 or R2-D2, all we got is Facebook serving us ads we don't want to click on, Netflix recommending us another movie that we probably shouldn't stay up to watch, and iRobot's Roomba. Where are all the robots? This is the question I've been trying to investigate while building my own robotics company (a currently stealth company named Chef Robotics in the food robotics space) as well as investing in many robotics/AI companies through my venture capital fund Prototype Capital. Industrial six degrees of freedom (read as six motors serially attached to each other) robot arms were actually developed around 1973 and there are hundreds of thousands of them out there -- it's just that up to this point, almost all of these robots have been in the extremely controlled environment of factory automation doing the same thing over and over again millions of times. And we've formed many multibillion dollar companies through these factory automation robots including FANUC, KUKA, ABB and Foxconn (yes they make their own robots). Go to any automotive manufacturing plant and you'll see hundreds (or in Tesla's case, thousands). They work insanely well and can pick up massive payloads -- a full car -- and have precision sometimes up to a millimeter.

Drives play an essential role in automation technology. Stating its importance, K T Chougule, DGM – drive solutions, factory automation & industrial division, Mitsubishi Electric India says, "Generally 70% of the electrical load is motor load in the industry and to run the motor with variable speed according to the machine/process application requires a drive. VFDs also play a critical role in energy saving particularly in variable torque application, where energy is saved considering the difference between process demand & supply, mainly for fan & pump application. Energy saving market is growing very fast in India due to relatively high cost of power in India." Further he adds, "Drive not only gives variable speed, it can also deliver smooth start-stop, which reduces mechanical impact on machines or equipment, improves the power factor of the system and also reduces the maximum demand (MD) of factory Drive plays a key role in the automation technology, and the drive market is more than 50% of total factory automation market."

Bright Machines today announced the closure of a $179 million funding round and launched out of stealth. The company aims to automate manufacturing operations in factories and make manufacturing hardware as simple as building software is today. Bright Machines was founded six months ago in part by former Autodesk interim CEO Amar Hanspal, while former lon Autodesk CEO Carl Bass sits on the company board of directors. Autodesk alum are joined by former Autodesk and Flex employees. Bright Machines operates on the belief that low-cost manufacturing in developing nations has reached its limits as more economies enter the middle class and factories encounter challenges hiring employees at the lower pay rates that have been common in the past.