Disarming Weapons Gets Easier With Robots
Acoustic Monitoring
Assembly Line
Robots Automate Disassembly of Chemical Weapons
Disarming and disassembling the rockets is not easy, and the task is made even more difficult because of the rocket’s design. The rocket propellant cannot be removed from the warhead without cutting open the rocket, and the propellant itself presents a hazard, because it becomes unstable as it ages. Another danger is leakage of the toxic nerve agents. As sarin decomposes, it forms acids that can corrode the aluminum casing inside the rocket.
Both Ankrom and Staggs have seen first-hand how advancements in chemical weapons destruction now require fewer and fewer people. Ankrom started working with chemical agents in the mid-1980s, recalling how his first project, which focused on a hallucinogenic, was entirely manual and required 15 people. Even as recently as 2014, workers at the Blue Grass depot had to manually separate the warheads from the rocket motors and then separate the fuses from the warheads to support testing at the Anniston Static Detonation Chamber disposal plant, adds Staggs, who has worked with chemical weapons since 1978. “Adding the automation with robots has assisted us with reducing people interaction with these aging chemical weapons,” Staggs says. But the Blue Grass depot’s original disposal system plans, even with its robots, presented problems when workers discovered leaking rockets.
The agency reached out to CRG Automation, an engineering firm best known for building packaging lines for the likes of Coca-Cola, Kellogg’s and Kraft. CRG Automation has been designing and building packaging and processing equipment for the food, beverage and consumer products industries for more than 20 years. CRG Automation developed an alternative method by holding the assembly fixed and making the cut with the rocket in a vertical orientation, ensuring that any leaking chemical agent would simply gather in the bottom of a containment device. Cutting the rockets in an upright orientation also meant that the operation could be done more precisely. The cut can be located with an accuracy of 0.001 inch, Ankrom says. Six-axis robots are used to load and unload the cutting machines.
Appliance Business Cast Off by GE Thrives Under Chinese Ownership
Kevin Nolan, GE Appliances’ chief executive, said the move out from under GE to appliance maker Haier has improved his company’s culture and decision making. It held 16.4% of the retail market for large appliances in the 12 months through September, its highest percentage in at least a decade, according to research firm TraQline. GE Appliances’ has found new life as their investment opportunities are no longer number twelve on a list of nine things that could be funded at GE.
Humber Zero: decarbonising an industrial cluster
The Humber is an industrial hub with an economy worth £18bn GVA and where one in ten jobs is associated with heavy industry. Two oil refineries, the second largest chemicals and process clusters, and an integrated steelworks all contribute to the Humber being the most carbon-intensive industrial cluster in the UK.
Blue hydrogen is the main focus at Immingham although Phillips 66 is progressing Gigastack, a green hydrogen project separate to Humber Zero that along with project partners ITM, Ørsted and Element Energy aims to generate green hydrogen and electricity from nearby offshore wind and electrolysis.
IBM’s vision of the connected factory
As far as our software is concerned, we are providing solutions for specific use cases that can deliver the quick wins that manufacturers are looking for. We have a solution called Maximo Application Suite which can monitor equipment effectiveness, asset health, asset performance, and visual inspection. And these kind of quick wins can already be delivered as part of a standard product. We are also working with customers in the field on things which are not necessarily already coded in the software. Something else which IBM brings to the table is that we are open source.
AWS Announces AWS IoT TwinMaker
Industrial companies collect and process vast troves of data about their equipment and facilities from sources like equipment sensors, video cameras, and business applications (e.g. enterprise resource planning systems or project management systems). Many customers want to combine these data sources to create a virtual representation of their physical systems (called a digital twin) to help them simulate and optimize operational performance. But building and managing digital twins is hard even for the most technically advanced organizations. To build digital twins, customers must manually connect different types of data from diverse sources (e.g. time-series sensor data from equipment, video feeds from cameras, maintenance records from business applications, etc.). Then customers have to create a knowledge graph that provides common access to all the connected data and maps the relationships between the data sources to the physical environment. To complete the digital twin, customers have to build a 3D virtual representation of their physical systems (e.g. buildings, factories, equipment, production lines, etc.) and overlay the real-world data on to the 3D visualization. Once they have a virtual representation of their real-world systems with real-time data, customers can build applications for plant operators and maintenance engineers that can leverage machine learning and analytics to extract business insights about the real-time operational performance of their physical systems. Because of the work required, the vast majority of organizations are unable to use digital twins to improve their operations.
Surge Demand
Japan’s shrinking labor force and the Omicron variant are causing Toyota problems. The electric vehicle recruitment continues as the United Kingdom is courting Rivian with a new motorway junction and training facilities.