INDUSTRY News
New AI Hub is now live
ABB COLUMN
SEVEN WAYS TO GET A RETURN ON YOUR ROBOTIC INVESTMENT
Critical digital infrastructure and continuity solutions provider, Vertiv has launched the AI Hub, where partners, customers and other visitors can gain access to expert information, reference designs and resources to successfully plan an AI-ready infrastructure. The AI Hub features white papers, industry research, library demonstrates scaleable liquid cooling and power infrastructure to support current and future chipsets from 10-140kW per rack. “Vertiv has a history of sharing new-to-world technology and insights for the data centre industry,” said Vertiv CEO Giordano Albertazzi. “We are committed to providing deep knowledge, the broadest portfolio and expert guidance current and future deployments. Our close partnerships with leading chipmakers and innovative data centre and partners on their AI journey.” The Vertiv AI Hub allows to be dynamically updated with new content by Vertiv partners. “Virtually every industry is exploring opportunities to drive business value through AI, but there are more questions than answers around how to deploy the building an AI strategy,” said Sean Graham, Research Director, data centers, at IDC.
Uncertainty about return on investment (ROI) is one of the main hurdles holding many UK manufacturers from investing in robots. Whilst a growing number of companies are interested in the possibilities that robotic automation can bring, many remain unsure of how to go about justifying the case for an investment in robots. A good starting point is to consider the areas where robots can help optimise production and boost profitability by assisting workers and helping to transform productivity, flexibility and competitiveness. Improved product quality and consistency – Capable of performing the same task repetitively to the highest levels of accuracy, robots enable consistently high-quality finishing of materials, helping to substantially reduce breakages and wastage and maximising yields. Increased production output – Robots can be left running overnight and during weekends with little supervision, so you can increase your output levels and meet your client’s order deadlines. Increased product manufacturing flexibility – Able to be easily switched between different production programs, robots enable you to get the most from your investment by providing the flexibility to handle a wide range of different products. Improved utilisation of production space – Available in a range of compact designs and with floor, ceiling and wall-mounted options, robots can make the most of your available production space. Improved quality of work for employees – By taking over tedious, repetitive or dirty tasks, robots can improve both job satisfaction and employee retention by enabling workers to perform higher value tasks, including programming and operating the robots. Improved health and safety – Robotic automation significantly reduces the likelihood of accidents caused by contact with machine tools or potentially hazardous production machinery or processes. They can also eliminate injuries associated with repetitive or intensive processes, such as heavy lifting or repetitive tasks. Improved predictability – By reducing wastage and speeding up cycle times, robots provide better predictability, allowing you to optimise production and efficiency and reduce capital costs through improved inventory control. There many more benefits robots can afford; to find out, call us on 01908 350300 or email
robotics@gb.abb.com.
Julian Ware, UK & Ireland Sales Manager – ABB Robotics New study improves fault diagnosis accuracy
Researchers from Xi’an Jiaotong University, Hunan University of Science and Technology in China, and UK’s Brunel University have developed a ‘label recovery and trajectory designable network’ to correct mislabelled data and align data distributions between the source and target domains for accurate fault diagnosis in machines. The method can accurately diagnose faults in bearings under Maintaining machinery is a time-consuming, challenging Now, instead of relying solely on manual inspections, automated diagnosis supported by intelligent models analyse vast amounts of data from sensors placed on machines to identify problems. This shift is made possible by advancements in deep transfer
automationmagazine.co.uk
knowledge gained from analysing well-studied machines (the source domain) to be applied to other machines operating under reduces the need for extensive data collection and training to build diagnosis models for each machine. However, for accurate fault diagnosis, these models require high-quality labelled data from the source domain, which is challenging to obtain. In addition to enchancing fault diagnosis, the research team’s method, LRTDN, also allows greater generalisation to the conditions of the target domain. It addresses the issue of incorrect labelling using three key components: a residual network with learning.
Automation | September 2024 7
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