Manufacturing

The machine is equipped with a three-ply, heavy-duty fines belt. (Image source: MDS)

MDS, a manufacturer of specialist screening equipment, has introduced the SCRAPMASTER 400, a powerful new machine tailored to the demands of the scrap and metals recycling industry.

This latest model builds on the robust foundation of the successful M412, which was designed for screening a range of materials, from lightweight substances to heavy demolition waste. After extensive research and customer consultations, MDS has refined the platform to create an ideal solution for scrap metal screening.

The SCRAPMASTER 400 is engineered for heavy-duty scrap processing, featuring a durable, wear-resistant push feeder built to handle abrasive materials, a rugged drum frame with customisable screen options from 25 to 150mm (1–6 inches), and an apron-style conveyor on the oversize material output, enhancing durability specifically for scrap applications.

The machine is equipped with a three-ply, heavy-duty fines belt for added strength, along with auto-reverse functionality and adjustable drum rotation speeds to meet varied processing needs.

Conor Hegarty, general manager MDS, said, “Up until now, many customers have had to rely on traditional recycling trommels or scalpers for the scrap and metal recycling segment, which often lacked the durability required for processing metals. MDS identified the need for a machine specifically dedicated to handling the toughest of tasks.

“MDS products excel in the toughest applications, and we have leveraged our existing heavy-duty technology to produce a machine that improves scrap processing efficiency and reliability. The addition of the SCRAPMASTER 400 to the MDS product range underlines our position as leaders in specialty screening applications.”

The last recorded cases of heat-related illness at EGA were in 2020. (Image source: EGA)

Emirates Global Aluminium (EGA), the UAE's largest industrial company outside the oil and gas sector, has announced achieving zero heat-related illnesses for the third consecutive summer.

Heat-related illnesses pose a significant risk for anyone working outdoors during the UAE's intense summer heat, with the potential to be life-threatening if not addressed promptly. EGA’s industrial operations, which generate additional heat, run continuously throughout the summer, requiring round-the-clock outdoor work.

EGA's 'Beat the Heat' programme, in place for over a decade, is a comprehensive, summer-long initiative designed to combat occupational heat stress. It focuses on raising awareness among employees about the early signs of heat-related illness and empowering them to take proactive measures to prevent its onset.

Stress prevention

EGA’s ‘Beat the Heat’ campaign incorporates several measures to prevent heat-related illnesses, including hydration tests conducted before and during shifts, regular breaks, and cooling showers. The programme also features cooling booths, drinking stations, icemakers, and portable air conditioning units installed throughout the production areas to ensure that both employees and contractors remain cool and comfortable during their work shifts.

Medical personnel from EGA’s on-site centres play an active role in heat stress prevention, working closely with employees and providing immediate treatment to anyone reporting early symptoms of heat stress.

Since 2022, EGA has partnered with US technology firm Kenzen to trial wearable technology that monitors key physiological indicators such as core body temperature and heart rate. This summer, 300 EGA employees used these devices, which provide real-time feedback to both the wearer and EGA’s safety team, allowing for the detection of early heat stress signs before they are physically felt.

The last recorded cases of heat-related illness at EGA were in 2020 when two employees required treatment. Both individuals received intravenous hydration and fully recovered within hours.

Abdulnasser Bin Kalban, CEO of EGA, said, “Our success in completely preventing heat-related illness on our sites for the third year in a row proves that this key hazard for outdoor workers in region can be overcome. Occupational heat stress remains a serious challenge in our region and beyond, and we believe our experience has important lessons for everyone employing people to work outside.”

Applications of cloud platforms include remote monitoring of production processes. (Image source: Canva)

Global technology intelligence firm ABI Research has completed its 2024 Manufacturers’ Technology Adoption & Attitudes Survey, gathering insights from 461 manufacturing decision-makers across the United States, Malaysia, and Germany. The survey reveals key trends and attitudes surrounding the technological landscape in the manufacturing sector.

A significant finding is the widespread belief among respondents that cloud platforms are essential for real-time collaboration with suppliers, distributors, and partners. According to the survey, 76% of respondents have already implemented cloud-based solutions to enhance data accessibility and improve supply chain efficiency.

Additional applications of cloud platforms include remote monitoring of production processes and the efficient management and analysis of production data.

New insights

These insights highlight the growing role of cloud technology in modern manufacturing, as companies increasingly rely on digital solutions to streamline operations and boost efficiency.

“Manufacturers are leveraging cloud platforms, especially hybrid cloud solutions, to help increase production output and efficiency. Manufacturers are leveraging cloud-based supply chain applications to track inventory, shipments, and production status, to improve supply chain visibility and transparency. However, some fundamental challenges remain, such as the integration of legacy infrastructure and data security concerns, that continue to hinder the widespread adoption of cloud solutions in the manufacturing industry,” saidYih-Khai Wong, principal analyst with ABI Research.

Manufacturers are accelerating their digital transformation efforts, driven by the increasing demand for Artificial Intelligence (AI) and Machine Learning (ML) solutions, the expansion of smart IoT devices, and the surge in data generation across both on-premises infrastructure and public cloud platforms.

However, many manufacturers operate within heterogeneous technology environments, where various platforms and solutions are used throughout the manufacturing process. This complexity and the lack of unified technology standards often hinder real-time collaboration. A cloud-based enterprise data fabric architecture offers a solution by breaking down data silos and integrating data from multiple sources, enabling seamless real-time collaboration across the business.

“Cloud platforms provide flexibility and scalability for manufacturers to scale up or down, based on production and business needs. This will be crucial in ensuring a robust enterprise data fabric architecture, which allows manufacturers to foster real-time collaboration, enhancing the capability for remote monitoring and analysing production data more efficiently, ultimately increasing production innovation,” concluded Wong.

This improvement was achieved using a reliable and precise deep learning machine vision solution. (Image source: Zebra technologies)

Zebra Technologies, a provider of digital solutions that enable businesses to intelligently connect data, assets, and people, announced that TAS, a global supplier to automotive OEMs, has enhanced the production quality of electric vehicle battery caps.

This improvement was achieved using a reliable and precise deep learning machine vision solution powered by Zebra’s Aurora Vision Studio software, ensuring greater accuracy and security in the manufacturing process.

To ensure precise finishing for each battery cap, TAS employs a meticulous process where robotic systems handle the metal sheets through various inspection stages. A highly sophisticated camera system is utilised to detect potential defects that could affect quality.

Custom-built operations

This custom-built camera system, designed by ID Engineering, a Zebra Registered Industrial Automation System Integrator specialising in machine vision, can identify even the smallest surface imperfections, ensuring the caps' safety and performance.

The adaptability of Aurora Vision Studio enhances the system's reliability, allowing TAS to continuously improve safety and precision by addressing coating irregularities, surface scratches, and laser marking issues.

Setting itself apart from other solutions, the Aurora Vision Studio system integrates deep learning tools that drive continuous improvement throughout the manufacturing process. The system is trained using a comprehensive dataset of images, enabling it to recognise and classify specific defect types. These image datasets are annotated and fed into the system, which can be retrained to identify new inspection criteria or fine-tuned for existing defects. This allows the image processing solution to evolve and improve continuously, leveraging deep learning technology.

A key advantage of this deep learning capability is its flexibility, ensuring reliable inspection even when industrial conditions change—a significant benefit over traditional image processing tools, which may not adapt well to evolving production environments. The system’s flowchart-based image processing solution uses a no-code approach, enabling fast and convenient training, ensuring that TAS maintains consistent product quality while adapting to production changes.

“The successful integration of surface treatment technology and a custom-built quality control system with deep learning represents a significant advancement in quality control and our continuous commitment to innovation,” said Temel Tas, managing director, TAS. “With Zebra Technologies’ machine vision system, we can meet the high-quality standards of the automotive industry, and we are already planning to implement this technology in future projects.”

“The main advantage of Zebra’s Aurora Vision Studio is its speed in development and execution time when analysing many and sometimes large image files simultaneously, which is much faster than other technologies we tested,” said Michael Sartor, machine vision department head, ID Engineering. “The scalable Zebra system is easy to use and it’s no-code solution enables fast development. Beyond the technology, we appreciate the valuable support from Zebra.”

“This solution is a good example of how deep learning algorithms can be used to help ensure better quality in industrial production,” said Donato Montanari, vice president and general manager, Machine Vision, Zebra Technologies. “Aurora Vision Studio and its deep learning add-on provide the foundation on which even huge amounts of data can be processed and utilised. This is an important contribution to the manufacturing technology of the future.”