Engineering

  FPT and SAP’s strategic partnership signing ceremony was attended by FPT Chairman Truong Gia Binh, SAP Asia Pacific and Japan President Paul Marriott, RWE AG CIO Edgar Aschenbrenner, and other senior executives. HANOI, Vietnam – Global IT services provider FPT  has joined the SAP Regional Strategic Services Partner (RSSP) initiative, established by SAP Asia Pacific Japan (APJ) to expand the capabilities and reach of established partners in the APJ region that are on a rapid growth trajectory. Through the RSSP initiative, SAP will provide eligible partners with strategic support, which may include coordinated industry-aligned solutions, a joint go-to-market strategy, and access to SAP regional and market unit industry expertise. The RSSP initiative will enable FPT to scale its SAP practice more rapidly across the APJ region and work more closely with SAP to drive joint customer success. Unlike SAP’s existing Global Strategic Services Partner (GSSP) programme, which includes a select group of the company’s most strategic global consulting, infrastructure, and technology partners, the RSSP initiative is designed to facilitate collaboration within partner organisations based in the region that demonstrate capabilities and capacity requirements specific to the needs of APJ customers. FPT’s SAP implementation and maintenance services are built on a strong foundation of a vast pool of certified and experienced SAP resources and well-established project management frameworks, with over 900 certifications and a dedicated team of SAP consultants. “At FPT, we are passionate about building a happier future for individuals, fostering success for organizations, and prosperity for nations. The 20 years of partnership between SAP and FPT has been a journey of happiness, because we shared a purpose – the purpose to enable enterprises in Vietnam and worldwide to manage their resources with efficiency, with transformation and with growth and expansion”, said Dr. Truong Gia Binh, FPT Chairman. “We […]

Analysis of materials can be done quicker and with less expertise with the help of proven machine learning techniques established in biomedical fields.  Researchers of RIKEN at Japan’s state-of-the-art synchrotron radiation facility, SPring-8, and their collaborators, have developed a faster and simpler way to carry out segmentation analysis, a vital process in materials science. The new method was published in the journal Science and Technology of Advanced Materials: Methods. Segmentation analysis is used to understand the fine-scale composition of a material. It identifies distinct regions (or ‘segments’) with specific compositions, structural characteristics, or properties. This helps evaluate the suitability of a material for specific functions, as well as its possible limitations. It can also be used for quality control in material fabrication and for identifying points of weakness when analyzing materials that have failed. Segmentation analysis is very important for synchrotron radiation X-ray computed tomography (SR-CT), which is similar to conventional medical CT scanning but uses intense focused X-rays produced by electrons circulating in a storage ring at nearly the speed of light. The team have demonstrated that machine learning is capable in conducting the segmentation analysis for the refraction contrast CT, which is especially useful for visualising the three-dimensional structure in samples with small density differences between regions of interest, such as epoxy resins. “Until now, no general segmentation analysis method for synchrotron radiation refraction contrast CT has been reported,” says first author Satoru Hamamoto. “Researchers have generally had to do segmentation analysis by trial and error, which has made it difficult for those who are not experts.” The team’s solution was to use machine learning methods established in biomedical fields in combination with a transfer learning technique to finely adjust to the segmentation analysis of SR-CTs. Building on the existing machine learning model greatly reduced the amount of […]

AutoStore’s new R5 Pro Robot for large-scale operations frees up space for additional products in the warehouse and improves Robot efficiency at a reduced lower total cost of ownership. AutoStore now has available the R5 Pro Robot, the latest version of the company’s field-proven R5 Robot. This new robotic solution is designed to address the specific demands of large-scale e-commerce operations, emphasising better space usage, higher performance, and reduced total ownership costs for companies running multishift operations at scale. The R5 Pro offers an edge by augmenting productivity per Robot during extended operations, optimising space usage, and reducing the total cost of ownership, ultimately enhancing the customer experience while boosting profitability. The R5 Pro is designed to meet the needs of e-commerce organizations with large-scale multishift operations. Key features and benefits of the R5 Pro Robot include: Enhanced productivity: By deploying the R5 Pro at a large AutoStore site, customers can reduce the number of Robots required on the same grid by up to 15%, when compared to using the R5 Robot, enabling better routing and enhanced system efficiency. Continuous operations: The use of an LTO (Lithium-Titanium Oxide) battery in the R5 Pro allows rapid charging, improving individual Robot availability during multishift operations. Space and Cost Optimisation: Up to 86% fewer chargers required with the LTO battery allows for more efficient use of warehouse space, accommodating additional SKU storage or reducing the required footprint. In addition, customers achieve significant cost savings related to electrical infrastructure.