Front Cover: EURO PM2026 by EPMA

The Euro PM2026 Congress & Exhibition, organised by the European Powder Metallurgy Association (EPMA), will take place in Budapest, Hungary, from 11-14 October 2026 at the Hungexpo Center. Euro PM2026 will feature a world-class technical programme and a 2500 m² exhibition showcasing the latest innovations from the global powder metallurgy (PM) supply chain.

www.europm2026.com

10) A Wow effect: LDDM meeting at the Antolini^® MilanoDuomo Stoneroom^®

18) Construtec 2026: building the future at IFEMA Madrid

22) Regional initiative: second update of the "Sicily quarry plan"

32) The job site during operations. Operational observations on the working area in diamond tool applications

Operations involving diamond tools are often perceived as rapid and localized interventions. Core drilling, wall chasing, localized cutting, or controlled demolition activities may last only a few minutes and occupy apparently limited areas.
In everyday practice, however, the job site continuously changes during these operations. The working area never corresponds solely to the point where the tool is operating. Around the machine, movements, temporary supports, cables, hoses, removed materials, support equipment, and access routes progressively develop and expand throughout the working day. This aspect becomes particularly evident in real working environments: interior renovations, technical rooms, stairwells, under-ground parking facilities, occupied buildings, or job sites where multiple activities are carried out simultaneously. These are environments in which specialized operations must coexist with limited space, tight schedules, and the operational continuity of other site activities...

39) From sintering route to cutting response: circular-saw granite cutting with microwave-hybrid sintered diamond segments

Abstract: Balancing low segment wear with stable cutting forces remains a challenge in granite sawing. This work compares diamond-impregnated saw segments produced by microwave-hybrid sintering (MWHS) and hot pressing (HP) when cutting Rosa Porriño granite. Tests were performed under tap-water cooling (22 L min^-1) while varying peripheral speed (20-40 m s^-1), feed speed (22-38 mm s^-1), and cutting depth (9-18 mm). Cutting forces were recorded during successive slots, and wear was quantified as mass loss per machined area (1.2-3.0 m² per test). MWHS segments exhibited lower wear than HP segments, with reductions up to ~20%, consistent with improved diamond retention and reduced binder exposure to debris-driven abrasion. Under higher cutting severity, however, MWHS segments developed higher forces, indicating reduced grit renewal and progressive blunting, plausibly linked to stronger diamond-matrix bonding and the low-friability diamond grade used. In contrast, HP segments operated at lower forces but showed higher wear, consistent with greater surface renewal through controlled grit release. Tuning diamond friability and matrix compliance in MWHS is proposed to stabilize forces while preserving the wear advantage. Overall, MWHS is a viable route for granite cutting segments, but further optimization is required to achieve HP-equivalent behavior across the tested conditions...

53) Back propagation neural network-based prediction model of marble surface quality cut by diamond wire saw

Abstract: Marble is widely used in the field of construction and home decoration because of its high strength, high hardness and good wear resistance. Diamond wire sawing has been applied in marble cutting in industry due to its features such as low material loss, high cutting accuracy and low noise. The sawing surface quality directly affects the subsequent processing efficiency and economic benefit of marble products. The surface quality is affected by multiple parameters such as process parameters and workpiece sizes, making it difficult to accurately predict through traditional empirical equations or linear models. To improve prediction accuracy, this paper proposes a prediction model based on backpropagation (BP) neural network. Firstly, through the experiments of sawing marbles with the diamond wire saw, the datasets of surface roughness and waviness under different process parameters were obtained. Secondly, a BP neural network model was established, and the mixed-strategy-improved whale optimization algorithm (IWOA) was used to optimize the initial weight and threshold of the network, and established the IWOA-BP neural network model. Finally, the performance of the model was verified by comparison with the traditional models. The results showed that the IWOA-BP neural network model demonstrated the optimal prediction performance in both the surface roughness Ra and waviness Wa. The minimum predicted values of the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) were 0.0342%, 0.0284% and 1.5614%, respectively, which proved that the model had higher prediction accuracy. This study provides experimental basis and technical support for the prediction of the surface quality of marble material cut by diamond wire saw...

72) SAIE Lab On Tour: three stops, over 600 professionals and an industry moving toward SAIE Bologna

75) 32nd Marble Izmir to Be Held on 13-16 April 2027