Industrial automation increasingly relies on multi-agent AI, yet evaluation remains difficult due to task complexity and data confidentiality. We present AssetOpsBench-Live, a demo of a competition-ready platform for real-time, privacy-preserving evaluation of multi-agent AI in industrial contexts. The platform integrates AssetOpsBench, which measures six dimensions of multi-agent performance and performs automated failure-mode discovery, with Codabench, which supports reproducible, code-oriented competitions. End users first validate agents locally, then submit containerized code for execution on hidden industrial scenarios. Instead of raw trajectories, the system provides quantitative scores and clustered failure modes (e.g., reasoning--action mismatch, step repetition), enabling participants to identify failures, apply targeted improvements, and iteratively resubmit. By combining competition-based engagement with actionable diagnostics, AssetOpsBench-Live delivers reproducible, real-time insights reflecting real-world industrial constraints.
Competition retrospectives are useful when they explain what a leaderboard measured, how hidden evaluation changed conclusions, and which design patterns were rewarded. We revisit the CODS 2025 challenge, a privacy-aware Codabench competition on industrial multi-agent orchestration built on . We combine final rank sheets, a 300-submission server log, 149-team registrations, best-submission exports, the organizer winners report, the companion system paper, and verified planning-track source trees. Five results stand out. First, the public planning leaderboard saturates at 72.73%, and richer prompts do not improve that peak. Second, hidden evaluation changes the story: public and private scores correlate moderately in planning (r=0.69) but negatively in execution (r=-0.13), with several 45.45% public execution systems reaching 63.64% on the hidden set. Third, the term is numerically almost inert in the official composite – combined on a 0–1 scale with 0–100 percentage scores, it contributes at most 0.05 points per track, and rescaling would swap the top two teams. Fourth, the competition is operationally account-based but substantively team-based: 149 registered teams reduce to 24 with non-zero public scores and 11 fully ranked, while 52.3% of deduplicated registrations list multiple usernames. Fifth, successful execution methods mostly improve guardrails – response selection, contamination cleanup, fallback, and context control – rather than novel agent architectures. These findings identify which behaviors the evaluation rewarded, and motivate scale-aware composites, skill-level diagnostics, and versioned artifact release.
Thermomechanical controlled processing (TMCP) serves as a key factor in determining the mechanical characteristics of high-strength low-alloy (HSLA) steels. This research investigates how key processing conditions—including the rolling draft schedule, finish rolling temperature, exit temperature of accelerated cooling (ACC), and rate of cooling—affect the microstructural development and mechanical properties of Nb-Mo-V-Ti containing steel. To evaluate these effects, tensile and Charpy impact tests are conducted, supported by optical and scanning electron microscopy, along with electron backscatter diffraction (EBSD) analyses. The results indicate that changes in finishing rolling temperature, accelerated cooling exit temperature, and cooling rate produce distinct microstructural features, which in turn result in significant variations in strength, toughness, and overall mechanical performance of the steel. The TMCP schedule involving controlled rolling within the α + γ dual-phase region, coupled with a reduced finishing temperature, lower ACC exit temperature, and higher cooling rate, promotes pronounced microstructural refinement. This processing route facilitates the formation of finer polygonal and quasi-polygonal ferrite, acicular ferrite, and bainitic constituents, along with a dense subgrain structure and finely dispersed precipitates. The increased fraction of low-angle grain boundaries and elevated dislocation density collectively contribute to enhanced yield strength, tensile strength, and impact toughness, demonstrating the strong dependence of mechanical performance on the evolved microstructures. Furthermore, under identical TMCP conditions, the lower carbon steel exhibits improved tensile strength–ductility balance, superior impact toughness, and enhanced weldability. Although the individual contributions of specific TMCP parameters are not independently isolated in the present investigation, the study provides a systematic evaluation of how combined thermomechanical processing variables and alloy design interact to control microstructural evolution and ultimately dictate the structure–mechanical property relationships in controlled rolled Nb-Mo-V-Ti high-strength low-alloy (HSLA) steels.
The generation of coke dust waste from steel industries represents a significant environmental challenge, particularly in developing countries such as India. Conventionally, this waste is utilized as a low-value fuel in boilers, resulting in increased carbon emissions and underutilization of its resource potential. The prepared adsorbent, designated as coke dust-based activated carbon (CDBAC), was synthesized through KOH-assisted thermo-chemical activation following a washing pretreatment.The physicochemical properties of CDBAC were characterized using ultimate and proximate analyses, Brunauer–Emmett–Teller (BET) surface area analysis, X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and field-emission scanning electron microscopy (FESEM). The batch adsorption was studied by varying concentration, pH, agitation rate, temperature, and dose amount. Continuous adsorption was performed to explore its industrial use as well. Its thermodynamic and Kinetic study was done along with economic analysis.The prepared CDBAC exhibited high carbon content (87.52 wt%), low ash (9.68 wt%), and low moisture (0.55 wt%), confirming favourable adsorbent characteristics. BET analysis revealed a high specific surface area of 1605.50 m2 g−1, a total pore volume of 1.09 cm3 g−1, and an average pore diameter of 3.57 nm. Under optimized batch conditions (30 °C, pH 7, agitation speed of 125 rpm, and adsorbent dosage of 4.5 g L−1), a maximum adsorption capacity of 388.9 mg g−1 was achieved, corresponding to a methylene blue removal efficiency of 95.54% within 100 min. Continuous fixed-bed experiments demonstrated a column adsorption capacity of 238.63 mg g−1 with a breakthrough time of 220 min at a bed height of 4.5 cm. The adsorption process was found to be spontaneous and exothermic in nature, while regeneration studies confirmed the reusability of the adsorbent over multiple cycles.
Graphite electrodes are a vital consumable in ladle furnace (LF) steelmaking significantly influencing operational costs through their role in electrical energy delivery, temperature control, and secondary refining. This study evaluates two industrial-scale process optimizations to reduce electrode consumption: slag chemistry modification and electrode tip spray cooling. Slag basicity was increased from 1.22 to 1.47 while reducing FeO below 1.5 wt
