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This article presents the results of a set of innovative research to analyse a new structural material – steel like austempered ductile cast iron with mechanical properties similar to heat-treated steel, and with technological and exploitation characteristic close to high-strength cast iron with nodular graphite. Specific examples of its high efficiency for the manufacture of critical, mass and heavy-loaded components of modern machinery and equipment are presented. New structural material MoNiCa was tested on tension and was compared to commercial grades of austempered ductile cast irons and heat treated steels. Unconventional behaviour of examined material was observed: with tensile strength increase to almost 1600 MPa the metal became less brittle. Hardness test revealed another distinctive feature of new material that there is no linear relation between strength and hardness increase, different hardness values ~ 40 HRC or ~ 55 HRC can be achieved with the same tensile strength 1000 – 1200 MPa. Microscopic analysis demonstrated of sophisticated structure formed owing to different regimes of austempering treatment. Specific properties emerged from successful ratio of three elements Mo, Ni, and Cu (carbon equivalent), and properly chosen heat treatment modes. DOI: http://dx.doi.org/10.5755/j01.ms.25.3.23079

The influence of the austempering temperatures on the microstructure and mechanical properties of austempered ductile cast iron (ADI) was investigated. ADI is nodular graphite cast iron, which owing to higher strength and elongation, exceeds mechanical properties of conventional spheroidal graphite cast iron. Such a combination of properties is achieved by the heat treatment through austenitization, followed by austempering at different temperatures. The austenitization conditions were the same for all the samples: temperature 890 °C, duration 30 min, and quenching in a salt bath. The main focus of this research was on the influence of the austempering temperatures (270 °C, 300 °C, and 330 °C) on the microstructure evolution, elongation, toughness, and fatigue resistance of ADI modified by certain amounts of Ni, Cu, and Mo. The Vickers and Rockwell hardness decreased from 535.7 to 405.3 HV/1 (55.7 to 44.5 HRC) as the austempering temperature increased. Optical images showed the formation of graphite nodules and a matrix composed of ausferrite; the presence of these phases was confirmed by an XRD diffraction pattern. A fracture surface analysis revealed several types of the mechanisms: cleavage ductile, transgranular, and ductile dimple fracture. The stress-controlled mechanical fatigue experiments revealed that a 330 °C austempering temperature ensures the highest fatigue life of ADI.

An effective system for monitoring the wear of the machine tool inserts could significantly contribute to saving costs in manufacturing. One of the most recent and popular of effective monitoring methods revolves around the use of sensing technologies for indirect estimation of tool wear. The sensory information is difficult to collect from machine tools due to the extremely poor signal-to-noise ratio of the relevant tool wear-related information because the milling operation is of interrupted nature since the work piece is in contact with the tool edge several times per second. Another issue is the varying thickness of the chip during the penetration of the work piece. Yet, many challenges still impede the practical application of this method for industrial environment. Therefore, the paper presents a method that could solve these challenges especially in industrial environment. The proposed selfpowered wireless sensor node is integrated in the structure of the cutting tool. The voltage generated from the cutting tool vibrations of the harvester exponentially rises when the capacitor is fully charged and wireless signal sent to the receiver. As the intensity of energy accumulation depends on the state of the cutting tool wear, it indicates and detects the tool condition. The proposed technique could be useful for the identification of the cutting tool quality and the relative tool-work piece position. The information about the variation of tool wear is beneficial for helping the manufacturers to control the cutting process, to minimize the product cost as well as to improve the machining quality and efficiency.

This research presents the results of tribo-fatigue behavior of austempered ductile cast iron MoNiCa and gives a comparison with standard grades of steel and cast iron. Due to the possibility to combine the castability of cast iron and toughness of steel in one material, new structural material MoNiCa attracted attention of industry and science because of economic benefits and high performance at the different application areas. After successful former experiments the main directions of further development of research for solving relevant practical wear and fatigue problems in rail-wheel system were framed. The complex experimental studies have demonstrated that MoNiCa is consistent with heat treated steels including the rail steels: required tensile strength of rail steel ranges from 1180 MPa to 1280 MPa when rolling surface hardness have to be from 38 HRC to 44 HRC whereas new structural material showed higher tensile strength up to 1400 MPa and slightly higher hardness up to 50 HRC. Herewith the workability of frictional couple cast iron MoNiCa/steel 20MnCr5G exceeds work performance of steel/steel system by 14 %.

There are many tool condition monitoring solutions that use a variety of sensors. This paper presents a self-powering wireless sensor node for shank-type rotating tools and a method for real-time end mill wear monitoring. The novelty of the developed and patented sensor node is that the longitudinal oscillations, which directly affect the intensity of the energy harvesting, are significantly intensified due to the helical grooves cut onto the conical surface of the tool holder horn. A wireless transmission of electrical impulses from the capacitor is proposed, where the collected electrical energy is charged and discharged when a defined potential is reached. The frequency of the discharge pulses is directly proportional to the wear level of the tool and, at the same time, to the surface roughness of the workpiece. By employing these measures, we investigate the support vector machine (SVM) approach for wear level prediction.

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