In recent years, the investigation of the acoustic signals (AS) produced from different machining processes have primarily focused on the ultrasonic frequency range. The objective of this work is to propose a novel technique for predicting the flank wear condition of a tool and ultimately tool failure (insert chipping) during the process of conventional face milling. Preliminary experiments suggest that the spectral content of audible acoustic emission (AAE) signals could be used to predict the cumulative flank wear in real time for an indexable carbide insert during the milling process. The experiments conducted for this study suggest a strong correlation between the magnitudes of the AAE in the selected frequency range, and the amount of wear on the insert.

Quenching is an important part of the heat treatment process for strengthening medium and high carbon steels. In the heat treatment cycle, the metal is heated to a desired temperature (above the eutectoid temperature) in the furnace and then cooled in a fluid medium such as water, brine, oil or air. Depending on the cooling rate, the mechanical and metallurgical properties of the metal can be altered in order to achieve the specific design parameters that are required by the part. The process in which the metal is cooled rapidly is termed the quenching process. Due to rapid cooling in a medium, such as water, brine, or oil, the quenching process produces an audible sound signature, as well as, acoustic emissions. In this paper, W1 tool steel is investigated through the use of a beam former that is equipped with 32 microphones. Using this device, it is demonstrated that the audible sounds that are produced when quenching depend on the heat treatment temperature and the size of the specimen.

Wireless sensors used in plant floor environments have been studied for obstruction and multipath propagation effects on signal quality. The trend towards wireless industrial data networks motivates this study, which explores the use of IEEE 802.15.1 radios in a machine shop at varying levels of operation. Previous studies have investigated the use of a wireless sensor embedded in a rotating tool holder to monitor tool life. In order to obtain information furthering the potential use of low power radio in conjunction with machining enclosures, a Bluegiga WT12 Class 2 Bluetooth 2.1 module is placed within several CNC machining enclosures at varying table positions and heights. An exterior module receives the data from the enclosed unit, and the module’s position is also varied in 3 dimensional space. Bit Error Rate and Received Signal Strength are measured, and the effects of spatial obstruction and multipath propagation are analyzed. An Agilent 8563E spectrum analyzer equipped with an Aaronia HyperLOG 7060 EMC antenna is also used to repeat the measurements at all of the points in order to provide EMI channel characterization and a redundant source of signal power data for comparison. Large-area transmissibility testing indicates that received signal strength is not dependent upon equipment operation. The enclosure tests (perimeter, height, and proximity comparison) suggest that distance, both static and transient path obstructions, multipath propagation, and line-of-sight are factors that influence bit error rate and received signal strength. Spectrum analyzer measurements in our shop show no significant emissions in the 2.4 GHz range that cause interference. At no time during this study did the bit error rate reach 0.2% of the transmitted bits and there were no failures in transmitting text between modules. Overall, the findings indicate that reliable data transmission with low power off-the-shelf Bluetooth modules is feasible.