Monitoring the condition of the cutting tool using self-powering wireless sensor technologies

Abstract

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.

Simultaneous Wireless Power and Data Transmission Over One Pair of Coils for Sensor-Integrated Rotating Cutter

“…Due to the limitations of current wired sensor systems, and in order to reduce the invasion degree of sensor system into the milling or drilling process and increase flexibility, a series of wireless sensor-integrated systems for rotating cutter have been developed [8]- [23], in which the sensors and other electronic components, such as sensor signal processing module, wireless data transfer module, and power supply module, are all integrated into the tool holder. For the key wireless data transfer module, the common technologies, namely Bluetooth [8]- [11], ZigBee [12]- [14], WiFi [15]- [20], Radio frequency identification (RFID) [21] and sub-1 GHz radio frequency [22], [23], have been adopted to transmit the measured condition data wirelessly to a upper host computer. It can be noted that WiFi is the most widely used transmission method for tool condition monitoring, which has the potential to be competitor of other wireless transmission technologies taking into account of its relatively high transmission speed and long transmission distance.…”

Monitoring high complex production processes using process capability indices

“…Thanks to SPM, it is possible to detect production system failures such as collision, overload, breakdown, and tool wear [3]; and thus, it is contributing to saving costs in manufacturing [4]. In this sense, SPM can increase the competitiveness of a machining process by increasing the utilized tool life and decreasing instances of part damage from excessive tool wear or tool breakage [5].…”

“…On the other hand, since the machining of the crankcases is not capable, he or she has to continue with the capability analysis and go one level deeper (feature). The third level (feature) suggests that the machining process is not capable for Hole A and that the process is critical (P CI (4) between 1 and 1.33) for Hole C . Now, the decision maker has to go one level deeper for both sets of product characteristics in order to nd the origin of the capability problems.…”

A review of univariate and multivariate process capability indices

“…C n = s max s (10) As it can be seen, a process is capable (C n values higher than 1) if the variability of the measured product characteristic (s) is smaller than the maximal allowable one (s max ). Veevers [27] introduced the concept of Viability (V r ) of a process by describing its window of opportunity (w).…”

“…The pioner of optimization models of production processes based on quality costs was Taguchi [7], whose principles and theories are accepted as reference models due to the revolution that they supposed to quality methods. In this context, Statistical Process Monitoring (SPM) is rated as a very important area of process control [8], to ensure economic productivity by detecting production failures such as collision or tool wear [9] and is contributing to saving costs in manufacturing [10].…”