Tool remaining useful life prediction considering wear state based on hybrid attention network
Shihao Wu,
Yang Li,
Weiguang Li
et al.
Abstract:Accurate prediction of the remaining useful life for the cutting tool is a key part of the predictive maintenance of computer numerical control machines. However, the wide variety of tools makes the process of modeling different tool wear regularities redundant and cumbersome. In addition, it is difficult to deal with the input characteristics of multi-sensor monitoring signals in a targeted manner. To solve the above problems, a hybrid predictive model with squeeze-and-excitation (SE) module is proposed. Comb… Show more
PurposeThe aim of this paper is to review the literature on the prediction of cutting tool life. Tool life is typically estimated by predicting the time to reach the threshold flank wear width. The cutting tool is a crucial component in any machining process, and its failure affects the manufacturing process adversely. The prediction of cutting tool life by considering several factors that affect tool life is crucial to managing quality, cost, availability and waste in machining processes.Design/methodology/approachThis study has undertaken the critical analysis and summarisation of various techniques used in the literature for predicting the life or remaining useful life (RUL) of the cutting tool through monitoring the tool wear, primarily flank wear. The experimental setups that comprise diversified machining processes, including turning, milling, drilling, boring and slotting, are covered in this review.FindingsCutting tool life is a stochastic variable. Tool failure depends on various factors, including the type and material of the cutting tool, work material, cutting conditions and machine tool. Thus, the life of the cutting tool for a particular experimental setup must be modelled by considering the cutting parameters.Originality/valueThis submission discusses tool life prediction comprehensively, from monitoring tool wear, primarily flank wear, to modelling tool life, and this type of comprehensive review on cutting tool life prediction has not been reported in the literature till now. The future suggestions provided in this review are expected to provide avenues to solve the unexplored challenges in this field.
PurposeThe aim of this paper is to review the literature on the prediction of cutting tool life. Tool life is typically estimated by predicting the time to reach the threshold flank wear width. The cutting tool is a crucial component in any machining process, and its failure affects the manufacturing process adversely. The prediction of cutting tool life by considering several factors that affect tool life is crucial to managing quality, cost, availability and waste in machining processes.Design/methodology/approachThis study has undertaken the critical analysis and summarisation of various techniques used in the literature for predicting the life or remaining useful life (RUL) of the cutting tool through monitoring the tool wear, primarily flank wear. The experimental setups that comprise diversified machining processes, including turning, milling, drilling, boring and slotting, are covered in this review.FindingsCutting tool life is a stochastic variable. Tool failure depends on various factors, including the type and material of the cutting tool, work material, cutting conditions and machine tool. Thus, the life of the cutting tool for a particular experimental setup must be modelled by considering the cutting parameters.Originality/valueThis submission discusses tool life prediction comprehensively, from monitoring tool wear, primarily flank wear, to modelling tool life, and this type of comprehensive review on cutting tool life prediction has not been reported in the literature till now. The future suggestions provided in this review are expected to provide avenues to solve the unexplored challenges in this field.
To resolve the issue of cooperative operation between large fixed wing Unmanned Aerial Vehicle (UAV) and civil aviation manned transport aircraft, preprocessing of large fixed wing UAV flight data that oriented to spatial dimension will be carried out to further complete the mathematical description and sort out the characteristics of the flight data of the digital twins, analyze the track protection zone of flight program recommended by International Civil Aviation Organization (ICAO) and systematic errors such as collision risks, then develop a flight conflict detection method applied to cooperative operation in joint airspace and draw certain quantitative conclusion. According to the simulation experiments and calculation results, it is shown that the use of the multi-element composite strategy (MCS) can achieve the flight conflict assessment of the joint airspace cooperative operation, and according to the assessment results combined with the implementation environment of the flight mission, it can be concluded that the density of the airspace is within the range of the systematic error standard stipulated by the ICAO, so as to complete the quantitative assessment of the safety risk of the cooperative operation and the planning scheme of the joint airspace Preliminary formulation, to provide support for the development of intelligent logistics.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.