A Probabilistic-Based Approach to Monitoring Tool Wear State and Assessing Its Effect on Workpiece Quality in Nickel-Based Alloys

The objective of this research is first to investigate the applicability and advantage of statistical state estimation methods for predicting tool wear in machining nickel-based superalloys over deterministic methods, and second to study the effects of cutting tool wear on the quality of the part. Nickel-based superalloys are among those classes of materials that are known as hard-to-machine alloys. These materials exhibit a unique combination of maintaining their strength at high temperature and have high resistance to corrosion and creep. These unique characteristics make them an ideal candidate for harsh environments like combustion chambers of gas turbines. However, the same characteristics that make nickel-based alloys suitable for aggressive conditions introduce difficulties when machining them. High strength and low thermal conductivity accelerate the cutting tool wear and increase the possibility of the in-process tool breakage. A blunt tool nominally deteriorates the surface integrity and damages quality of the machined part by inducing high tensile residual stresses, generating micro-cracks, altering the microstructure or leaving a poor roughness profile behind. As a consequence in this case, the expensive superalloy would have to be scrapped. The current dominant solution for industry is to sacrifice the productivity rate by replacing the tool in the early stages of its life or to choose conservative cutting conditions in order to lower the wear rate and preserve workpiece quality. Thus, monitoring the state of the cutting tool and estimating its effects on part quality is a critical task for increasing productivity and profitability in machining superalloys. This work aims to first introduce a probabilistic-based framework for estimating tool wear in milling and turning of superalloys and second to study the detrimental effects of functional state of the cutting tool in terms of wear and wear rate on part quality. In the milling operation, the mechanisms of tool failure were first identified and, based on the rapid catastrophic failure of the tool, a Bayesian inference method (i.e., Markov Chain Monte Carlo, MCMC) was used for parameter calibration of tool wear using a power mechanistic model. The calibrated model was then used in the state space probabilistic framework of a Kalman filter to estimate the tool flank wear. Furthermore, an on-machine laser measuring system was utilized and fused into the Kalman filter to improve the estimation accuracy. In the turning operation the behavior of progressive wear was investigated as well. Due to the nonlinear nature of wear in turning, an extended Kalman filter was designed for tracking progressive wear, and the results of the probabilistic-based method were compared with a deterministic technique, where significant improvement (more than 60% increase in estimation accuracy) was achieved. To fulfill the second objective of this research in understanding the underlying effects of wear on part quality in cutting nickel-based superalloys, a comprehensive study on surface roughness, dimensional integrity and residual stress was conducted. The estimated results derived from a probabilistic filter were used for finding the proper correlations between wear, surface roughness and dimensional integrity, along with a finite element simulation for predicting the residual stress profile for sharp and worn cutting tool conditions. The output of this research provides the essential information on condition monitoring of the tool and its effects on product quality. The low-cost Hall effect sensor used in this work to capture spindle power in the context of the stochastic filter can effectively estimate tool wear in both milling and turning operations, while the estimated wear can be used to generate knowledge of the state of workpiece surface integrity. Therefore the true functionality and efficiency of the tool in superalloy machining can be evaluated without additional high-cost sensing

Time-Variant Reliability Assessment and Its Sensitivity Analysis of Cutting Tool under Invariant Machining Condition Based on Gamma Process

The time-variant reliability and its sensitivity of cutting tools under both wear deterioration and an invariant machining condition are analyzed. The wear process is modeled by a Gamma process which is a continuous-state and continuous-time stochastic process with the independent and nonnegative increment. The time-variant reliability and its sensitivity of cutting tools under six cases are considered in this paper. For the first two cases, the compensation for the cutting tool wear is not carried out. For the last four cases, the off-line or real-time compensation method is adopted. While the off-line compensation method is used, the machining error of cutting tool is supposed to be stochastic. Whether the detection of the real-time wear is accurate or not is discussed when the real-time compensation method is adopted. The numerical examples are analyzed to demonstrate the idea of how the reliability of cutting tools under the invariant machining condition could be improved according to the methods described in this paper

Multi-categories tool wear classification in micro-milling

Ph.DDOCTOR OF PHILOSOPH

Micro/Nano Manufacturing

Micro- and nano-scale manufacturing has been the subject of ever more research and industrial focus over the past 10 years. Traditional lithography-based technology forms the basis of micro-electro-mechanical systems (MEMS) manufacturing, but also precision manufacturing technologies have been developed to cover micro-scale dimensions and accuracies. Furthermore, these fundamentally different technology platforms are currently combined in order to exploit the strengths of both platforms. One example is the use of lithography-based technologies to establish nanostructures that are subsequently transferred to 3D geometries via injection molding. Manufacturing processes at the micro-scale are the key-enabling technologies to bridge the gap between the nano- and the macro-worlds to increase the accuracy of micro/nano-precision production technologies, and to integrate different dimensional scales in mass-manufacturing processes. Accordingly, this Special Issue seeks to showcase research papers, short communications, and review articles that focus on novel methodological developments in micro- and nano-scale manufacturing, i.e., on novel process chains including process optimization, quality assurance approaches and metrology

Emerging environmental contaminants and human health : risk assessment of dietary exposure to microplastics

Microplastics (MPs) are an emerging contaminant ubiquitous in the environment. There is growing concern regarding potential human health effects. A major human exposure route is hypothesised to be the dietary pathway via ingestion of contaminated food. A risk assessment perspective was employed, which is the standard approach for human health protection regarding food safety. It is comprised of the four interconnected evidence-based steps of hazard identification, hazard characterization, exposure assessment and risk characterization. Existing scientific data were collected via the execution of scoping, systematic and rapid reviews, using state of the art, robust methodology. Quantitative meta- analysis and meta-regression analyses were also employed. Two bespoke novel risk-of-bias tools were developed and implemented in the execution of the reviews for the standardized quality appraisal of the studies.Seventy-two studies were included in the systematic reviews on food contamination from three categories. The majority of the samples were contaminated in varying levels: 0-4889 MPs/L in drinking water, 0–10.5 MPs/g in seafood and 0–1674 MPs/kg in salt, thus establishing the dietary ingestion route for MP human exposures. According to the exposure assessment modelling, the estimated levels for MP dietary aggregate exposures could be as high as 3.6 million MPs per year.Seventeen studies were included in a rapid review focusing on human cell in vitro MP toxicological effects. Four biological endpoints displayed MP-associated effects: cytotoxicity, immune response, oxidative stress and barrier attributes. Irregular shape was found to be the only MP characteristic predicting cell death, along with the duration of exposure and MP concentration (μg/mL). Minimum concentrations of 10 μg/mL (5– 200 μm), had an adverse effect on cell viability, and 20 μg/mL (0.4 μm) on cytokine release, effectively constituting thresholds of adverse effects. The preliminary comparison of the levels of the thresholds and the exposures reveals that human health could be at risk due to MP dietary exposures.Further high-quality research using standardized methods is needed to cement the scientific evidence on MP contamination and human exposures. On the other hand, serious data gaps exist regarding toxicodynamics and toxicokinetics which are necessary for a complete toxicological profile

Advances in Robotics, Automation and Control

The book presents an excellent overview of the recent developments in the different areas of Robotics, Automation and Control. Through its 24 chapters, this book presents topics related to control and robot design; it also introduces new mathematical tools and techniques devoted to improve the system modeling and control. An important point is the use of rational agents and heuristic techniques to cope with the computational complexity required for controlling complex systems. Through this book, we also find navigation and vision algorithms, automatic handwritten comprehension and speech recognition systems that will be included in the next generation of productive systems developed by man

Focused ion beam technology : implementation in manufacturing platforms and process optimisation

Process chains are regarded as viable manufacturing platforms for the production of Microand Nano Technology (MNT) enabled products. In particular, by combining several manufacturing technologies, each utilised in its optimal process window, they could benefit from the unique advantages of high-profile research technologies such as the focused ion beam (FIB) machining. The present work concerns the development of process chains and the investigation of pilot cost-effective implementations of the FIB technology in manufacturing platforms forfabrication of serial replication masters.EThOS - Electronic Theses Online ServiceGBUnited Kingdo