Intelligent Machining Systems

Machining is one of the most widespread manufacturing processes and plays a critical role in industries. As a matter of fact, machine tools are often called mother machines as they are used to produce other machines and production plants. The continuous development of innovative materials and the increasing competitiveness are two of the challenges that nowadays manufacturing industries have to cope with. The increasing attention to environmental issues and the rising costs of raw materials drive the development of machining systems able to continuously monitor the ongoing process, identify eventual arising problems and adopt appropriate countermeasures to resolve or prevent these issues, leading to an overall optimization of the process. This work presents the development of intelligent machining systems based on in-process monitoring which can be implemented on production machines in order to enhance their performances. Therefore, some cases of monitoring systems developed in different fields, and for different applications, are presented in order to demonstrate the functions which can be enabled by the adoption of these systems. Design and realization of an advanced experimental machining testbed is presented in order to give an example of a machine tool retrofit aimed to enable advanced monitoring and control solutions. Finally, the implementation of a data-driven simulation of the machining process is presented. The modelling and simulation phases are presented and discussed. So, the model is applied to data collected during an experimental campaign in order to tune it. The opportunities enabled by integrating monitoring systems with simulation are presented with preliminary studies on the development of two virtual sensors for the material conformance and cutting parameter estimation during machining processes

Performance improvement of the LM device and its application to precise measurement of motion trajectories within a small range with a machining centre

In order to apply the LM device previously developed to precisely measuring small motion trajectories located on the different motion planes, three major improvements are successfully performed under the condition of completely maintaining the advantages of the device. These improvements include 1) development of a novel connection mechanism to smoothly attach the device to the spindle of a machining centre; 2) employment of a new data sampling method to achieve a high sampling frequency independent of the operating system of the control computer; and 3) proposal of a set-up method to conveniently install the device on the test machining centre with respect to different motion planes. Practical measurement experiment results with the improved device on a machining centre sufficiently demonstrate the effectiveness of the improvements and confirm several features including a very good response to small displacement close to the resolution of the device, high precision, repeatability and reliance. Moreover, based on the measurement results for a number of trajectories for a wide range of motion conditions, the error characteristics of small size motions are systematically discussed and the effect of the movement size and feed rate on the motion accuracy is verified for the machining centre tested

Smart machining system platform for CNC milling with the integration of a power sensor and cutting model

Novel techniques and strategies are investigated for dynamically measuring the process capability of machine tools and using this information for Smart Machine System (SMS) research. Several aspects of the system are explored including system integration, data acquisition, force and power model calibration, feedrate scheduling and tool condition monitoring. A key aspect of a SMS is its ability to provide synchronization between process measurements and model estimates. It permits real time feedback regarding the current machine tool process. This information can be used to accurately determine and keep track of model coefficients for the actual tooling and materials in use, providing both a continued improvement in model accuracy as well as a way to monitor the health of the machine and the machining process. A cutting power model is applied based on a linear tangential force model with edge effect. The robustness of the model is verified through experiments with a wide variety of cutting conditions. Results show good agreement between measured and estimated power. A test platform has been implemented for performing research on Smart Machine Systems. It uses a commercially available OAC from MDSI, geometric modeling software from Predator along with a number of modules developed at UNH. Test cases illustrate how models and sensors can be combined to select machining conditions that will produce a good part on the first try. On-line calibration allows the SMS to fine tune model coefficients, which can then be used to improve production efficiency as the machine learns its own capabilities. With force measurements, the force model can be calibrated and resultant force predictions can be performed. A feedrate selection planner has been created to choose the fastest possible feedrates subject to constraints which are related to part quality, tool health and machine tool capabilities. Monitoring tangential model coefficients is shown to be more useful than monitoring power ratio for tool condition monitoring. As the model coefficients are independent of the cutting geometry, their changes are more promising, in that KTC will increase with edge chipping and breakage, while KTE will increase as the flank wearland expands

The effectiveness of computer simulation in training programmers for computer numerical control machining

The purpose of this study was to investigate the effectiveness of microcomputer simulation, and to compare the differences in skill mastery and in the need for a teacher\u27s assistance among students using a microcomputer with a partner, using a microcomputer alone, and those who did not use a microcomputer simulator in learning CNC programming skills;A pretest-posttest control group design was used in this study. All of the students obtaining scores in pretest were taken out from the research to assure the homogeneity of the subjects;A total of ninety students was randomly selected from five classes in National Yunlin Institute of Technology in Taiwan. These students were further randomly assigned to three groups;A Chinese microcomputer package was used for the research. The experimental process was completed in three weeks. There were a total of eighteen hours of instruction;A multiple covariance analysis was used to analyze the data. Students\u27 previous experiences in mathematics, mechanical drafting, and computer concepts were used as control variables;The findings of the study revealed that mathematics scores and mechanical drafting scores did not have a significant effect on the posttest scores. The results of further analysis showed that there is no significant difference in achievement among those three groups. However, the number of questions raised per student in each group during the programming practice period was significantly different. Group one students, those who used program simulation packages individually, had significantly more questions per student than those who used program simulation packages with a partner or those who did not use a microcomputer. It was also noticed that during the experimental period students in the groups of using computers were more motivated in learning programming skills. It was therefore concluded that computer simulation is as effective as the traditional method. The teacher in a CNC laboratory could spend less time on students when they are working on a microcomputer simulator in pairs. The teacher then could spend more time helping students who are running programs on a CNC machine tool

A simulation approach for predicting energy use during general milling operations

Manufacturing processes have a high impact on global energy consumption. Machine tool’s environmental impact is typically dominated by the energy absorbed during the use phase. Energy efficiency is progressively considered as an additional performance index in comparing alternative machines, process planning, and machining strategies. For this purpose, this paper proposes a simulation approach that estimates the energy used by a machine tool in producing a generic workpiece by general milling operations. The developed tool simulates the execution of a standard ISO part program, basing on an explicit geometric and mechanistic representation of the cutting process, coupled with an energy model of the machine tool reproducing the power consumption of spindle, axes, and auxiliary units. Energy models were identified by an experimental characterization procedure that can be easily adopted in industrial contexts. The simulator was validated comparing the estimated energy with measurements performed on different cutting tests, evaluating also its computational effort. Moreover, the simulator performances were compared to alternative energy evaluation methods proposed in the literature

Traceability of on-machine tool measurement: a review

Nowadays, errors during the manufacturing process of high value components are not acceptable in driving industries such as energy and transportation. Sectors such as aerospace, automotive, shipbuilding, nuclear power, large science facilities or wind power need complex and accurate components that demand close measurements and fast feedback into their manufacturing processes. New measuring technologies are already available in machine tools, including integrated touch probes and fast interface capabilities. They provide the possibility to measure the workpiece in-machine during or after its manufacture, maintaining the original setup of the workpiece and avoiding the manufacturing process from being interrupted to transport the workpiece to a measuring position. However, the traceability of the measurement process on a machine tool is not ensured yet and measurement data is still not fully reliable enough for process control or product validation. The scientific objective is to determine the uncertainty on a machine tool measurement and, therefore, convert it into a machine integrated traceable measuring process. For that purpose, an error budget should consider error sources such as the machine tools, components under measurement and the interactions between both of them. This paper reviews all those uncertainty sources, being mainly focused on those related to the machine tool, either on the process of geometric error assessment of the machine or on the technology employed to probe the measurand

Development of a moderate-cost device for teaching numerical control programming

The study was undertaken to develop a machine which could be used to provide a realistic experience in the operation of a numerically controlled machine at moderate cost. The machine was designed to be used in the high school industrial arts laboratory. The machine was controlled by a microcomputer which was interfaced to stepping motors which powered a plotting table and the quill feed of a drill press. A router bit was placed in the chuck, so student selected designs could be cut in wood or plastic;The development of the machine and computer program was followed by a study of the effects of its use in a high school industrial arts curriculum on the students\u27 acquisition of numerical control and automated manufacturing concepts, on their development of numerical control programming skills, and on their attitudes toward numerical control and the unit of study;The results of data analysis of the posttest and attitude instruments did not support use of the prototype machine to enhance concept acquisition, skill development, or positive attitudes toward the unit of study, although it was noted that all but four of the approximately 230 students participating in the study or pilot studies developed skills sufficient to complete at least one numerical control programming project successfully