Virtual Machining: Capabilities and Challenges of Process Simulations in the Aerospace Industry

AbstractMilling processes for the manufacturing of parts for aerospace applications can be influenced by various effects. When machining structural parts with high material removal rates, the stiffness of the machine tool can be a limiting factor because chatter vibrations. Additionally, vibrations of thin-walled structures, e. g., the blades of impellers or turbines, can lead to chatter vibrations and surface location errors. Thermo-mechanical deformations are another cause for violations of given shape tolerances. Geometric physically-based process simulations can be used to analyze milling processes with regard to these effects in order to optimize the process parameters. In this paper, an overview of several applications of a geometric physically-based simulation system for analyzing different effects during milling processes is presented. Depending on the relevant effects, process forces, the dynamic behaviour of the tool-spindle-machine system, vibrations of workpieces and fixture systems, as well as thermo-mechanical deformations are calculated

Virtual Machining: Capabilities and Challenges of Process Simulations in the Aerospace Industry

AbstractMilling processes for the manufacturing of parts for aerospace applications can be influenced by various effects. When machining structural parts with high material removal rates, the stiffness of the machine tool can be a limiting factor because chatter vibrations. Additionally, vibrations of thin-walled structures, e. g., the blades of impellers or turbines, can lead to chatter vibrations and surface location errors. Thermo-mechanical deformations are another cause for violations of given shape tolerances. Geometric physically-based process simulations can be used to analyze milling processes with regard to these effects in order to optimize the process parameters. In this paper, an overview of several applications of a geometric physically-based simulation system for analyzing different effects during milling processes is presented. Depending on the relevant effects, process forces, the dynamic behaviour of the tool-spindle-machine system, vibrations of workpieces and fixture systems, as well as thermo-mechanical deformations are calculated

Prediction of temperature induced shape deviations in dry milling

In this paper a model for a simulation based prediction of temperature induced shape deviations in dry milling is presented. A closed loop between Boolean material removal, process forces, heat flux and thermoelastic deformation is established. Therefore, an efficient dexel based machining simulation is extended by a contact zone analysis to model the local workpiece load. Based on the computed contact zone the cutting forces and heat flux are calculated using a semi-empirical process model. For a detailed consideration of the loads they are discretized and localized on the dexel-represented workpiece surface. A projection of the localized workpiece loads on the boundary of the finite element domain, taking into account the Boolean material removal during the process, allows the calculation of the current temperature and deformation of the workpiece. By transforming these thermomechanical characteristics back to the dexel-model a consideration in the machining simulation is possible. An extended contact zone analysis is developed for the prediction of the localized shape deviations. Finally, the results of the simulation are compared with measured data. The comparison shows that workpiece temperatures, workpiece deformation and shape deviations in different workpiece areas are predicted accurately.DFG/DE 447/90-2DFG/MA 1657/21-

IN-SITU CHARACTERIZATION OF SURFACE QUALITY IN γ-TiAl AEROSPACE ALLOY MACHINING

The functional performance of critical aerospace components such as low-pressure turbine blades is highly dependent on both the material property and machining induced surface integrity. Many resources have been invested in developing novel metallic, ceramic, and composite materials, such as gamma-titanium aluminide (γ-TiAl), capable of improved product and process performance. However, while γ-TiAl is known for its excellent performance in high-temperature operating environments, it lacks the manufacturing science necessary to process them efficiently under manufacturing-specific thermomechanical regimes. Current finish machining efforts have resulted in poor surface integrity of the machined component with defects such as surface cracks, deformed lamellae, and strain hardening. This study adopted a novel in-situ high-speed characterization testbed to investigate the finish machining of titanium aluminide alloys under a dry cutting condition to address these challenges. The research findings provided insight into material response, good cutting parameter boundaries, process physics, crack initiation, and crack propagation mechanism. The workpiece sub-surface deformations were observed using a high-speed camera and optical microscope setup, providing insights into chip formation and surface morphology. Post-mortem analysis of the surface cracking modes and fracture depths estimation were recorded with the use of an upright microscope and scanning white light interferometry, In addition, a non-destructive evaluation (NDE) quality monitoring technique based on acoustic emission (AE) signals, wavelet transform, and deep neural networks (DNN) was developed to achieve a real-time total volume crack monitoring capability. This approach showed good classification accuracy of 80.83% using scalogram images, in-situ experimental data, and a VGG-19 pre-trained neural network, thereby establishing the significant potential for real-time quality monitoring in manufacturing processes. The findings from this present study set the tone for creating a digital process twin (DPT) framework capable of obtaining more aggressive yet reliable manufacturing parameters and monitoring techniques for processing turbine alloys and improving industry manufacturing performance and energy efficiency

Special Issue of the Manufacturing Engineering Society (MES)

This book derives from the Special Issue of the Manufacturing Engineering Society (MES) that was launched as a Special Issue of the journal Materials. The 48 contributions, published in this book, explore the evolution of traditional manufacturing models toward the new requirements of the Manufacturing Industry 4.0 and present cutting-edge advances in the field of Manufacturing Engineering focusing on additive manufacturing and 3D printing, advances and innovations in manufacturing processes, sustainable and green manufacturing, manufacturing systems (machines, equipment and tooling), metrology and quality in manufacturing, Industry 4.0, product lifecycle management (PLM) technologies, and production planning and risks

Development of a model for temperature in a grinding mill

Abstract Grinding mills are generally very inefficient, difficult to control and costly, in terms of both power and steel consumption. Improved understanding of temperature behaviour in milling circuits can be used in the model-based control of milling circuits. The loss of energy to the environment from the grinding mill is significant hence the need for adequate modeling. The main objectives of this work are to quantify the various rates of energy loss from the grinding mill so that a reliable model for temperature behaviour in a mill could be developed. Firstly models of temperature behaviour in a grinding mill are developed followed by the development of a model for the overall heat transfer coefficient for the grinding mill as a function of the load volume, mill speed and the design of the liners and mill shell using the energy balances in order to model energy loss from the mill. The energy loss via convection through the mill shell is accounted for by quantifying the overall heat transfer coefficient of the shell. Batch tests with balls only were conducted. The practical aspect of the work involved the measurement of the temperatures of the mill load, air above the load, the liners, mill shell and the environmental temperature. Other measurements were: mill power and sound energy from the mill. Energy balances are performed around the entire mill. A model that can predict the overall heat transfer coefficient over a broad range of operating conditions was obtained. It was found that the overall heat transfer coefficient for the grinding mill is a function of the individual heat transfer coefficients inside the mill and outside the mill shell as well as the design of the liners and shell. It was also found that inside heat transfer coefficients are affected by the load volume and mill speed. The external heat transfer coefficient is affected by the speed of the mill. The values for the overall heat transfer coefficient obtained in this work ranged from 14.4 – 21W/m2K. iv List of Publications The author has published the following papers based on the contents of this dissertation as follows: Published conference abstract Kapakyulu, E., and Moys, M.H., 2005. Modelling of energy loss to the environment from the grinding mill, Proceedings of the Mineral Processing 2005’ Conference, SAIMM, Cape Town, South Africa, 4-5 Aug. pp 65-66 - SP03 Research Papers: Accepted for publication and currently in press in Minerals Engineering: Kapakyulu, E., and Moys, M.H., 2006. Modelling of energy loss to the environment from a grinding mill, Part I: Motivation, Literature Survey and Pilot Plant Measurements, (Currently in press in Minerals Engineering) Kapakyulu, E., and Moys, M.H., 2006. Modelling of energy loss to the environment from a grinding mill, Part II: Modeling the overall heat transfer coefficient, (Currently in press in Minerals Engineering

Process analytical technology tools for process control of roller compaction in solid pharmaceuticals manufacturing

This article presents an overview of using process analytical technology in monitoring the roller compaction process. In the past two decades, near-infrared spectroscopy, near-infrared spectroscopy coupled with chemical imaging, microwave resonance technology, thermal effusivity and various particle imaging techniques have been used for developing at-, off-, on- and in-line models for predicting critical quality attributes of ribbons and subsequent granules and tablets. The common goal of all these methods is improved process understanding and process control, and thus improved production of high-quality products. This article reviews the work of several researchers in this field, comparing and critically evaluating their achievements

Developing a Lab-Scale Fluidized Bed Dryer System to Enhance Rough Rice Drying Process

For more than half of the world\u27s population, rice (Oryza sativa L.) is a staple meal. However, rice growers encounter difficulties supplying this demand, particularly in developing nations, where rice is susceptible to spoilage if the moisture content is not lowered to a safe level soon after harvest. As a result, traditional drying methods, such as sun drying and natural air drying, are commonly used by rice growers, particularly in underdeveloped nations. However, these procedures are time-consuming and can lead to rice spoilage. On the other hand, fluidized bed drying is a well-established technology that might give rice growers a rapid, practical, economical, and portable drying procedure. According to past research, the primary benefit of fluidized bed drying is the increased drying rate. On the other hand, other research has expressed concerns about inferior rice quality, which is considered a significant weakness in fluidized bed drying. In the United States of America, the farmers and processors lack consensus and thus there is a mistrust to utilize fluidized bed drying for rice. As a result of the lack of agreement, an extensive study to understand the fluidized bed drying of rice is needed. In the Mid-South region of the United States, high humidity ambient air is typical, resulting in stoppage of the in-bin rice drying process to avoid rewetting of rice. Ambient air dehumidification may be able to solve this problem and allow for a continual drying process. However, no study utilized desiccant for ambient air dehumidification for drying rice; through this study, an attempt was made to bridge the research gap and determine the benefits and practicalities of ambient air dehumidification to achieve continuous rice drying. A lab-scale mobile batch fluidized bed dryer was constructed and used in this study. Several tests were done to improve the system that included designs, additions, and replacements of parts. In a fluidized bed and fixed bed drying system, the effects of ambient air dehumidification, air temperature, and drying duration on rough rice quality were investigated. Energy and exergy analyses were done to determine the thermal efficiency of the drying system. Mathematical modeling was done to optimize the drying of rough rice. Overall, it was found that fluidized bed drying technology can be utilized for drying rough rice without compromising the quality compared to the fixed bed drying. The air temperature used was between 40 to 50°C, and rice was dried for no more than 60 min. In addition, the ambient air dehumidification reduced the relative humidity of drying air and did not affect rice quality but increased the rice moisture removal, ultimately increasing the drying rate. The study recommends using air temperatures below 50°C and a drying duration of less than 60 min to achieve effective rough rice drying with fluidized bed drying technique. In addition, ambient air dehumidification can be employed for reducing ambient air relative humidity by few points. However, more research must be done at the farm and industrial scale to check the accuracy of these findings at a large scale

Trochoidal Milling of AlSiCp with CVD Diamond Coated End Mills

Metal matrix composites have seen a rise in demand within the last decade. Aluminum alloy reinforced with silicon carbide particles is a type of particle metal matrix composite that has seen applications in the aerospace, ground transportation, and electronics industry. However, the abrasive SiC particles have made this material difficult to machine through conventional machining strategies. This research will focus on using computer aided manufacturing with trochoidal tool paths to maximize machining productivity and extend the tool life of CVD diamond coated end mills. The focus of this research will be on AlSiCp with a high volume fraction of reinforcement (30%) to expand the potential applications of this pMMC. The cutting experiments are divided into three parts: cutting test, confirmation test, and endurance test. Taguchi method will be used to perform an analysis of variance and signal-to-noise ratio to optimize a combination of material removal rate, average cutting forces, and surface roughness. The optimal cutting conditions were found to be 254 mm/min, 30°, and 9500 r/min for MRR+AvgFxy+Ra, 1524 mm/min, 30°, and 9500 r/min for MRR+AvgFxy, and 1524 mm/min, 90°, and 9500 r/min. The cutting conditions for MRR+AvgFx+Ra was not considered for the endurance tests as the machining productivity was too low to be considered a feasible option in the industry. It was concluded that trochoidal milling under wet cutting conditions produced nearly half the tool wear as previous research with conventional milling strategies. However, the longer the CVD diamond coated end mills were engaged in the AlSiCp workpiece, the more dominant the abrasive wear mechanisms appear and cause tool damage. It was concluded that square end mills may not be suitable for machining AlSiCp and that future research should focus on varying the tool geometry or utilizing ball end mills

The present state of surface conditioning in cutting and grinding

All manufacturing processes have an impact on the surface layer state of a component, which in turn significantly determines the properties of parts in service. Although these effects should certainly be exploited, knowledge on the conditioning of the surfaces during the final cutting and abrasive process of metal components is still only extremely limited today. The key challenges in regard comprise the process-oriented acquisition of suitable measurement signals and their use in robust process control with regard to the surface layer conditions. By mastering these challenges, the present demands for sustainability in production on the one hand and the material requirements in terms of lightweight construction strength on the other hand can be successfully met. In this review article completely new surface conditioning approaches are presented, which originate from the Priority Program 2086 of the Deutsche Forschungsgemeinschaft (DFG)