Search Results for machining data

This article is a comprehensive collection of machining data, presented in tables, covering most of the commonly used machining operations including turning, face milling, end milling (peripheral), drilling, reaming, and tapping of several materials. It provides starting recommendations for the range of speeds and feeds for various machining operations, parameters for the selection of tool geometry, and guidelines on the selection and identification of cutting fluids.

This article presents the analytics challenges in additive manufacturing. It discusses the types and applications of data analytics. Data analytics can be classified into four types: descriptive, diagnostic, predictive, and prescriptive. The diverse applications of data analytics and machine learning include design, process-structure-properties (PSP) relationships, and process monitoring and quality control. The article also presents tools used for data analytics.

An understanding of the influence of microstructure on machinability can provide an insight into more efficient machining and the correct solution to problems. Providing numerous microstructures to depict examples, this article describes the relationship between the microstructure and machinability of cast irons, steels, and aluminum alloys. It presents data on hardness values and the effect of the matrix microstructure of cast iron on tool life. It also explains how a higher inclusion count improves the machinability of steels and why aluminum alloys can be machined at very high speeds.

In situ process monitoring includes any technologies that monitor or inspect during an additive manufacturing (AM) process. This article presents the types, process considerations, and challenges of in situ monitoring technologies that can be implemented during an AM process. The types include system health monitoring, melt pool monitoring, and layer monitoring. The article discusses data analysis, and provides an overview of the integration of sensors into AM machines.

The machinability of carbon and alloy steels is affected by many factors, such as the composition, microstructure, and strength level of the steel; the feeds, speeds, and depth of cut; and the choice of cutting fluid and cutting tool material. This article describes the influence of the various attributes of carbon and alloy steels on machining characteristics. It lists the relative machinability ratings for some plain carbon steels, standard resulfurized steels, and several alloy steels. The addition of lead to carbon steels is one of the means of increasing the machinability of the steel and improving the surface finish of machined parts. Low carbon content of carburizing steels may be beneficial to tool life and production rate. The sulfur content of through-hardening alloy steels can significantly affect machining behavior. Cold drawing generally improves the machinability of steels containing less than about 0.2% carbon.

Additive manufacturing (AM) creates parts layer by layer directly from three-dimensional computer-aided design data. This article discusses systematic ways to address the challenges in AM data integration by exploring various AM-specific data-integration scenarios that can improve the current AM ecosystem. Representative AM data sources are also described. A reference framework that captures the heterogenous AM data sources and existing data-integration mechanisms are used. General data-integration practices—based on existing manufacturing data and lab information system integration experiences—are recommended to automate AM data flow, operations, and development. Lastly, the article discusses the seven steps in the big-data-integration workflow.

Specific machining processes that employ electrochemical machining technology include deburring and deep-hole drilling. This article describes the principle and applications of electrochemical deburring as well as the machine tools used in the process. The system, process capabilities, and applications of electrochemical deep-hole drilling are also discussed. The article also reviews the pulse electrochemical machining.

This article lists the system parameters of the friction welding process and describes the four categories of monitoring and control of the manufacturing process. It discusses the monitoring methods of a rotary friction welded sample, for determining in-process quality of ferrous alloys, and dissimilar metals using acoustic emission. The article reviews the feasibility of detecting the presence of ferrite during microstructural evolution of friction welding of three austenitic stainless steels: 310, 304, and 255. It also explains the in-process quality control of friction welding.

This article discusses the evolution of computer numerical control and direct numerical control for machine tools. It describes the fundamentals and advantages of numerical control (NC) systems. The article reviews the manual or computer assisted off-line programming methods for programming the tools with the aid of the automatically programmed tool language. It also explains point-to-point and continuous-path or contouring of NC systems and the adaptive systems used for NC.

This article surveys common additive manufacturing (AM) data-acquisition methods, covering preprocess materials characterization in the lab, machine calibration in the field, in-process monitoring during a build, and the postprocess part inspections and tests. The focus is to identify acquisition-related metadata for AM data sets to improve data usability and reusability. Also included in the article are exemplar metadata definitions for a data set acquired from light-scattering-based particle size analysis.

This article describes the basic functions that should be included when considering the relationship of computer-aided design (CAD)/computer-aided manufacturing (CAM) and machining. These include design, analysis, drafting, process planning, part programming, program verification, part machining, and inspection. The article provides information on hardware, data base, interfaces, and benefits of integrating machining with the CAD/CAM system of a manufacturing plant. It also provides an overview of direct, computer and, distributed numerical control, which are devoid of a number of problems inherent in conventional numerical control.

Modeling will help reduce machining problems and thereby enable more rapid introduction of high-performance materials and components. This article discusses the technical needs of aircraft engine and airframe structural components and modeling of heat-treat-induced residual stress by finite-element residual-stress analysis. It describes the two-dimensional (2-D) and three-dimensional (3-D) procedures involved in finite-element residual-stress analysis. The article deals with the 2-D and 3-D machining distortion validation on engine-disk-type components. It describes methods for obtaining machining-induced residual stresses, including detailed finite-element analysis of the cutting process, the simple fast-acting mechanistic model, and the semi-empirical linear stress model. The article concludes with information on the modeling benefits and implementation of modeling in a production environment.

This article distinguishes between a surface finish and a surface texture. It provides information on the surface integrity technology that describes and controls the many possible alterations produced in a surface layer during manufacture, including their effects on material properties and the performance of the surface in service. The types of surface alterations associated with metal removal practices are described. The article discusses the surface roughness, surface integrity, and produced in manufacturing processes, and mechanical property effects. Surface alterations associated with metal removal practices of traditional and nontraditional machining operations, as well as their effect on the static mechanical properties of materials, are reviewed. Finally, the article provides guidelines for material removal, postprocessing, and inspection.