Search Results for online monitoring

Additive manufacturing (AM) is a revolutionary technology that fabricates parts layerwise and provides many advantages. This article discusses polymer AM processes such as material extrusion, vat photopolymerization (VPP), powder-bed fusion (PBF), binder jetting (BJ), material jetting (MJ), and sheet lamination (SL). It presents the benefits of online monitoring and process control for polymer AM. It also introduces the respective monitoring devices used, including the models and algorithms designed for polymer AM online monitoring and control.

This article provides a discussion on general nondestructive evaluation (NDE) science and considerations for specific technique selection. It explains the basic concept of flaw detection and evaluation and probability of detection. The article provides an overview of NDE methods with their applications, limitations, and advantages. It includes details on NDE codes, calibration standards, inspection frequency, guidance on how to perform inspections, applicability, and mandatory and nonmandatory practice. The article also provides tips on where to focus inspections in order to align with the likely areas of damage or degradation and a number of other aspects of inspection.

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.

Electromagnetic signals at microwave and millimeter-wave frequencies are well suited for inspecting dielectric materials and composite structures in many critical applications. This article presents a partial list of reported nondestructive testing (NDT) application areas for microwaves. It discusses the advantages and limitations of inspection with microwaves. The article discusses the physical principles, including reflection and refraction, absorption and dispersion, scattering, and standing waves. It provides a discussion on terahertz (THz) imaging for nondestructive evaluation (NDE). The article concludes with information on ground-penetration radar (GPR) that uses electromagnetic radiation and detects the reflected signals from subsurface structures.

This article explores the use of the electrochemical and nonelectrochemical techniques for measuring the corrosion behavior of buried metals and the types of probes used. The electrical resistance technique is the main nonelectrochemical technique used for measuring corrosion rate. Electrochemical techniques discussed include linear polarization resistance, electrochemical noise, harmonic distortion analysis, electrochemical impedance spectroscopy, and hydrogen permeation. The principles of operation for the corrosion measuring techniques are described along with examples of their use in soils.

This article discusses the installation of the most commonly used force-monitoring devices, namely, load cells and piezoelectric force sensors. It describes the purpose and operation of commonly used displacement sensors, such as linear variable differential transformers, proximity sensors, photoelectric sensors, and ultrasonic sensors. The article provides information on the sensors used for detecting tool breakages and flaws in parts, the measurement of material flow during sheet metal forming, and lubrication. It also describes the operating stages of machine vision systems used for automated quality-control purposes. The theory of eddy-current-based material properties evaluation is also discussed.

The measurement techniques for die wear can be classified into the following two categories: direct measurements, which are done using lab techniques; and indirect nondestructive measurements, which are done by plant monitoring. This article describes the details of the plant monitoring techniques, along with comprehensive discussions on the measured wear data based on roughness and hardness of die surfaces. It presents a comparison between the predicted and measured die wear rates.

The formation of defects within additive-manufactured (AM) components is a major concern for critical structural and cyclic load applications. Thus, understanding the mechanisms of defect formation in fusion-based processes is important for prescribing the appropriate process parameters specific to the alloy system and selected processing technique. This article discusses the formation of defects within metal additive manufacturing, namely fusion-based processes and solid-state/sintering processes. Defects observed in fusion-based processes include lack of fusion, keyhole collapse, gas porosity, solidification cracking, solid-state cracking, and surface-connected porosity. The types of defects in solid-state/sintering processes are sintering porosity and improper binder burnout. The article also discusses defect-mitigation strategies, such as postprocess machining, surface treatment, and postprocessing HIP to eliminate defects detrimental to properties from the as-built condition. The use of noncontact thermal, optical, and ultrasound techniques for inspecting AM components are also considered. The final section summarizes the knowledge gap in our understanding of the defects observed within AM components.

This article reviews weld quality monitoring considerations for two automotive materials, steel and aluminum, with a focus on photosensor technology. It provides an overview of the process description, process parameters, and weld characteristics of laser welding. The article discusses real-time or in-process monitoring, which is done with optical, acoustic, and/or charged-particle sensors. It highlights the advantages, applications, and selection criteria of weld monitoring system and concludes with examples of laser weld monitoring in the production of tailor-welded blanks.

Nondestructive testing (NDT), also known as nondestructive evaluation (NDE), includes various techniques to characterize materials without damage. This article focuses on the typical NDE techniques that may be considered when conducting a failure investigation. The article begins with discussion about the concept of the probability of detection (POD), on which the statistical reliability of crack detection is based. The coverage includes the various methods of surface inspection, including visual-examination tools, scanning technology in dimensional metrology, and the common methods of detecting surface discontinuities by magnetic-particle inspection, liquid penetrant inspection, and eddy-current testing. The major NDE methods for internal (volumetric) inspection in failure analysis also are described.

The material data for forging can be divided into two categories, namely, mechanical properties and thermophysical properties. This article describes the flow characteristics of key engineering materials, such as steels, aluminum alloys, copper alloys, titanium alloys, and nickel-base superalloys. It discusses the thermophysical properties for designing or optimizing a metalworking process: specific heat, coefficient of thermal expansion, thermal conductivity/diffusivity, and density.

This article presents the primary considerations and mechanisms for corrosion and explains how they are involved in the selection of materials for process equipment in refineries and petrochemical plants. It discusses the material selection criteria for a number of ferrous and nonferrous alloys used in petroleum refining and petrochemical applications. The article reviews the mechanical properties, fabricability, and corrosion resistance of refinery steels. It describes low- and high-temperature corrosion, hydrogen embrittlement, and cracking such as stress-corrosion, sulfide stress, and stress-oriented hydrogen-induced cracking. The article considers hydrogen attack, corrosion fatigue, and liquid metal embrittlement and the methods of combating them. It explains the causes of velocity-accelerated corrosion and erosion-corrosion. The article summarizes some corrective measures that can be implemented to control corrosion. The applicable standards for materials used in corrosive service conditions in upstream and downstream petroleum service are presented in a tabular form.

Additive manufacturing (AM) is the process of joining materials to make parts from three-dimensional (3D) model data, usually layer upon layer, as opposed to subtractive manufacturing and formative manufacturing methodologies. This article discusses various defects in AM components, such as porosity, inclusions, cracking, and residual stress, that can be avoided by using vendor recommended process parameters and approved materials. It describes the development of process-structure-property-performance modeling. The article explains the practical considerations in nondestructive evaluation for additively manufactured metallic parts. It also examines nondestructive testing (NDT) inspection and characterization methods for each of the manufacturing stages in their natural order. The article provides information on various inspection techniques for completed AM manufactured parts. The various electromagnetic and eddy current techniques that can be used to detect changes to nearsurface geometric anomalies or other defects are also discussed. These include ultrasonic techniques, radiographic techniques, and neutron imaging.

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.