Search Results for closed loop control

The primary goal of quality control in electron beam (EB) welding is to consistently produce defect-free and structurally sound welds. This article discusses the common procedures for controlling the EB welding process, the control of the essential machine parameters, and the introduction of closed-loop controls and diagnostic feedback systems in the EB welding systems. It reviews the beam diagnostic tools that interrogate the beam to produce a reconstruction of the power density distribution and provide additional information on the size and shape of the EB. Knowledge of these beam parameters can be used to improve process understanding and control. The article also describes the application areas of beam diagnostics: machine characterization, weld parameter transfer, and weld quality control.

This article describes the phenomena of crack initiation and early growth. It examines specimen design and preparation as well as the apparatus used in crack initiation testing. The article provides descriptions of the various commercially available fatigue testing machines: axial fatigue testing machines and bending fatigue machines. Load cells, grips and alignment devices, extensometry and strain measuring devices, environmental chambers, graphic recorders, furnaces, and heating systems of ancillary equipment are discussed. The article presents technologies available to accomplish closed loop control of materials testing systems in performing standard materials tests and for the development of custom testing applications. It explores the advanced software tools for materials testing. The article includes a description of baseline isothermal fatigue testing, creep-fatigue interaction, and thermomechanical fatigue. The effects of various variables on fatigue resistance and guidelines for fatigue testing are also presented.

This article provides an overview of the methods used to control aspects of the arc welding process and research associated with the development of closed-loop feedback control of the process. Successful implementation of a closed-loop feedback control system requires sensing, modeling, and control. The article describes the commonly applied sensing techniques for arc welding control: arc sensing and nonimaging and imaging optics. It reviews the physics-based, empirically-derived, and neural network models for arc welding control. The article also discusses the research and development activities that attempt to extend the commercial, welding process controllers, namely, adaptive control, intelligent control, multivariable control, and distributed, hierarchical control.

This article discusses various control processes carried out in powder feeding, thermal spraying, and gas flow of the thermal spray process to standardize the coating quality. Quality of the entire powder feeding process can be achieved by controlling the processing of feeding equipment as well as the characteristics of the powder being fed. Gas flow control can be achieved by using rotameters, critical orifices, and thermal mass flowmeters, whose ability to provide useful information is defined by their resolution, accuracy, linearity, and repeatability. The commercial thermal spray controls discussed here include the open-loop input-based, open-loop output-based, closed-loop input-based, and closed-loop output-based or adaptive controls. The article discusses the common causes and practical solutions for arc starting problems. It also outlines certain important developments in measuring individual and collective particle velocities, temperature, and trajectories as well as other plume characteristics for the plasma spray process.

The use of an effective control design, along with high-performance hardware and software for controller implementation, allows the use of feedback process control for manufacturing processes to improve part quality and consistency. This article provides an overview of control system design and its application to various manufacturing processes. It presents various examples of control system applications to show that appropriate control strategies increase the robustness of the processes by eliminating process sensitivity to system variations and external disturbances.

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.

Process optimization is the discipline of adjusting a process to optimize a specified set of parameters without violating engineering constraints. This article reviews data-driven optimization methods based on genetic algorithms and stochastic models and demonstrates their use in powder-bed fusion and directed energy deposition processes. In the latter case, closed-loop feedback is used to control melt pool temperature and cooling rate in order to achieve desired microstructure.

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 reviews the emerging manufacturing technology that is alternatively called additive manufacturing (AM), direct digital manufacturing, free-form fabrication, three-dimensional (3-D) printing, and so on. It provides a broad contextual overview of metallic AM. The article focuses on the mechanical properties of AM-processed Ti-6Al-4V, IN-625, and IN-718. The development of closed-loop, real-time, sensing, and control systems is essential to the qualification and advancement of AM. This involves the development of coupled process-microstructural models, sensor technology, and control methods and algorithms. AM has the potential to revolutionize the global parts manufacturing and logistics landscape. It enables distributed manufacturing and the productions of parts on demand while offering the potential to reduce cost, energy consumption, and carbon footprint. The article explores the materials science, processes, and business considerations associated with achieving these performance gains. It concludes that a paradigm shift is required to fully exploit AM potential.

The basic elements of control design are safety, process control, process verification, machine control, productivity, repeatability, and ease of setup. Effective systems of quality control/quality assurance are essential for heat treating practices. This article provides information on process control modes, as well as on process signatures of some items that require control, monitoring, verifying, and logging methods. It provides information on programmable logic controllers that have become efficient in machine control and monitoring. The article describes possible noise issues, National Electric Code clearance requirements, monitoring requirements, and machine accuracy that need to be considered when designing induction equipment.

Physics-based feedforward control is discussed in this article for two important laser-based metal additive manufacturing (AM) processes: directed-energy deposition and laser powder-bed fusion. For each type of process, control-oriented, lumped-parameter models that characterize melt pool dynamics as a function of process parameters are discussed first. Then, the derivation of model-based controllers is illustrated, followed by experimental evaluations of the model-based controller implemented as a feedforward control on a commercial AM system.

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.

Cooling towers are designed to remove heat from water in an induction system and dissipate it into the atmosphere. This article provides information on closed-loop recirculating water systems of an induction system to cool the power supply. It focuses on various types of cooling towers, namely, air-cooled heat exchangers, air-cooled heat exchangers with trim cooler, closed-circuit evaporative cooling towers, and open evaporative cooling towers. The article discusses the importance of their placement or positioning to reduce the chances of air recirculation, and concludes with a discussion on refrigerant chillers.

High-pressure die casting is a fast method for the net shape manufacturing of parts from nonferrous alloys. This article reviews the automation technologies for the different stages or steps of the process. These steps include liquid metal pouring, injection, solidification, die open, part extraction, die lubrication, insert loading, and die close. Some manual aspects of the operations, together with automation options, are discussed. The article describes finishing steps, such as finish trimming, detailed deflashing, shot blast cleaning, and quality checks. Automation of the postcasting process is also discussed.