Search Results for feedback process control

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.

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.

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.

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 provides an overview of the components of a resistance welding machine. It focuses on the single-phase control system and medium-frequency direct current system of resistance welding. The article also includes information on their feedback systems, rectification systems, and power sources.

Part quality in additive manufacturing (AM) is highly dependent on process control, but there is a lack of adequate AM control methods and standards. Laser powder-bed fusion (L-PBF) is one of the most-used metal AM techniques. This article focuses on the following laser control parameters: laser focus, laser power, laser position, and laser power-position synchronization. It then provides a discussion on laser scan strategies. The article also provides an overview of the AM control framework, the two major sections of which are software and hardware.

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.

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 focuses on laboratory atomic force microscopes (AFMs) used in ambient air and liquid environments. It begins with a discussion on the origin of AFM and development trends occurring in AFM. This is followed by a section on the general principles of AFM and a comprehensive list of AFM scanning modes. There is a brief description of how each mode works and what types of applications can be made with each mode. Some of the processes involved in preparation of samples (bulk materials and those placed on a substrate) scanned in an AFM are then presented. The article provides information on the factors applicable to the accuracy and precision of AFM measurements. It ends by discussing the applications for AFMs in the fields of science, technology, and engineering.

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.

This article outlines the requirements and methods associated with the inspection of brazements. It emphasizes the incorporation of these requirements into the overall quality system. The article reviews the acceptance limits, design limitations, and nondestructive and destructive inspection techniques involved in the brazement inspection. Selected case studies are also provided for further reference.

The objective of dimensional management is to create a design and process that absorbs as much variation as possible without affecting the function of the product. This article describes the steps followed by the dimensional management process. These include defining product dimensional requirements, determining process and product requirements, ensuring accurate documentation, developing a measurement plan that validates product requirements, establishing manufacturing capabilities versus design intent, and establishing production-to-design feedback loop. The article discusses the simulation model in terms of a functional feature product model, component part variation, assembly method variation, measurement schemes, and assembly sequences.

Laser soldering uses a well-focused, highly controlled beam to deliver energy to a desired location for a precisely measured length of time. This article focuses on two types of laser soldering operations, namely, blind laser soldering and intelligent laser soldering. It discusses the function of the blind laser soldering and provides a brief description on key attributes of the blind laser soldering, including repeatability, speed, quality, safety, and flexibility. The article explores the function of the intelligent laser soldering and concludes with a section on key attributes of the intelligent laser soldering. The key attributes of the intelligent laser soldering include repeatability, speed, quality, safety, cost, and flexibility.

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.