Process variable

About: Process variable is a research topic. Over the lifetime, 3983 publications have been published within this topic receiving 43130 citations. The topic is also known as: process parameter.

Empirical Dynamic Modeling of Friction Stir Welding Processes

Abstract: Current friction stir welding (FSW) process modeling research is mainly concerned with the detailed analysis of local effects such as material flow, heat generation, etc. These detailed thermomechanical models are typically solved using finite element or finite difference schemes and require substantial computational effort to determine temperature, forces, etc., at a single point in time, or for a very short time range. Dynamic models describing the total forces acting on the tool throughout the entire welding process are required for the design of feedback control strategies and improved process planning and analysis. In this paper, empirical models relating the process parameters (i.e., plunge depth, travel speed, and rotation speed) to the process variables (i.e., axial, path, and normal forces) are developed to understand their dynamic relationships. First, the steady-state relationships between the process parameters and the process variables are constructed, and the relative importance of each process parameter on each process variable is determined. Next, the dynamic characteristics of the process variables are determined using recursive least-squares. The results indicate the steady-state relationship between the process parameters and the process variables is well characterized by a nonlinear power relationship, and the dynamic responses are well characterized by low-order linear equations. Experiments are conducted that validate the developed FSW dynamic models.

Process-Machine Interaction (PMI) Modeling and Monitoring of Chemical Mechanical Planarization (CMP) Process Using Wireless Vibration Sensors

Abstract: We present a deterministic process-machine interaction (PMI) model that can associate different complex time-frequency patterns, including nonlinear dynamic behaviors that manifest in vibration signals measured during a chemical mechanical planarization (CMP) process for polishing blanket copper wafer surfaces to near-optical finish (Ra ~ 5 nm) to specific process mechanisms. The model captures the effects of the nonuniform structural properties of the polishing pad, pad asperities, and machine kinematics on CMP dynamics using a deterministic 2 ° of freedom nonlinear differential equation. The model was validated using a Buehler (Automet 250) bench top CMP machine instrumented with a wireless (XBee IEEE 802.15.4 RF module) multi-sensor unit that includes a MEMS 3-axis accelerometer (Analog Devices ADXL 335). Extensive experiments suggest that the deterministic PMI model can capture such significant signal patterns as aperiodicity, broadband frequency spectra, and other prominent manifestations of process nonlinearity. Remarkably, the deterministic PMI model was able to explain not just the physical sources of various time-frequency patterns observed in the measured vibration signals, but also, their variations with process conditions. The features extracted from experimental vibration data, such as power spectral density over the 115-120 Hz band, and nonlinear recurrence measures were statistically significant estimators (R2 ~ 75%) of process parameter settings. The model together with sparse experimental data was able to estimate process drifts resulting from pad wear with high fidelity (R2 ~ 85%). The signal features identified using the PMI model can lead to effective real-time in-situ monitoring of wear and anomalies in the CMP process.

Generation of a set point for process control

Abstract: In a process in which a first process variable is manipulated so as to maintain a second process variable substantially equal to a desired value for the second process variable, a set point for the first process variable is generated based on the difference between the actual value of the second process variable and the set point for the second process variable. The magnitude of the set point is determined by the probability that the second process variable may reach an undesirable value and thus control using the set point takes into the consideration the fact that large control actions may be required under some circumstances and minimal control actions may be required under other circumstances in a process.

FDM Process Parameter Optimization by Taguchi Technique for Augmenting the Mechanical Properties of Nylon–Aramid Composite Used as Filament Material

Abstract: Fused deposition modelling (FDM) is one such technique of additive manufacturing (AM) that deposits the extruded thermoplastic material layer by layer to build the desired part. The study is focused on the introduction of new thermoplastic material that widens the application of FDM process and also to use the part for functional purpose rather than just the prototype. Nylon is used as the feed filament material for FDM due to its higher mechanical properties and wear resistant characteristics that are often used as sliding bearing. The properties of nylon are further enhanced by adding the aramid short fibres. In this investigation, the process parameter optimization of FDM process is performed by using Gray Taguchi technique for the quality and mechanical characteristics enhancement. Layer thickness, print temperature, raster angle, infill part density and infill pattern style were considered as the influencing factors for optimization. Mechanical properties including tensile strength, flexural strength, impact strength and compression strength (responses) were studied for the designed experiments which were conducted according to ASTM standards. Analysis of variance was performed using Minitab 18 software to understand the signal-to-noise ratio for the respective objective. The overall combined objective is framed by providing equal importance to all the four responses. From the analysis, the following factors were identified as the optimum settings, layer thickness of 0.4 mm, print temperature of 300 °C, infill part density of 90%, raster angle of 90° and infill pattern style of rectilinear. The results from the test sample printed at the determined optimum setting has exhibited tensile strength of 51.455 MPa, flexural strength as 98.164 MPa impact strength of 0.637 MJ/sq m, compressive strength as 19.42 MPa. The test result of the parts printed from pure nylon as per the prescribed standard setting exhibited tensile strength of 48 MPa, flexural strength as 80.5 MPa, impact strength as 0.51 MJ/sq m and compression strength as 18.12 MPa. A significant increase by 7.2% in tensile strength, 22.7% in flexural strength, 27.4% in impact strength and 7.5% in compressive strength were noticed. From the investigation, it was possible to conclude that even short fibre composites can also be used as FDM raw materials and valid predictions can be made using regression equations with very less error and is justified by experimental trails.

Consumer product winding control and adjustment

Abstract: Apparatus (200) and method for controlling the winding of a sheet of material such as paper and film finished consumer products into a log using an adjustable reference profile. The apparatus (200) and method may provide improved process control, product quality, manufacturing production rate and/or process repeatability. The apparatus (200) and method provide more consistent finished log properties by measuring at least one process parameter during the manufacturing process. The process parameter is then correlated with the desired finished product characteristics and an appropriate correction is made to the reference profile.