Topic
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.
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TL;DR: Abrasive powder-mixed electrical discharge machining (APM-EDM), a hybrid manufacturing process involving the use of a dielectric fluid mixed with abrasive powder, combines the benefits of mechanical and thermal interactions.
Abstract: Abrasive powder-mixed electrical discharge machining (APM-EDM), a hybrid manufacturing process involving the use of a dielectric fluid mixed with abrasive powder, combines the benefits of mechanical and thermal interactions. The aim of this article is to use a new approach of performance evaluation, gray relational analysis (GRA), to evaluate the effectiveness of optimizing multiple performance characteristics of APM-EDM of 6061Al/Al2O3p/20p aluminum matrix composites (AMCs). The considered process parameter includes the seven control factors namely pulse current (A), pulse ON time (μs), duty cycle (%), gap voltage (V), time interval of tool lift (s), abrasive powder concentration (g/L), abrasive particle size (μm), and a noise factor, aspect ratio (shape of tool electrode). The combination of L18 (21 × 37) orthogonal array design of experiment with GRA enables to determine the optimal parameters for multiple responses. GRA is used to obtain a single performance index, gray relational grade through gray relational coefficient to optimize the APM-EDM process with lower tool wear rate, surface roughness, and higher material removal rate. In addition, analysis of variance (ANOVA) for the GRC is also utilized.
70 citations
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TL;DR: In this article, an attempt to select the optimum process parameters for friction stir welding of aluminium 2024 alloy based on multiple criteria decision-making approach is made, where the response parameters measured are ultimate tensile strength, impact toughness and hardness of welded joint that determines quality of joint.
69 citations
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TL;DR: In this article, a comparative study of response surface methodology (RSM) and artificial neural networks (ANN) for the modeling of yield and process parameters was carried out in Biodiesel production from algae oil at low temperature.
69 citations
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TL;DR: In this article, a response surface methodology (RSM)-based optimization design for process parameter optimization of abrasive water jet machining (AWJM) process on machining of green composites is presented.
Abstract: The objective of this paper is to develop a response surface methodology (RSM)-based optimization design for process parameter optimization of abrasive water jet machining (AWJM) process on machining of green composites. The experiments are performed based on the Box-Behnken design, and most optimal parameters are selected using multi-response optimization through desirability. The machining parameters are pressure within the pumping system (PwPS), stand-off distance (SoD), and nozzle speed (NS). The corresponding response parameters that have been identified are surface roughness (Ra) and process time (PT). Additionally, the significance of the developed optimization design has been identified using analysis of variance (ANOVA). Finally, the validity and adequacy of the developed model are done through confirmation tests. The numerical result shows that the optimum process parameters obtained are PwPS (150 MPa), SoD (3.5 mm), and NS (125 mm/min), and also the percentage error in prediction of response parameters is reasonable and comparable with the experimental results. The proposed design can be used as a systematic framework for parameter optimization in environmentally conscious manufacturing processes.
68 citations
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21 Jun 1993TL;DR: A flexible automation system for variable industrial processes (e.g. for processes on an oil or gas conveyer platform) includes programmable controllers that are linked via bus subsystems to process variables that are assigned in digital or analog form.
Abstract: A flexible automation system for variable industrial processes (e.g. for processes on an oil or gas conveyer platform) includes programmable controllers that are linked via bus subsystems to process variables that are assigned in digital or analog form. The bus subsystems have communication interfaces for retrieving process variables from the programmable controllers. A retrieval signal is assigned to each process variable in coded form.
68 citations