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: In this paper, the effect of process parameters on surface roughness and kerf width of aluminum and mild steel are investigated and single objective taguchi method is used for process parameter optimization.
35 citations
Patent•
07 Sep 2005
TL;DR: In this article, the actual value transmitter is made of electrical actual value transmitting transducers that are subordinated to sensors, and the transmitter delivers an adjusting signal according to an assignable control algorithm for a subordinate control member of the control system after comparison of an actual value with the nominal value of an observed offset.
Abstract: The biogas plant-control method includes metering biomass substrate (9) by a substrate metering device (8) and regulating a process parameter as control variable of a fermentation process by a control mechanism with an automatic controller (18). The biogas plant has a fermentation tank (2). A parameter nominal value is assigned to the controller and to which a respectively assigned actual value transmitter (14, 15, 16, 17) is attached. The biogas plant-control method includes metering biomass substrate (9) by a substrate metering device (8) and regulating a process parameter as control variable of a fermentation process by a control mechanism with an automatic controller (18). The biogas plant has a fermentation tank (2). A parameter nominal value is assigned to the controller and to which a respectively assigned actual value transmitter (14, 15, 16, 17) is attached. The transmitter delivers an adjusting signal according to an assignable control algorithm for a subordinate control member of the control system after comparison of the actual value with the nominal value of an observed offset. The offset relative to the process parameter takes place through a control metering of an assigned control biomass, which influences the respective process parameter during the fermentation process. The assigned control biomasses are held back in assigned control storage vessels in liquid and/or granulate-like form and are conveyed by pumps and/or presses and/or worm drive for the control metering. The control biomasses are metered by a control metering device. The influence of assigned control biomasses on the process parameters is stored as program and/or characteristic diagram in a computer. The computer has the function of the automatic controller or assigns the nominal values for a separate automatic controller to a subordinate control metering device. The process parameters obtained by the parameter actual value transmitter are components that are detectable using instrumentation techniques and/or are characteristics of the fermented substrate and/or the produced biogas. The parameter actual value transmitter is made of electrical actual value transmitting transducers that are subordinated to sensors. The control storage vessels are arranged in a battery with a common transport/conveyor-line that is subordinate to the control members that are arranged respectively to the fermentation tank. The control metering takes place directly into the fermentation tank and/or into the substrate metering device as addition to the substrate biomass. A cascade control is intended, in which the regulation of control biomass is assigned as a guidance regulation that is overlaid upon a faster subsequent regulation. A proportional-integral-derivative algorithm is used as control algorithm.
34 citations
TL;DR: The proposed method finds an optimal setting from historical data without constructing an explicit quality function by sequentially partitioning the reduced process variable space using a rule induction method.
Abstract: In process optimization, the setting of the process variables is usually determined by estimating a function that relates the quality to the process variables and then optimizing this estimated function. However, it is difficult to build an accurate function from process data in industrial settings because the process variables are correlated, outliers are included in the data, and the form of the functional relation between the quality and process variables may be unknown. A solution derived from an inaccurate function is normally far from being optimal. To overcome this problem, we use a data mining approach. First, a partial least squares model is used to reduce the dimensionality of the process and quality variables. Then the process settings that yield the best output are identified by sequentially partitioning the reduced process variable space using a rule induction method. The proposed method finds an optimal setting from historical data without constructing an explicit quality function. The propo...
34 citations
TL;DR: In this paper, a suitable and stable process parameter set for a reference grain fraction (10−63μm) have been developed, and variations of grain size distribution will be taken into account, so that a high material density as well as high surface quality can be achieved.
34 citations
TL;DR: It was apparent that lactose/MCC-based formulations correlated better than lactose- based formulations, indicating the possible process robustness of the first filler combination to accommodate API and excipient variability and to handle APIs with different characteristics.
34 citations