Improving the prediction of the roll separating force in a hot steel finishing mill

This paper focuses on the development of a hybrid phenomenological/inductive model to improve the current physical setup force model on a five stand industrial hot strip finishing mill. We approached the problem from two directions. In the first approach, the starting point was the output of the current setup force model. A feedforward multilayer perceptron (MLP) model was then used to estimate the true roll separating force using some other available variables as additional inputs to the model.

It was found that it is possible to significantly improve the estimation of a roll separating force from 5.3% error on average with the current setup model to 2.5% error on average with the hybrid model. The corresponding improvements for the first coils are from 7.5% with the current model to 3.8% with the hybrid model. This was achieved by inclusion, in addition to each stand's force from the current model, the contributions from setup forces from the other stands, as well as the contributions from a limited set of additional variables such as: a) aim width; b) setup thickness; c) setup temperature; and d) measured force from the previous coil.

In the second approach, we investigated the correlation between the large errors in the current model and input parameters of the model. The data set was split into two subsets, one representing the "normal" level of error between the current model and the measured force value, while the other set contained the coils with a "large" level of error. Additional set of data with changes in each coil's inputs from the previous coil's inputs was created to investigate the dependency on the previous coil.

The data sets were then analyzed using a C4.5 decision tree. The main findings were that the level of the speed vernier variable is highly correlated with the large errors in the current setup model. Specifically, a high positive speed vernier value often correlated to a large error. Secondly, it has been found that large changes to the model flow stress values between coils are correlated frequently with larger errors in the current setup force model.

Cold rolling mill thickness control using the cascade-correlation neural network

The improvements in thickness accuracy of a steel strip produced by a tandem cold-roIling mill are of substantial interest to the steel industry. In this paper, we designed a direct model-reference adaptive control (MRAC)  scheme that exploits the natural level of excitation existing in the closed-loop with a dynamically constructed cascade-correlation neural network (CCNN) as a controller for cold roIling mill thickness control. Simulation results show that the combination of a such a direct MRAC scheme and the dynamically constructed CCNN significantly improves the thickness accuracy in the presence of disturbances and noise in comparison with to the conventional PID controllers.

Misunderstanding John Stuart Mill on science: Paul Feyerabend`s bad influence

Feyerabend, 1975; Feyerabend, 1981 and Feyerabend, 1987 takes J. S. Mill’s On Liberty to support the proliferation of theories in science and to emphasize the fallibility of scientific knowledge. On Liberty, according to Feyerabend, contradicts and overthrows Mill’s major study of science, A System of Logic. Staley (1999) reads the 2 works of Mill as giving complementary accounts of science. The present author rejects these interpretations of Mill, arguing that A System of Logic and On Liberty are mutually compatible since On Liberty concerns the nature of non-scientific knowledge and the methods that Mill believes are appropriate to expanding and assessing that knowledge.

Mill specific prediction of worsted yarn performance

Different spinning mills use different raw materials, processing methodologies, and equipment, all of which influence the quality of the yarns produced. Because of many variables, there is a difficulty in developing a universal empirical/theoretical model. This work presents a multilayer perceptron algorithm (MLP) model for the purpose of building a mill specific worsted spinning performance prediction tool. Sixteen inputs are used to predict key yarn properties and spinning performance, including number of fibers in cross-section, unevenness (U%), thin places, neps, yarn tenacity, elongation at break, thick places, and spinning ends-down. Validation of the model on mill specific commercial data set shows that the general fit to the target values is good. Importantly, the performance of the MLP shows a certain degree of stability to different, random selections of independent test data. Subsequent comparison against the predicted outputs of Sirolan Yarnspec™ confirms the overall performance of the artificial neural network (ANN) method to be more accuratefor mill specific predictions.

Predicting the rolling force in hot steel rolling mill using an ensemble model

Accurate prediction of the roll separating force is critical to assuring the quality of the final product in steel manufacturing. This paper presents an ensemble model that addresses these concerns. A stacked generalisation approach to ensemble modeling is used with two sets of the ensemble model members, the first set being learnt from the current input-output data of the hot rolling finishing mill, while another uses the available information on the previous coil in addition to the current information. Both sets of ensemble members include linear regression, multilayer perceptron, and k-nearest neighbor algorithms. A competitive selection model (multilayer perceptron) is then used to select the output from one of the ensemble members to be the final output of the ensemble model. The ensemble model created by such a stacked generalization is able to achieve extremely high accuracy in predicting the roll separation force with the average relative accuracy being within 1% of the actual measured roll force.

Liberty in key works of John Locke and John Stuart Mill

The ideas of liberty presented in the important works of John Locke and John Stuart Mill, The Second Treatise of Government (1689) and On Liberty (1859), are often viewed as belonging to the same conceptual tradition, that of English liberalism. This thesis is an articulation of the diversity between the theories of liberty expressed by Locke and Mill in the Second Treatise and On liberty. \ am aiming to provide a corrective to the tendency to ignore or to gloss over very significant differences between the two men. The work concentrates on the philosophical aspects of each theory of liberty, arguing that they differ in four respects. These are; definitions of liberty; justifications of liberty; how much liberty and for whom they recommend it, and finally, who they believe threatens liberty and how this threat is to be curbed. It is the purpose of this thesis to show that in terms of these areas Locke and Mill are pursuing different ends. I conclude that Locke and Mill present strikingly different theories of liberty and cannot be thought of as belonging to the one conceptual tradition in terms of the definition, the justification, the prescription and the threat to liberty. Ultimately, I question the value of including Locke and Mill in the one conceptual tradition of liberty solely on the basis that they argue ‘freedom from.’

Determination of resin acids in pulp mill effluent and receiving waters by high performance liquid chromatography

Resin acids are reported to be of major toxicological importance in pulp mill effluents for Rainbow Trout. Their determination, using a high performance liquid chromatographic method, is described.

Modeling and control of flatness in cold rolling mill using fuzzy petri nets

Today, having a good flatness control in steel industry is essential to ensure an overall product quality, productivity and successful processing. Flatness error, given as difference between measured strip flatness and target curve, can be minimized by modifying roll gap with various control functions. In most practical systems, knowing the definition of the model in order to have an acceptable control is essential. In this paper, a fuzzy Petri net method for modeling and control of flatness in cold rolling mill is developed. The method combines the concepts of Petri net and fuzzy control theories. It focuses on the fuzzy decision making problems of the fuzzy rule tree structures. The method is able to detect and recover possible errors that can occur in the fuzzy rule of the knowledge-based system. The method is implemented and simulated. The results show that its error is less than that of a PI conventional controller.

Sex-related differences in the organismal and cellular stress response in juvenile salmon exposed to treated bleached kraft mill effluent

Exposure of fish to stressors can elicit biochemical and organismal changes at multiple levels of biological organization collectively known as stress responses. The organismal (plasma glucose and cortisol levels) and cellular (hepatic hsp70) stress responses in fish have been studied in several species, but little is known about sex-related differences in these responses. In this study, we exposed sexually immature juvenile chinook salmon (Oncorhynchus tshawytscha) to bleached kraft mill effluent (BKME: 0%, 1%, and 10% v/v) for 30 days and then measured components of their organismal and cellular stress responses. Males exposed to 1% BKME had higher levels of plasma glucose than females. Plasma cortisol levels were unaffected in females exposed to BKME, but males exposed to 10% BKME had significantly higher levels of plasma cortisol relative to non-exposed males. While exposure to BKME did not affect hsp70 levels in males, females exposed to 1% BKME had higher levels of hsp70 relative to non-exposed and 10% BKME groups. Within any given treatment, females had higher levels of hsp70 relative to males. This study demonstrates that sex-related differences exist in commonly used indicators of stress in fish, and points out the importance of considering the sex of the fish in stress research.