Neural modelling, control and optimisation of an industrial grinding process

This paper describes the development of neural model-based control strategies for the optimisation of an industrial aluminium substrate disk grinding process. The grindstone removal rate varies considerably over a stone life and is a highly nonlinear function of process variables. Using historical grindstone performance data, a NARX-based neural network model is developed. This model is then used to implement a direct inverse controller and an internal model controller based on the process settings and previous removal rates. Preliminary plant investigations show that thickness defects can be reduced by 50% or more, compared to other schemes employed

Neural modelling, control and optimisation of an industrial grinding process

This paper describes the development of neural model-based control strategies for the optimisation of an industrial aluminium substrate disk grinding process. The grindstone removal rate varies considerably over a stone life and is a highly nonlinear function of process variables. Using historical grindstone performance data, a NARX-based neural network model is developed. This model is then used to implement a direct inverse controller and an internal model controller based on the process settings and previous removal rates. Preliminary plant investigations show that thickness defects can be reduced by 50% or more, compared to other schemes employed

Neural modelling, control and optimisation of an industrial grinding process

This paper describes the development of neural model-based control strategies for the optimisation of an industrial aluminium substrate disk grinding process. The grindstone removal rate varies considerably over a stone life and is a highly nonlinear function of process variables. Using historical grindstone performance data, a NARX-based neural network model is developed. This model is then used to implement a direct inverse controller and an internal model controller based on the process settings and previous removal rates. Preliminary plant investigations show that thickness defects can be reduced by 50% or more, compared to other schemes employed

Neural modelling, control and optimisation of an industrial grinding process

This paper describes the development of neural model-based control strategies for the optimisation of an industrial aluminium substrate disk grinding process. The grindstone removal rate varies considerably over a stone life and is a highly nonlinear function of process variables. Using historical grindstone performance data, a NARX-based neural network model is developed. This model is then used to implement a direct inverse controller and an internal model controller based on the process settings and previous removal rates. Preliminary plant investigations show that thickness defects can be reduced by 50% or more, compared to other schemes employed

Serotonergic dysfunction may mediate the relationship between alcohol consumption and Alzheimer’s disease

The impact of Alzheimer’s disease (AD) and its related dementias is rapidly expanding, and its mitigation remains an urgent social and technical challenge. To date there are no effective treatments or interventions for AD, but recent studies suggest that alcohol consumption is correlated with the risk of developing dementia. In this review, we synthesize data from preclinical, clinical, and epidemiological models to evaluate the combined role of alcohol consumption and serotonergic dysfunction in AD, underscoring the need for further research on this topic. We first discuss the limitations inherent to current data-collection methods, and how neuropsychiatric symptoms common among AD, alcohol use disorder, and serotonergic dysfunction may mask their co-occurrence. We additionally describe how excess alcohol consumption may accelerate the development of AD via direct effects on serotonergic function, and we explore the roles of neuroinflammation and proteostasis in mediating the relationship between serotonin, alcohol consumption, and AD. Lastly, we argue for a shift in current research to disentangle the pathogenic effects of alcohol on early-affected brainstem structures in AD