We propose a method for dynamic batch mode active learning where the batch size and selection criteria are integrated into a single formulation.

a shortcut procedure as quick, easy-to use method for design and simulation of multicomponent batch distillation is used to predict the operating condition of recovering xylene from solvent in an existing batch distillation column in benzol refinery. the procedure can be used to investigate the effect of the operating parameters on the operation of column for three possible modes of batch disti...

The goal of metabolomics data pre-processing is to eliminate systematic variation, such that biologically-related metabolite signatures are detected by statistical pattern recognition. Although several methods have been developed to tackle the issue of batch-to-batch variation, each method has its advantages and disadvantages. In this study, we used a reference sample as a normalization standar...

This paper addresses a production and outbound distribution scheduling problem in which a set of jobs have to be process on a single machine for delivery to customers or to other machines for further processing. We assume that there is a sufficient number of vehicles and the delivery costs is independent of batch size but it is dependent on each trip. In this paper, we present an Artificial Imm...

The contribution of this paper presents a systematic, indicator and process heuristics based retrofit method for batch processes. The developed framework considers the identification of improvement opportunities in a generic batch plant by considering also the product market situation. The evaluation of retrofit actions is performed using dynamic batch models.

Dynamics are inherent characteristics of batch processes, and they may exist not only within a particular batch, but also from batch to batch. To model and monitor such two-dimensional (2D) batch dynamics, two-dimensional dynamic principal component analysis (2D-DPCA) has been developed. However, the original 2D-DPCA calculates the monitoring control limits based on the multivariate Gaussian di...

We formulate and evaluate the Automated Simulation Analysis Procedure (ASAP), an algorithm for steady-state simulation output analysis based on the method of nonoverlapping batch means (NOBM). ASAP delivers a confidence interval for an expected response that is centered on the sample mean of a portion of a simulation-generated time series and satisfies a user-specified absolute or relative prec...