Data Table of Influence of extended dwell time during pre- and main compression on the properties of ibuprofen.

This dataset is related to the manuscript 'Influence of extended dwell time during pre- and main compression on the properties of ibuprofen'. While the compaction rate in most tableting machines is only determined by the tableting speed, the high speed rotary tableting machine used in this research project (MODUL P, GEA Process Engineering, Halle, Belgium) can adjust and control the dwell time independently from the tableting speed, using an air compensator which allows displacement of the upper (pre-) compression roller. The effect of this machine design on process parameters and tablet properties was investigated using a formulation containing 80% ibuprofen. The granules were compressed into tablets at 250, 500 and 1000 tablets per minute via double compression (pre- and main compression) with or without extended dwell time. Process parameters and tablet properties were analyzed using Multivariate Data Analysis. Principal Component Analysis (PCA) was performed on the machine settings and logged data obtained from the tableting press and data acquisition system in order to provide an overview of the performed experiments and investigate the correlations between all process variables. A Partial Least Squares (PLS) regression model was developed to explore the correlations between the machine settings and logged data (X) and the tablet properties (Y). The Data Table contains all data used in the Multivariate Data Analysis (tab 'Data Table'), together with a description of the used keys (tab 'Meaning Data Table') and a schematic overview of the performed experiments (tab 'Meaning Exp')本数据集关联于学术手稿《预压与主压阶段延长保压时间对布洛芬性质的影响》。当前绝大多数压片机的压片速率仅由压片速度决定，而本研究项目所用的高速旋转式压片机（型号MODUL P，制造商为比利时哈勒的GEA Process Engineering公司），可通过空气补偿装置独立调节并控制保压时间——该装置可实现上（预压）压辊的位移。本研究采用含80%布洛芬的处方，探究了该机型设计对工艺参数与片剂性质的影响。研究人员将颗粒以每分钟250、500和1000片的速率，通过带或不带延长保压时间的双压工艺（预压与主压）压制成片剂。本研究采用多元数据分析（Multivariate Data Analysis）对工艺参数与片剂性质进行分析：首先对压片机参数设置、压片机与数据采集系统获取的日志数据开展主成分分析（Principal Component Analysis，PCA），以概览本次实验并探究所有工艺变量间的相关性；随后构建偏最小二乘（Partial Least Squares，PLS）回归模型，以挖掘机器设置与日志数据（自变量X）和片剂性质（因变量Y）之间的关联。本数据集包含了多元数据分析所用的全部数据（工作表“Data Table”）、所用键值的说明（工作表“Meaning Data Table”）以及本次实验的流程示意图（工作表“Meaning Exp”）。