Dataset - Biopharmaceutical manufacturing

This data was generated using an advanced mathematical simulation of a 100,000 litre penicillin fermentation system referenced as IndPenSim. All details describing the simulation are available on the following website: http://www.industrialpenicillinsimulation.com/. **IndPenSim **is the first simulation to include a realistic simulated Raman spectroscopy device for the purpose of developing, evaluating and implementation of advanced and innovative control solutions applicable to biotechnology facilities. This data set generated by IndPenSim represents the biggest data set available for advanced data analytics and contains 90 batches with all available process and Raman spectroscopy measurements (~2.5 GB). This data is highly suitable for the development of big data analytics, machine learning (ML) or artificial intelligence (AI) algorithms applicable to the biopharmaceutical industry. The 90 batches are controlled using different control strategies and different batch lengths representing a typical Biopharmaceutical manufacturing facility:<br>batch_recipe: Controlled by recipe driven approachbatch_operator: Controlled by operatorsbatch_APC: Controlled by an Advanced Process Control (APC) solution

本数据集基于命名为IndPenSim的10万升青霉素发酵系统高级数学仿真模型生成。该仿真的全部细节可通过以下网址获取：http://www.industrialpenicillinsimulation.com/。IndPenSim是首款集成真实模拟拉曼光谱（Raman spectroscopy）设备的仿真系统，旨在开发、评估并落地适用于生物技术设施的先进创新型控制方案。由IndPenSim生成的本数据集是当前面向高级数据分析的规模最大的公开数据集之一，包含90个发酵批次的全流程工艺数据与拉曼光谱测量数据，总数据量约2.5 GB。该数据集十分适合用于开发适用于生物制药行业的大数据分析、机器学习（ML）或人工智能（AI）算法。本次数据集的90个发酵批次采用不同控制策略与批次时长，覆盖典型生物制药生产场景，具体控制方式如下：
- batch_recipe：采用配方驱动模式实施控制
- batch_operator：由操作人员手动控制
- batch_APC：通过先进过程控制（APC）解决方案实现控制

搜集汇总

背景与挑战

背景概述

该数据集是通过IndPenSim模拟生成的青霉素发酵系统数据，包含90个批次的过程和拉曼光谱测量数据（约2.5GB），适用于大数据分析和AI算法开发。数据集特别之处在于包含了三种不同控制策略（配方驱动、操作员控制和高级过程控制）的批次数据，模拟了典型生物制药生产设施的场景。