Data for: Modern day monitoring and control challenges outlined on an industrial-scale benchmark fermentation process

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: 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 100 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 100 batches are controlled using different control strategies and different batch lengths representing a typical Biopharmaceutical manufacturing facility:

Batches 1-30: Controlled by recipe driven approach
Batches 31-60: Controlled by operators
Batches 61:90: Controlled by an Advanced Process Control (APC) solution using the Raman spectroscopy
Batches 91:100: Contain faults resulting in process deviations.

Please reference:

Goldrick S., Stefan, A., Lovett D., Montague G., Lennox B. (2015) The development of an industrial-scale fed-batch fermentation simulation Journal of Biotechnology, 193:70-82.
and
Goldrick S., Duran-Villalobos C., K. Jankauskas, Lovett D., Farid S. S, Lennox B., (2019) Modern day control challenges for industrial-scale fermentation processes. Computers and Chemical Engineering.

Additionally help publicise this work on the following platforms:
Twitter: @Stephen_Goldric
Github: StephenGoldie
LinkenIn: Stephen Goldrick - Post Doc @UCL Biochemical Socitey

本数据集由IndPenSim高级数学模拟系统生成，该系统模拟了一个100,000升青霉素发酵系统，被称作IndPenSim。描述该模拟的所有细节均可在以下网站上查阅：www.industrialpenicillinsimulation.com。IndPenSim是首个纳入真实模拟拉曼光谱设备以开发、评估及实施适用于生物技术设施之先进与创新控制解决方案的模拟。由IndPenSim生成此数据集为目前可供高级数据分析的最大数据集，包含100批次的全部工艺及拉曼光谱测量数据（约2.5GB）。该数据对于大数据分析、机器学习（ML）或人工智能（AI）算法在生物制药行业的应用极为适宜。100批次通过不同的控制策略和不同的批次长度进行控制，以模拟典型的生物制药制造设施：

批次1-30：通过配方驱动的方法进行控制
批次31-60：由操作员进行控制
批次61-90：通过利用拉曼光谱的先进过程控制（APC）解决方案进行控制
批次91-100：包含导致工艺偏差的故障。

请参考以下文献：
Goldrick S., Stefan, A., Lovett D., Montague G., Lennox B. (2015) 工业级分批发酵模拟之开发，Journal of Biotechnology，193:70-82。
以及
Goldrick S., Duran-Villalobos C., K. Jankauskas, Lovett D., Farid S. S, Lennox B., (2019) 工业规模发酵工艺的当代控制挑战，Computers and Chemical Engineering。
此外，请在以下平台宣传此项工作：
Twitter: @Stephen_Goldric
Github: StephenGoldie
LinkedIn: Stephen Goldrick - 博士后 @UCL 生物化学学会

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100,000升青霉素发酵系统的数据，包含100个批次的详细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。数据集特别设计了不同的控制策略（包括配方驱动、操作员控制、APC和故障批次），为生物制药行业的研究提供了丰富的实验材料。