This paper presents an implementation of an automated algorithm powered by market and physical data to improve procurement and production of a chemical plant with the goal of improving the overall economics on the entity. Herein, the algorithm is applied to two scenarios that serve as case studies: conversion of natural gas to methanol and crude palm oil to biodiesel. The program anticipates opportunities to increase profit or avoid loss by analyzing the futures market prices for both reagents and the products while considering cost of storage and conversion derived from physical simulations of the chemical process. Analysis conducted on June 11, 2018, in the biodiesel scenario shows that up to 219.28 USD per tonne of biodiesel can be earned by buying contracts for delivery of crude palm oil in July 2018 and selling contracts for delivery of biodiesel in August 2018 which equates to a margin 11.6% higher than in case of the direct trade. Moreover, it is shown that losses of up to 11.3% can be avoided, and therefore, it is shown that there is realistic scope for increasing the profitability of a chemical plant by exploiting the opportunities across different commodity markets in an automated manner. Consequently, such a cyber system can be used to assist eco-industrial parks with supply chain management, production planning, as well as financial risk governance and, in the end, help to establish a long-term strategy. This study is part of a holistic endeavor that applies cyber–physical systems to optimize eco-industrial parks so that energy use and emissions are minimized while economic output is maximized.

中文翻译：

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化工厂的增强的采购和生产策略：利用实时财务数据和高级算法

本文介绍了一种由市场和实物数据提供支持的自动化算法的实现，以改善化工厂的采购和生产，目的是提高实体的整体经济性。在本文中，该算法适用于两个案例研究：天然气转化为甲醇，粗棕榈油转化为生物柴油。该程序通过分析试剂和产品的期货市场价格，同时考虑化学过程的物理模拟得出的存储和转换成本，来预测增加利润或避免损失的机会。2018年6月11日在生物柴油情景中进行的分析显示，这一数字高达219。通过在2018年7月购买原油棕榈油的交付合同并在2018年8月出售生物柴油的交付合同，每吨生物柴油可赚取28美元，这比直接贸易的利润率高11.6％。此外，显示出可以避免高达11.3％的损失，因此，显示了通过自动利用不同商品市场中的机会来增加化工厂的盈利能力的现实空间。因此，这样的网络系统可用于协助生态工业园区进行供应链管理，生产计划以及财务风险治理，并最终帮助制定长期战略。