Mitsubishi Chemical Group Corporation, Japan’s largest chemical company, faced quality problems in the company's polymer manufacturing processes that could not be detected on time, resulting in impacts to production. Using Aspen Hybrid Models with Aspen Plus®, Mitsubishi Chemical Group Corporation had the opportunity to create a robust and performant model that accurately predicted quality issues and supported preventive actions.

Novozymes A/S, a global biotechnology company based in Denmark, was looking to support the development and optimization of biodiesel processes due to increasing biodiesel market demand, rising materials costs and more stringent industry regulations.

Repsol S.A. is a global energy and petrochemical company based in Madrid, Spain that operates three integrated petrochemical complexes, managed as a single hub. Repsol was looking for an end-to-end supply chain control tower that would provide economic and customer service trade-offs for planning across the entire chemicals value chain.

SABIC is a leading multinational manufacturing company, specializing in the manufacture of petrochemicals, chemicals, industrial polymers, fertilizers and metals. Energy efficiency is a key focus area for SABIC. To close the gap towards achieving 2025 goals, SABIC identified the need to quantify energy losses and execute actions to optimize operations while addressing daily plant challenges.

Learn how Borealis, a leading provider of innovative solutions in the fields of polyolefins, base chemicals and fertilizers, implemented Aspen PIMS-AO to support the optimization team and bring about better decision-making for more profitable results. This case study explores how Borealis achieved dramatically faster run time, employed nonlinear modeling, deployed planning models to a centralized, virtual environment, and eased software deployment time and maintenance with more efficient use of hardware.

As part of an effort to drive reliability in its refinery operations, Saras turned to Aspen Mtell® prescriptive maintenance to improve equipment uptime and decrease maintenance costs.

Shell’s Manufacturing Margin Optimization team uses AspenTech solutions to optimize its energy and petrochemicals business, including planning and scheduling applications. In a highly collaborative global project with AspenTech, Shell successfully deployed Aspen PIMS-AO in the Cloud resulting in margin uplift, improved work-life balance and reduced IT costs. Read this case study to learn how you can improve margins with Aspen PIMS-AO in the Cloud.

Shell’s Manufacturing Margin Optimization team uses AspenTech solutions to optimize its energy and petrochemicals business, including planning and scheduling applications. In a highly collaborative global project with AspenTech, Shell successfully deployed Aspen PIMS-AO in the Cloud resulting in margin uplift, improved work-life balance and reduced IT costs. Read this case study to learn how you can improve margins with Aspen PIMS-AO in the Cloud.

壳牌的制造业利润优化团队使用AspenTech解决方案优化其能源和石化业务，包括规划和调度应用程序。 在与AspenTech高度合作的全球项目中，壳牌成功地在云上部署了Aspen PIMS-AO，从而提高了利润率，改善了工作与生活的平衡，降低了IT成本。阅读本案例研究，了解如何在云中使用Aspen PIMS-AO提高利润率。

Learn how one of world’s largest multinational energy companies used Aspen GDOT to maximize production of specific diesel and jet fuel products at one of its refineries. By using real-time optimization across multiple APC units, the refinery was able to decrease sulfur giveaway by 70%. Download this case study to learn how you can optimize production and reduce product giveaway.