Corporate Responsibility

Why digital twins should be an integral part of sustainability programmes

By Dr Paige Morse, Chemicals Industry Lead at AspenTech

In today’s volatile chemicals marketplace, managing the complexity of tradeoffs between profitability and sustainability is daunting, given the volume of information to be analyzed and the need for agility and scenario development. Implementing a digital twin strategy as part of an overall digitalization plan is key. A digital twin has greatest value when aligned with business and sustainability strategy, aiding decision-making and helping to enable the achievement of important corporate goals.

Today, when it comes to sustainability, chemical companies are moving towards specific process metrics that consider emissions and resource use. These solutions provide the visibility, analysis and insight needed to address the challenges inherent in sustainability goals. Success begins by harnessing the voluminous data available from operations — applying new technologies, such as artificial intelligence (AI) — to gain insight and to control operations; and empowering operators to make the decisions that will deliver performance to customers while also addressing societal sustainability and business profit.

Using a digital simulation of operational processes, companies can select the best process scheme and equipment to maximize energy efficiency and reduce emissions. Design engineers can weigh the best options, selecting process steps and equipment that deliver the best outcome. After construction, these same models are used to optimize operations by adjusting them in accordance with feedstock and operational variations to ensure efficient resource and energy use.

Additionally, engineers can improve process yields and minimize waste discharged from production units, as well as boost efficiencies through digital solutions. And they’re exploring new energy sources with lower carbon footprints. Digital twins give insight into these options, allowing companies to compare existing operations with future alternatives.

Charting progress on sustainability is important to success, a process made easier with visibility gained through digital dashboards. Process simulation technology tracks and optimizes CO2 and other pollutant emissions and effluents; the same tools, combined with other technologies such as planning solutions and enterprise visualization tools, provide the basis for emissions reporting for chemical plants.

Types of digital twin

Digital simulations, typically referred to as digital twins, can be classified according to three main use cases: asset-focused as the plant digital twin; process optimization through the operational excellence digital twin; and reliability with the operational integrity digital twin.

Plant digital twin

These models simulate the process plant using rigorous engineering simulations, enhanced by AI capabilities. They can also include embedded cost and risk models enabling alternative investment and business scenarios to be explored using a range of market views. They can be deployed offline or online and are often calibrated to plant operating conditions through autonomous model tuning.

This concept can be applied across a wide scope: from single equipment, such as a reactor, to unit operations (steam cracker), plant-wide (energy and utility systems), or enterprise-wide (entire complex or regional operations).

In the context of sustainability, the plant digital twin helps engineers integrate the safety needs of the process while also considering its environmental impact. From the start of a project, process engineers can design for process safety, including pressure relief and flare systems, delivering optimal plans that comply with industry safety standards, and more efficient designs that reduce the carbon footprint.

Operational excellence digital twin

Plant operations, from a business level to a control level, can be modelled and virtually viewed as planning, scheduling, control and utility analysis tools. Operational excellence digital twins inform business decisions such as supply chain planning, and can also aid technical decision-making, such as optimizing quality, energy use, emissions compliance and safety.

Digital twins of supply chains have found particular value in the global chemicals industry, where long and complex supply lines can become disrupted and uncertain. A model of the production plan for a site or integrated business unit helps to identify efficiency opportunities throughout the planning process, such as an optimum production sequence that minimizes lower quality production between grades.

Operational integrity digital twin

This digital twin can provide guidance on both tactical and strategic decisions around prescriptive maintenance, offering real-time recommendations to maximize uptime. Such insight is used to adjust production to manage failing equipment, minimize environmental impacts, mitigate production losses, and prioritize safety. In addition, quality and risk assessment provide a future view of equipment and asset health, risk profiles and the root cause of failures to improve uptime and operational integrity. The scope of the operational integrity digital twin ranges from a single piece of equipment, a single process unit, to a plant-wide or enterprise-wide twin based on the challenges for each production system.

The AI-enabled solution uses machine learning to identify precise failure patterns with high accuracy to predict equipment degradation weeks or even months in advance so that action can be taken to prepare and avoid a potential environmental or safety incident and to minimize business disruption. The technology learns from existing design and operations data and then integrates process knowledge to perform prescriptive maintenance and optimize asset performance.

Looking ahead

Global efforts to move towards new energy sources and the circular economy will drive a strategic shift in business metrics and the practices that will enable future success. Digital twins are key to this, enabling improved process design, greater manufacturing insight, and better operational integrity.

The integration of sustainability targets with business goals will be transformational for chemical companies, especially as these topics are being raised in shareholder meetings by large institutional investors and by the media. And this activity also positions businesses towards long-term business success.

Achieving the fragile balance of sustainability goals — equally considering people, planet and profit — is a challenge, but one that must be addressed to be competitive in the chemicals markets of today and tomorrow.