SCG Chemicals is one of Asia’s largest petrochemical companies, with operations spanning upstream production of olefins to downstream production of polyethylene, polypropylene, and polyvinyl chloride.

With such a tightly integrated business, any asset failure has the potential to shut down the entire production line — with major financial repercussions. To address this and reach their goal of zero plant shutdowns, the team saw a need to harness data and build an advanced asset performance management (APM) and digital reliability platform that would help drive their digital transformation.

We helped the team develop a Digital Reliability Platform (DRP) with the ability to predict equipment health, monitor performance and cut unplanned downtime through advanced maintenance.

A number of AVEVA solutions are deployed in the platform. With AVEVA™ Predictive Analytics, the team is able to apply artificial intelligence and detect performance anomalies in real-time, using online and offline data collected through AVEVA™ Asset Information Management. At the same time, AVEVA™ Enterprise Asset Management improves how SCG teams contextualize and connect with their data to reduce human error and optimize plant efficiency.

As well as providing actionable information in less than 10 seconds, the cloud-based system has standardized work execution and risk management – delivering maintenance savings of 40% and helping the team work safely and sustainably.

Combining AI, predictive analytics, and machine learning on AVEVA™ Connect, our industrial cloud platform, the DRP has helped SCG Chemicals achieve industry-leading standards in plant efficiency and asset reliability. Due to its success, the platform has been scaled up across all 15 of their plants around the world.

Lubrizol is one of the world’s leading producers of specialty chemicals for the transport, industrial and consumer markets. As part of their long-term efforts to reduce process variability, the team set out to adopt a multivariate approach that could improve their process monitoring strategy and provide a smooth transition for operators.

Lubrizol knew that process variability was a clear target for improvement. Their existing model used traditional process monitoring and led to major variability, reducing reliability, affecting capacity and raising costs.

They wanted to introduce a multivariate approach that could analyze all variables and their relationships simultaneously, providing engineers with a full understanding of the process and accurate prediction of the final batch’s characteristics.

Lubrizol deployed AVEVA™ PI System, leveraging PI Asset Framework and Event Frames to capture historical data from previous batches. With the data now clearly accessible, the team could identify critical moments in the process and understand the levels of permissible variability that would still result in high quality outputs.

Combined with some simple data analytics, operators now have access to additional guidance throughout the process, as well as alert and alarming capabilities.

The new solution had an immediate impact, resulting in a 56% reduction in batch variety. Today, it’s helping improve process understanding across the business and equipping process engineers with the ability to understand and troubleshoot process disturbances.

Covestro is one of the world’s leading polymer producers, creating precursors for polyurethane foams and high-performance plastic polycarbonate, as well as for coatings, adhesives, sealants, and specialty products.

Sustainability is a key pillar of Covestro’s long-term business strategy. To achieve their goal of reducing energy and CO² consumption, the team used AVEVA™ PI System to enable a program called STRUCTese® — with remarkable results.

Thanks to a long-standing implementation of AVEVA™ PI System, the team at Covestro already had access to high quality, readily available data from across their operations.

The STRUCTese® program put this data to work. First, the team carried out a detailed evaluation of energy efficiency, including process analysis and a review of consumption, before identifying possible efficiency projects and creating action plans.

Next, Covestro made it easier for control rooms to see and understand process data, visualizing current performance against best practices and identifying opportunities for improvement.

Lastly, the team needed a way to see the results. More than 4,000 energy-specific tags were created and used to gather vital consumption data from across the business. With the ability to aggregate data at plant, site, or business unit level, the team was able to take the wide view — uncovering trends, revealing insights, and making adjustments as necessary.

Today, STRUCTese® has received energy management certification from the German government, securing major tax rebates for Covestro. The program has been implemented in more than 60 plants around the world, and has reduced energy consumption per ton of product by 30% and CO² consumption per ton by 39% — even as production capacity has increased.

Air Liquide is the world leader in gas production, spanning 75 countries and with a global revenue of €23.3bn. They specialize in producing essential small molecules, such as nitrogen, hydrogen, argon and oxygen for industrial customers. In 2015, the company launched an enterprise-wide program with two specific targets: zero unplanned shutdowns and double efficiency gain.

The team implemented a customized AVEVA™ PI System, enabling them to collect, transform and leverage data at scale. Each plant has its own distributed control system, collecting local data which is then collated at one of two centralized control centers, one for Europe and one for Asia. In total, more than 1 billion data points are collected daily. Information from outside sources, including energy markets, is also incorporated, providing remote and data-driven decision-making for their 250 global plants.

From here, teams at Air Liquide’s Remote Operations Control Centers (ROCCs) are able to see everything happening across the network in real-time. With the ability to troubleshoot or deploy optimizations remotely, the plant teams are free to concentrate on adding value on-site, in safety, reliability or maintenance.

This bird’s eye view has opened up incredible opportunities for optimization. Take the Singapore Pipeline, a 200km-long network made up of dozens of pieces of rotating equipment, each of a different age, generation and with different levels of efficiency. Optimizing such a complex operation was highly difficult, until the ROCC team stepped in.

They developed a Digital Twin that leveraged decades of operating data and combined it with real-time insights collected with PI System. The result was a decision-support tool that helped teams ensure the optimal combination of compressors and plant load to serve their customers, while reducing energy and CO² consumption.

It’s just one example of the at-scale optimizations made possible by AVEVA™ PI System, and the model continues to roll out across the Air Liquide network.