Aspen Technology (AspenTech)
Canvas Category Software : Information Technology : Asset Performance Management
AspenTech is a leading provider of enterprise asset performance management, asset performance monitoring, and asset optimization solutions. AspenTech’s suite of asset management software helps organizations to streamline engineering and maintenance processes, leading to reduce downtime and increase operational efficiency. AspenTech has also been an industry leader in leveraging industrial AI, plant digitalization, and digital twin technology to ensure our customers keep pace with rapidly evolving manufacturing technologies. Predictive Analytics for industrial data helps AspenTech deliver downtime reduction for the connected enterprise.
Assembly Line
Seeq and AspenTech accelerate self-service industrial analytics on AWS
With Seeq powered by the wealth of data stored in IP.21 running on AWS, you can clean, perform calculations on, and analyze IP.21 data—including context from relational data sources such as MES, batch, and other applications—to diagnose and predict issues and share findings across the organization. With NRT expert collaboration and deeper insights, Seeq helps organizations advance toward their sustainability and operational excellence goals. By tapping into rich data from IP.21, Seeq helps substantially reduce maintenance costs and minimize downtime. You can set up advanced workflows like ML with data-driven, state-of-the-art methods already proven in critical industries using the Seeq SaaS platform in conjunction with the AWS Cloud. The Seeq SaaS solution is listed on AWS Marketplace, making it easier to procure, deploy, and manage your workload.
Industrial Software Helps Pipeline Operators Transition to More Sustainable Operation
For many midstream companies, the key to meeting that challenge lies in increasing flexibility. Some operators are looking at ways to convert their pipelines to transport hydrogen and carbon dioxide (CO2). But transporting these materials that are relatively new to the industry requires new methods of operation and monitoring, which in turn requires increased digitalization. To be successful, teams need a perfectly clear vision of what is going on—all the time.
The key is to implement modern supervisory control and data acquisition (SCADA) solutions to help keep a finger on the pulse of operations. Today’s modern SCADA solutions bring real-time operational data from the field to operators—in the control room, in the field, or wherever else they may be. But to get the most out of those solutions, teams also need powerful industrial software to give them insight into how well their operations perform. One of the most critical tools midstream operations teams need is pipeline management software, for analytics and real-time operational intelligence across their network.
Unlock Trapped Value – Digital Transformation in the Chemicals Industries
Business processes, a set of activities that accomplish a specific organizational goal, are everywhere throughout organizations. In this blog, I highlight four key business processes present in chemicals companies and their purposes. I also share some examples of chemicals companies that have unlocked business value within and across these processes as part of digital transformation initiatives.
Organizations should pay attention to business processes because they determine how well they can move toward achieving its sustainability, agility and profitability goals. The better a company’s processes, the more effective the business. More importantly, an organization’s business processes can become a competitive advantage for chemicals’ producers, especially if you deeply synchronize key value chain processes with manufacturing operations processes. This is critically important in the context of digital transformation initiatives.
Emerson Unveils Architecture Vision for ‘Boundless Automation’
Building on a deep legacy of industry-leading digital automation expertise through its Plantweb™ digital ecosystem, global technology and software company Emerson (NYSE: EMR) today shared its vision of a new software-defined automation architecture designed to catalyze the future of modern manufacturing.
This next-generation architecture will empower companies through “boundless automation” to manage, connect and deliver operational technology (OT) and information technology (IT) data seamlessly and easily across the enterprise. Moving data freely and securely across OT and IT domains – from the intelligent field to the edge and cloud – will enable operational and business performance optimization across the enterprise.
Emerson, drawing upon decades of automation leadership through its preeminent Plantweb digital ecosystem, shared this vision to accelerate manufacturing today at its Emerson Exchange convening nearly 3,000 industrial experts to discuss emerging ways to optimize business and sustainability performance through advanced automation. This vision follows Emerson’s latest expansion of Plantweb with the Aspen Tech industrial software portfolio.
Improving asset criticality with better decision making at the plant level
The industry is beginning to see reliability, availability and maintainability (RAM) applications that integrally highlight the real constraints, including the other operational and mechanical limits. A RAM-based simulation application provides fault-tree analysis, based on actual material flows through a manufacturing process, with stage gates, inventory modeling, load sharing, standby/redundancy of equipment, operational phases, and duty cycles. In addition, a RAM application can simulate expectations of various random events such as weather, market dynamics, supply/distribution logistical events, and more. In one logistics example, a coker unit’s bottom pump was thought to be undersized and constraining the unit production. Changing the pump to a larger size did not fix the problem, because further investigation showed insufficient trucks on the train to carry the product away would not let the unit operate at full capacity.
Emerson and AspenTech Complete Transaction, Creating New AspenTech
Emerson (NYSE: EMR) and AspenTech announced the successful closing of the combination of Emerson’s industrial software businesses – OSI Inc. and its Geological Simulation Software business – with AspenTech to create a global industrial software leader (“new AspenTech”). With the close of the transaction, Emerson owns 55% of new AspenTech on a fully diluted basis and AspenTech shareholders own the remaining 45%. Shares of new AspenTech will begin trading on NASDAQ under the ticker symbol “AZPN” (previously AspenTech’s ticker symbol) starting May 17, 2022.
Make Digital Twins an Integral Part of Your Sustainability Program
Digital solutions provide the visibility, analysis and insight needed to address the challenges inherent in sustainability goals. A digital twin strategy as part of an overall digitalization plan can be a crucial capability for asset intensive industries such as refining and chemicals. A digital twin needs to encompass the entire asset lifecycle and value chain from design and operations through maintenance and strategic business planning.
Comprehensive sustainability solutions are stretching the capabilities of thermodynamic first principle-based digital twins and driving the need for the next generation of solutions. Reduced order hybrid models offer a critical capability to achieve digitalization, sustainability and business goals faster. Reduced-order models can abstract models to enterprise views which inform executive awareness and strategic decision-making. Site-wide models can run faster and more intuitively to drive agile decision-making and optimize assets to achieve safety, sustainability and profit.
How and Why Pharmaceutical Manufacturers Are Applying Artificial Intelligence
“Opportunities to reduce manufacturing costs exist across all stages of the product lifecycle. Advanced analytics can reveal those opportunities, allowing pharma companies to take informed action to save money,” said Richard Porter, global director, pharmaceuticals, at AspenTech. “Whether using multivariate analytics to identify process degradation and its impact on quality or predicting final product quality to reduce lab testing lag times, these techniques offer pharmaceutical companies a competitive advantage.”
A purified water system at a pharmaceutical manufacturing facility.“The company tried to avoid batch losses—with each batch valued between $250,000-$300,000—as frequent shutdowns to replace the seals limited capacity,” said Porter. “As the company needed to ramp up capacity, it purchased two additional mills. Adopting Aspen Mtell, which connects to OPC UA supported devices, for predictive maintenance allowed the company to reduce supply chain disruptions from seal replacements and cut lifecycle maintenance costs by 60%. In addition, the company reduced capital expenditures and associated lifecycle maintenance costs by 50%.”
Debottlenecking Takes A Broader View
AspenTech’s strategy is to seek more innovative and lower-cost debottlenecking solutions by looking at the system in a broader way, considering whole plant operation from a process and energy point of view as opposed to addressing each bottleneck in isolation.
One such case study involves a 39,000-tonne/yr Reliance Industries’ acrylonitrile plant in India. Here, AspenTech’s modeling tool, Aspen Plus, was used to develop a steady-state model of the total plant in an effort to address a number of processing challenges. The simulation so far has spurred a 50% reduction in hydrogen cyanide emissions, a 75% decrease in effluent color and a 15% increase in acetonitrile concentration. An ongoing study at the same site also might lead to a cut in flare losses that currently are running the equivalent of about $22,500/yr.
Another project spotlighted at the conference involves cryogenic unit number one at Pemex’s Ciudad Pemex gas processing plant in Mexico. It had been operating at an efficiency of 76.72% for C2+, well below its originally designed capability of 81.94%. Once updated to reflect the plant’s current operating conditions, the Aspen Plus model pinpointed low efficiency in a heat transfer unit. Adjusting that unit gave a production improvement worth $7.6 million/yr.