Shell, a global group of energy and petrochemical companies, was facing inefficiencies and limited flexibility due to the independent operation of its many refineries. The actions of one refinery could adversely affect another in the same region, leading to higher costs and lower overall profits. Each refinery conducted business in its unique way to increase profit margin, but such 'siloed' operations often resulted in inefficiencies and lower margins. Shell identified uncommon operating procedures at each of its refineries, which led to these inefficiencies and lower margins.

PETROLTERV, a Hungarian engineering design and consulting company, was tasked with revamping the gas treatment technology at Hungary’s largest underground gas storage facility to meet new European (EN) standards. The new standards imposed more stringent hydrocarbon and water dew point requirements for natural gas handling systems than what was previously prevailing in Hungary. The site had three gas treatment trains each employing a TEG (Triethylene glycol) dehydration unit and a low temperature separation (LTS) unit which employed a propane refrigeration system and brazed aluminum heat exchangers (BAHX).

The petrochemical company was facing significant losses due to light component losses that go to the bottom of a fractionation column and pressurize the downstream column. This pressure resulted in downstream column production being lost to the flare. This stream contained a very valuable product, and the loss represented more than $1M USD. The company was looking for a solution to understand and resolve this production problem faster to limit the losses.

Glanbia Food Ingredients’ facility in Ireland processes about 1.4 billion liters of milk annually into butter, cheese, milk proteins, and whey derivatives. Anticipated increases in milk supply meant that the plant would not meet processing demand in the near future, so Glanbia sought ways to improve production throughput in order to meet new expectations. Management decisions were based primarily on anecdotal information. Whenever a problem arose, managers would dig through log sheets and spreadsheets and talk to operators and engineers in an effort to determine the root cause of the problem. Each area had its own way of capturing the data and calculating and presenting performance metrics, which led to inconsistent and unreliable information. This lack of credible information resulted in less-than-optimal operating decisions. Improvement opportunities went unnoticed or were never acted upon because no one could determine the root cause of the problem.

Linde’s U.S. engineering organization was facing high estimating variances and overruns, coupled with a large, dispersed estimating team. The problem was diagnosed as an inconsistent use of tools and business processes in the estimating function. The company was looking for a more strategic, centralized solution to streamline its estimating discipline, improve the accuracy of capital cost estimates, and achieve long-term cost savings.

Saudi Aramco, the state-owned oil company of the Kingdom of Saudi Arabia, was facing a challenge with one of its semi-conversion refineries. The refinery was producing excessive fuel oil, which was limiting the facility’s margin to a level lower than comparably sized refineries. The company decided to revamp the refinery to upgrade the bottom of the barrel products to create more value and improve the refinery’s profit margins. The refinery was also considering changing the crude oil it was processing. The revamp plan included adding new units and modifying existing ones.

INEOS, Europe’s leading independent crude oil refiner, processes more than 410,000 barrels of crude oil per day. Their production network spans 76 manufacturing facilities in 20 countries around the world. INEOS’ success is linked to a simple approach to business — a focus on customer satisfaction, total quality and reliability. When INEOS set its mission toward continuous improvement to become a low-cost producer of high-quality products, the heat exchange system became a priority because of its impact on productivity, costs and overall profitability. Fouling in each heat exchanger and the entire heat exchanger train is a common problem for refineries. Without proper monitoring and insight, refiners resort to reactive rinsing and cleansing operations, significantly disrupting the safe, efficient operation of plants — and costing them millions of dollars in lost revenue.

PETRONAS Melaka Refineries faced the challenge of creating an integrated refinery scheduling model to eliminate many standalone spreadsheets and leverage multi-user interaction under a single network. The process was long and tedious, and led to different versions of the same schedule — which increased the likelihood for errors and resulted in less than optimal crude production.

S&B Engineers and Constructors Ltd., a Houston-based EPC, has been facing challenges due to shrinking client budgets and tighter project schedules. Clients are demanding more for less, including more detailed digital handover of data to accompany traditional project deliverables. To remain competitive, S&B needed to find a solution that was faster and more tailored to the process industries than the traditional approach of producing project estimates.

A major U.S. transportation company was facing significant losses due to undetected catastrophic failures of locomotives. These line-of-road (LoR) engine failures were costing the company over a million dollars each in repairs, additional operational costs, and fines. The company's existing reliability techniques were not sufficient to detect these failures in time, leading to disruptions in the delivery of customer goods and impacting the company's reputation for safety and reliability.

Hyundai Oilbank was facing a challenge with their FCC (Fluid Catalytic Cracking) unit yield. The yield was not matching the planned yield as the plans did not consider changes in feed quality. This discrepancy was causing inefficiencies in their operations and was a potential source of financial loss. The company needed a solution that could accurately factor in feed changes and optimize operations accordingly.

The company, a leading Asian refining company, was facing challenges in reducing planning run times while increasing solution quality. They wanted to gain time to explore complex, multiple price and operation scenarios and eliminate the occurrence of local optima. The company also wanted to increase internal customer satisfaction through faster response times to different business processes and have the ability to capture and explore more opportunities. The decision to expand the use of Aspen PIMS-AO was due to the recently enhanced global optimization capabilities with the new Aspen PIMS-AO V8.7 algorithm and the intention to explore the parallel processing feature for the maximum business impact.

The Siam Cement Group (SCG), the second largest company in Thailand, sought to enhance its existing production capabilities by implementing innovative non-linear Advanced Process Control (APC) software. The focus of this project was on the downstream petrochemical production lines of Thai Polyethylene Co., Ltd. & Thai Polypropylene Co., Ltd. These facilities produce a wide range of polyethylene, polypropylene, and high-value added products. The challenge was to drive enterprise value and maximize return on assets with non-linear APC and enable engineers to gain proficiency and extend APC applications across multiple polyolefin manufacturing units.

Phillips66, a leading integrated oil producer, invests millions of dollars a year in refining capital projects, which can include maintenance, clean fuels upgrades, and growth investments. Completing these projects in a timely, efficient manner will help the company meet its operational goals and significantly improve the bottom line. However, with market dynamics keeping refinery loads at over 90% capacity and regulatory pressures requiring clean fuels and emissions upgrades, Phillips66 faces a steady growth of downstream capital investment projects. The company adheres to three principles for each project: capital discipline, operational excellence and execution, and financial optimization. That’s why the estimating function—now managed through Aspen Capital Cost Estimator—is so critical in examining the volume of capital proposals, and providing estimates earlier in the process.

Fluor, a leading engineering and construction company, faced a challenge in modeling sulfur recovery units (SRUs) with both liquid elemental sulfur and vapor allotropes. The process typically required several simulation files which were iterated manually to balance material and energy recycle loops required in the COPE II process. Multiple files were generally required because of an inability to use multiple property packages in a single simulation. This manual adjustment of the recycle streams was time-consuming and introduced room for error. Fluor needed a solution that could integrate multiple property packages into a single simulation and offer several other benefits for their SRU COPE II modeling.

Criterion’s goal was to implement a planning and scheduling solution that eliminated legacy tools and transformed their Sales & Operations Planning (S&OP) process into a world-class operation. However, significant challenges within their supply chain and scheduling processes had to be addressed. Prior to the use of Aspen Plant Scheduler, site scheduling was onerous and time-consuming, so the scheduling time horizon was limited to less than three months. Prior to a rigorous S&OP process, demand was also not represented very far into the future. These factors combined to provide an inaccurate view of available capacity against which supply chain had to perform multiple, daily ad-hoc quote feasibility (Can we do it?) analyses, leading to occasional over-committed situations.

Oxiteno, a leading manufacturer of surfactants and chemicals, needed a plant-wide model to evaluate options that could increase plant capacity and quickly and accurately respond to market demand. With constant fluctuations in feedstock and energy prices, reacting to economic changes quickly was vital to capitalize on the most profitable assets. In the past, unit operations were modeled separately and case studies could not be analyzed quickly and accurately. It was very difficult to increase plant throughput by evaluating individual pieces of equipment without the ability to examine the effect of changing process variables on downstream processes.

Cabot, a global specialty chemicals company, operates 39 manufacturing plants across 19 countries. The globalization of Cabot’s business posed a significant challenge for the manufacturing function. Independent site-based groups needed to transform into an integrated global organization. Access to information from different sources — including manufacturing, the supply chain and financial systems — was vital to make better, faster business decisions. An MES could help with the transformation by integrating and visualizing information across the enterprise. To help overcome the challenge and realize the business potential, Cabot launched an MES visioning process to define the direction and business advantages for their manufacturing systems.

Cabot’s Carbon Black business was using their own Microsoft® Excel and Access-based tools for scheduling, which did not provide the visibility required to make timely business decisions. Planning was performed regionally, scheduling was performed offline through customized tools at each plant, and executing events was done manually in the ERP system. As a result, schedulers were forced to spend the majority of their time gathering the data needed to make decisions. Cabot sought to improve the information available to the schedulers and enrich communication along the supply chain.

The company initiated a production planning and scheduling project as part of a major initiative focused on process re-engineering and automation. The overall goal of the production planning and scheduling project was to support several business initiatives. These included replacing the manual scheduling process, improving customer service, optimizing raw material and finished products inventories, reducing costs associated with off-specification quality, campaign transitions, packaging, and logistics and distribution, sharing information and improving cooperation between marketing/sales and production planning functions, and integrating planning and scheduling with the ERP system.

A large producer of synthetic rubber had been having quality issues with its batch products. These quality issues were resulting in significant revenue loss, as the company often needed to either reprocess the material or sell it for a lower price than expected. The producer was unable to determine what was causing the batches to be out of spec. The company was investigating issues with a reactor process that brings together ingredients to manufacture synthetic rubber. There were multiple reactors that performed this process, but the Aspen ProMV project would focus on the production of one reactor.

Saras, the owner of the most complex refinery in the Mediterranean, was looking for ways to improve reliability in their capital- and asset-intensive refinery operations. They had a strategic objective to improve uptime and decrease maintenance costs. The challenge was to ensure reliable operation of a 300,000 BPD refinery and a 575-megawatt integrated gasification combined cycle (IGCC) power generation plant. The initial project focused on four pieces of equipment: a feed pump, a wash oil pump, a makeup H2 compressor, and a recycle compressor. The desired outcomes of the pilot project were an accurate solution that detects precise patterns of normal behavior, failures, and anomalies, a solution that indicates early warning, with significant lead time from point of detection to actual failure, and the ability to capture a failure signature and use it to detect failures in unseen data on the same assets and/or similar assets.

Pan Pacific Technologies, a small company with powerful thought leadership in the area of algae to biofuels conversion, was seeking a rigorous approach to validate the technical and economic feasibility of its proprietary algal conversion concepts. A key challenge was to find a modeling environment that would provide an effective way to capture and communicate their proprietary ideas to researchers worldwide. They needed to simulate a complex biological system that was previously difficult to model, improve understanding of process constraints and scale-up, and complete techno-economic analysis.

SK E&C, a global EPC and Total Solution Supplier, was facing fierce competition in bidding and estimating capital construction projects. The company needed a technology and workflow process that would allow them to compete against low-labor-cost competitors. The main challenges were improving target accuracy, maintaining sufficient data for a Class IV estimate, and optimizing bids as time was spent developing the estimates rather than refining them. The company also needed to counter global threats to their business with technology that would enhance efficiency and develop bids that were more accurate, flexible, and reflective of historical cost data.

Graham Hart, a UK-based supplier of engineered process systems, needed to deliver optimized designs that meet stringent performance conditions. The company's value proposition is in the supply of highly-reliable, high-performance heat exchangers. To achieve and maintain this differentiated market position, the ability of its engineering team to propose and deliver best-fit designs to meet stringent performance conditions is paramount. The engineering team needed to depend on the quality, accuracy, reliability, and predictability of the software tools used to conduct the modeling and analysis to develop and verify designs. This includes the actual layout and design of heat exchanger systems, including temperatures, configurations, and materials.

The chemicals industry is complex with a small number of raw materials often transformed into hundreds of thousands of final products. The industry employs expensive, heavy, and complex manufacturing assets that can cover the full spectrum of process operations: continuous, semi-continuous, or batch. Shutting down and then restarting the process is expensive; time consuming (think days, not hours); and has environmental, health, and safety implications. A hyper compressor’s job is to build up pressure needed in the conversion process. These compressors typically go down many times a year. Mitigating this problem could be worth millions of dollars to chemical companies.

In the chemical, oil, and gas and other process industries, EPC firms are tasked with designing and developing increasingly large and complex installations. EPCs face the challenges of highly competitive bid situations and then delivering those projects within tight budgets and timeframes. After start up, plant owner-operators face challenges related to ensuring efficient operations and maintaining or renewing assets over a period that can stretch into decades. In both cases, solutions such as Aspen Fidelis Reliability can provide significant value through discrete event simulation. The AspenTech solution constructs plant models and runs multiple scenarios to analyze the impact of variables such as equipment capacities, operating logic, and production schedules on system-wide performance over time.

AspenTech, a company with a 36-year history in process engineering simulation, advanced process control, process optimization, and supply chain activities, has decided to venture into the asset performance space. The decision was driven by feedback from customers who, despite praising AspenTech's process optimization tools, expressed that poor asset performance was hampering their overall business performance. They found that they could not optimize the process and improve profit margins when assets failed to live up to expectations and intended reliability. This sparked AspenTech's new direction towards optimizing overall asset performance in industrial process plants.

Siirtec Nigi, an engineering and contracting company, was tasked by one of their customers to nearly double sulfur production capacity. The challenge was to find the optimal level of oxygen enrichment and set up controls to increase sulfur recovery unit capacity. The customer was anticipating expensive changes with a huge impact on equipment and processes. The key challenge was determining an operating envelope for optimal operations.

CEPSA, an integrated energy company, was looking to create a solution that would involve various business units in a coordinated way to optimize the global margin by establishing an integrated management model. Prior to the corporate initiative to improve the business processes in CEPSA, schedulers had been using homemade tools based on Excel files that were managed and reported by each individual scheduling stakeholder in a refinery. Since this method of scheduling provided no collaboration, there was little to no interaction among schedulers, causing inefficiencies and lost opportunities within CEPSA’s refineries to execute on the optimal plan. Additionally, because the spreadsheets were standalone, they provided no integration with Aspen PIMS (CEPSA’s planning solution since 2014), creating siloed departments and a disconnect between planning and operations.