Developing a Model-Based Culture: Optimizing Chemical Production

  • May 09, 2016
  • AspenTech
  • Feature

By Terumi Okano, Product Engineering, AspenTech

Chemicals are the cornerstone of everyday life. In a world witnessing increasing industrialization and urbanization, the demand for products is creating an increasingly competitive landscape. Against a backdrop of market volatility and stringent governmental regulations, chemical companies must adapt to both regional and global competition through the downstream value chain. This requires operational efficiencies, streamlined processes and appropriate skills to get the most value from the operation and to meet customer demand.

To remain profitable, many bulk chemical companies are focused on implementing operational efficiency measures, such as reducing energy and driving maximum throughput of plant assets. Those businesses which adopt a model-based approach to manufacturing, utilizing cutting-edge technology, have the flexibility to address operational issues and achieve the most immediate benefits. With powerful tools, companies can minimize costly downtime, increase throughput and optimize product yields.

Getting the most out of bulk chemical plants

The bulk chemicals industry is energy-intensive, producing products, such as ammonia, sulphuric acid, sodium hydroxide, chlorine and ethane, in high volumes and at low margins. Approximately 60 percent of energy use in the bulk chemicals industry is for feedstocks or raw materials used in the manufacturing process of chemicals. Most bulk chemicals are intermediate products used to produce final products, such as plastic containers or fertilizer. In general, bulk chemicals fall into four groups: organic chemicals; resins, synthetic rubber and fibers, inorganic chemicals and agricultural chemicals.

According to the Energy Information Administration (EIA), the value of bulk chemicals shipments is expected to grow to $429 billion by 2025. As such, the global chemicals industry has witnessed rapid growth over the past decade, particularly in emerging countries like China. Many industry experts predict that at least half of the top ten chemical companies in the next ten years will come from China and the Middle East. Taking advantage of the shale gas boom resulting in cheaper feedstocks in the US, the chemical industry there is also strong. On the other hand, Europe will continue to experience slow growth with the on-going threat of chemical plant closures due to strong competition.

Reducing production costs is important for basic chemical producers and there is a strong recognition among industry leaders that technology can help significantly in driving the overall operational effectiveness of plants. For example, PwC recently completed its “Breakthrough Innovation and Growth” survey of nearly 1,800 C-suite executive-level respondents, including some 50 chemicals industry participants from 12 countries. 95 percent of chemicals industry respondents said they foresaw digital technology innovation at their company over the next three years and 50 percent expected breakthrough or radical advances.

Supporting operations with rigorous models

Investments in optimization software can increase reliability, reduce costs and create greater operational efficiencies in production and supply chain management. Embracing advanced integrated software solutions empower staff to optimize operations and take advantage of market opportunities.

The advanced engineering software available today addresses operational challenges by providing integrated solutions that tackle inefficiencies end-to-end throughout engineering, planning and scheduling and plant operations processes. Companies deploying the innovative software are able to generate millions of dollars of benefits per year per plant with payback in months instead of years. These advanced solutions bring broad benefits with respect to yield, quality, energy use, operational costs and process flexibility. This includes controlling the process with advanced process control, collection and analyzing data from the process with manufacturing executions systems, modelling the process with integrated simulators, improving the supply chain, inside and outside the plant and improving the process.

Making it easier to quickly get to the root cause of operational issues is vital to plant engineers. For example, through a familiar Excel interface, engineers and operators have the benefits of using a rigorous process simulator. This helps engineers tackle process instability by determining variable sensitivity and creating what-if scenarios of different process operations without needing to disrupt the plant. Using these intuitive tools, it is also easy to determine an optimal maintenance schedule by monitoring equipment performance (i.e. heat exchangers, reactors, columns).

Building the model

Being able to visualize plant data and predict values of process variables is essential when it comes to developing a model-based culture. Viewing contextual data alongside process data to show what is happening in production delivers greater insights into the source of problems. The process model drives value in plant operations, and by being detailed enough can robustly predict real plant behavior over an expected range of conditions linked to process data. The data itself is conditioned to smooth out measurement errors with an execution environment to run the model whether on-demand, scheduled or event-driven.

Using advanced integrated tools, the process engineer can build a model of the unit and validate it against plant data from the production engineer and the plant data historian. The model is then used to identify alternate operating conditions. By building an interface in Excel on top of the rigorous plant model and linking it with plant data tags, the chemical production engineer can use the model to identify alternate operating conditions. To take model-based operations to the next level, engineers can reconcile the model as the model runs online. Data is then saved in the data historian, so the production engineer can see immediately how the model changes over time. After using Real-Time Optimization (RTO) to deploy the model 24/7, the model calibrates itself daily and provides optimized set points to the process control system. The plant is then able to reach and maintain capacities higher than ever previously seen and frees up significant time for the unit engineer. Using a custom modeler makes it quick and easy to create unique process and equipment simulations that can be customized with accuracy and ease. The software helps to build custom forms and plots for customized models, so it is easy to lay out data in a way that makes sense to the engineer.

Integrated software for chemicals supports cross-functional collaboration through the use of consistent models and data. By driving process improvements and innovative designs through rigorous plant models, companies can:

  • Increase capacity and decrease energy
  • Improve yield and margins
  • Reduce capital and operating costs
  • Increase engineering efficiency
  • Bring new products and designs to market faster at a higher return on investment

Model for success

Chemical companies continue to experience volatility in commodity prices and increased competition with much of the market shifting eastwards. Many global chemicals companies are striving to tap into this booming business, even though they face strong rivalry from local companies in supply and demand.

Addressing asset optimization needs to be done in a holistic way to tackle debottlenecking issues and overcome operational complexities to produce higher product quality and yields at reduced costs. Better operating strategies can reduce overall costs, which include better energy usage, utility cost optimization, improving operating work process efficiency and lowering maintenance costs to help manufacturers be more profitable. Those bulk chemical firms that implement a model-based culture using cutting-edge technologies will improve end-to-end production performance and remain competitive in an uncertain marketplace.

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