Key points
Higher performing assets deliver higher results. Improving operational management can dramatically help operations staff to quickly predict outcomes and better understand the impact of changes on production performance. An efficient operating model can be the difference between razor-sharp decision-making and blunt poor execution.
The model-based approach that improves asset performance
To determine the appropriate strategy for optimising plant assets, it is essential to align goals towards achieving full customer satisfaction and product differentiation. Investment in proven cutting-edge technology is a crucial component of the game plan to be successful.
According to many industry analyst firms, including, McKinsey, Gartner, IHS and others, business leaders today see maximising asset utilisation as a primary objective. Reports show that although running production with traditional methods has previously brought success, without the right tools, processes and collaborative strategies in place, chemical firms will struggle to survive. The message is adapt or die.
Obstacles and opportunities
The world's population is expected to rise from 7.2 billion to over 9 billion by 2050 and with an increasing number of people living in densely-populated urban areas, consumer demand for plastics and chemicals will rise markedly.​
Interestingly, the core of the chemicals industry is shifting to Asia, which has experienced major growth in the past 25 years and now owns nearly half of global chemicals sales.
Chemical plants have for many years comfortably operated using proprietary methods and relied heavily on experienced operators who have accumulated decades’ worth of plant production knowledge.
Best case scenarios have been based upon trial and error or ‘rule of thumb’ methods, which have formed the backbone of policy and procedures. When an organisation loses this expertise and knowledge through retiring veterans or workforce reduction, then the business faces serious challenges to maintain standards.
In addition, departments that operate in silos limit communication and this inhibits collaborative work practices, which in turn creates inefficiencies affecting overall plant performance.
Opportunities, however, do exist even in this turbulent market. Chemical manufacturers focused on improving operational excellence using scalable models will significantly reduce costs and mitigate downtime.
Being lean means manufacturers can ensure continuous process improvements across the organisation. Optimised assets dramatically increase yields, lower maintenance expenditures and drive greater energy efficiencies, which help protect product quality and boost profit margins.
So, what if there was a more effective, robust method of capturing knowledge, such as process simulation with plant data, to achieve consistent quality results?
Better process insights and integrated workflows deliver greater efficiency and reliability. Model-based decision-making brings together plant simulation with plant data, whereby engineers are able to make better-informed decisions based upon accurate behaviour of the model.
The process model drives value in plant operations because they are robust, detailed and can predict real plant behaviour 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.
With this approach, operators can still use their knowledge and skills, but are able to make corrective decisions to plant production idiosyncrasies based upon deeper process insights, as well as see precisely the consequence of their actions.
In addition, the highly valuable knowledge gained can be captured in the model, which is accessible to all key stakeholders. Hence, this method of working is more transparent, investigative, reliable and sustainable and avoids information simply being stored in someone’s head.
Best practice forms the blueprint for success and adds structure to processes, aligns functions creating a value stream from end-to-end engineering through scheduling and plant operations.
Modelling success
If business investment plans represent the overall physical architecture of the asset, then the operating model represents how the plant assets function.
Therefore, to maximise production performance, streamline processes and push the operation to safe, but productive limits, adopting the model-based approach brings tangible benefits to the bottom line.
All chemical assets operate under constraints. Rigorous software modelling capabilities help engineers understand how to operate optimally within asset limitations.
When operational changes occur, engineers can use software models to quickly predict the impact of changes for an improved workflow. Lowering maintenance costs is also important for delivering greater efficiencies.
Engineering simulators
Engineering simulators make it easier to monitor inferential variables to determine the optimal maintenance schedule based on cost and impact to plant performance.
Furthermore, integrated support through the engineering lifecycle, allows the flexibility to complete all engineering needs, such as simulation, equipment design, conceptual and detailed economic analysis and safety analysis – all in one software suite, reducing total cost of ownership.
Having on-demand operations support allows unit engineers to plug real plant data into process models to more quickly troubleshoot problems. The tools today are designed with a simple user interface that provides fast support and on-boarding to both new and experienced engineers.
Using advanced process control software enables companies to control operations more effectively in real-time and deploy a continuous self-calibrating model that provides optimised set points to the process control system.
For example, the aspenONE software suite 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 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, collecting and analysing 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 workflow process.
Benefits of model-based decision-making
Typical benefits enjoyed by many chemicals companies using robust model-based decision-making include:
- Quickly predict plant behaviour based upon reliable data to determine optimal production outcomes
- Reduce energy consumption by 5–20% by modelling the complex cost trade-offs that exist within a chemical plant to make operational decisions
- Increase yield by 1–5% and produce consistent quality products to meet customer demands
- Ensure safe, consistent and efficient operations with continuous coordination of plant-wide changes
- Automatically detect, control and correct operating conditions that may lead to costly shutdowns
- Avoid ad-hoc manual support methods that cause inefficiencies and time-consuming tasks
- Improve overall plant profitability
Cutting out the competition
A rigorous operating model forms the building blocks to a successful strategy. To overcome complexity and achieve business goals, smart chemical companies today are adapting their business strategies and aligning operations with the use of cutting-edge process optimisation software.
These firms have experienced significant increases in production yields, consistent product quality and have enjoyed uplifting financial benefits.
Successful chemicals companies today are striving to lead by example in best practice and provide innovative solutions that create greater value. Pursuing operational excellence, whilst considering safety, strengthens an organisation’s foothold in the market and ensures cost competitiveness from feedstocks source to product delivery.
Therefore, to exceed in serving customers, chemical companies must embrace a model-based decision-making approach using cutting-edge software to achieve reliable execution, thereby paving the way for them to be stronger and leaner.
With the right operating model, firms will become more agile, better equipped to reach numerous types of customers with multiple and diversified products, as well as be able to successfully outpace competitors in a rapidly shifting marketplace.
