Getting insights of the Process Plant through Petro-SIM
Is a Digital Twin necessary? That’s not the question. The question is what makes a Digital Twin a useful tool for the Process Industry?
Petro-SIM® simulation modeling software provides an accurate digital twin of your value chain from end to end. The result is insight into your processes of exactly “what it takes” to think, decide, and act in the Process Industry such as:
1. What it takes for an Operator in the field at night in the rain to climb up a ladder and rotate a valve ; to change a pump holding 320 degree Celsius fluid in it ; to fill liquid nitrogen (which is lower than minus 196 degree Celsius) through a valve in to a small potable drum from the liquid nitrogen line.
2. What it takes for a Panel officer to control the hazardous hydrocarbon plant by clicks of buttons and acknowledging several alarms.
3. What it takes for an Engineer who is striving hard for safety of all plant members while meeting the daily planned production demands irrespective of issues between maintenance team and operations team.
4. What it takes for Central Technical Services department engineers and analysts to keep on improvising the plant efficiency, productivity, and solving the bottlenecks.
5. What it takes for Top Management employees in Corporate offices to make decisions for finding new businesses, expanding current market share, and increasing the company’s share value.
Then put yourself in those situations.
“Tell me and I will forget,
Show me and I may remember
Involve me and I will understand”
Benjamin Franklin
As Benjamin Franklin said above, involve yourself to understand the system. To understand the system, you either become all above or experience all above with the help of a Digital Twin.
This Digital Twin not only presents you with the current situation, but also provides you the insights to improve the current situation and find the solution of most of the things mentioned above. It gives you the perspective to see the problem from the field level to Corporate office level.
As engine is for car, similarly simulation is for process industry. The performance of car and process industry is highly dependent on quality of engine and simulation respectively. Petro-SIM, a simulation tool from KBC (a Yokogawa company) for Process Industry is the heart of Digital Twin technology for several manufacturing sectors, such as Refining, Petrochemicals, LNG and upstream oil production.
Petro-SIM works in two different modes, steady state and dynamic.
Steady-state mode is widely used for Engineering and Optimization studies whereas Dynamic mode is mostly utilized in the field of Operator Training System (OTS) and for deep insight studies of the plant to understand transient behaviors especially in the area of plant safety.
A Digital Twin not only relies upon a robust simulation engine. Data needs to flow into and out of the Digital Twin and be displayed to the data consumers in a timely fashion, whether they be operating the unit or making decisions in the board room. With efficient data handling, information can be brought together from different systems to provide a holistic picture of unit performance (e.g. combining process, reliability and economic data) and allow for better and faster decision making. Petro-SIM makes this easy by being able to import/export data from/to data historians.
Success Story
Client Challenge
A liquefied natural gas (LNG) plant in South East Asia has eight trains. Their energy consumption is tightly linked to production. The reduction in global oil prices pushed the operator to move towards a “manage for margin” approach. Energy efficiency, the plants largest controllable operating cost became a concern. Their goal was to increase profits by reducing their energy costs and improving their yields.
They contacted KBC (a Yokogawa company) to help them improve their yields and identify energy saving methods. In addition, the operator wanted to develop a corporate culture of continuous improvement. They needed to improve their employee skill set so they could identify and implement their own profit improvement programs.
The Solution
KBC (a Yokogawa company) applied a structured margin optimization methodology, considering process energy and reliability interactions. The consultants performed a sitewide energy review of all eight trains using Best Technology benchmarking and gap analysis. They identified more than 100 profit improvement opportunities.
This included energy improvement potential projects. However, it was not practical to address this issue for just one train as it relates to site-wide power and boil-off balances. Complexity increases on multi-train sites, which typically share product storage and utility systems. This means changes on any one train will affect the others.
Only a structured methodology and tools that consider the interactions will achieve improvement in the production margin. By using Petro-SIM simulation software, KBC (a Yokogawa company) and the client team worked together to build a digital twin of the first train. KBC (a Yokogawa company) developed a complex-wide roadmap to outline constraints and manage uncertainty around gas feed composition changes and site expansion plans.
The digital twin helped to identify gaps and test the value of the proposed improvements. The project team agreed to implement 6 of the identified production improvement opportunities worth over 73 million/year with no capex.
Using a holistic approach, the consultants managed the complex interaction of process, fuel, steam, and power balances. They provided reduced bottlenecks and improved reliability performance
Results
The operator increased profits by 73 million USD /year.
The organization now has a robust multi-year investment plan and sustainable improvement processes as part of their culture. This project enhanced the skill set of the plant engineers so they could sustain their own profit improvement initiatives going forward for the other seven trains. They continue to identify and implement profit improvement programs to maintain their competitive edge.