<img height="1" width="1" style="display:none;" alt="" src="https://dc.ads.linkedin.com/collect/?pid=544292&amp;fmt=gif">

Innovative Thinking

4 Ways to Improve Midstream Process Optimization

acd drives vs dc drives (1)-1.png

Uncertainty in global markets acts as one of the biggest motivator for optimization of all sorts. The recent oil price slump was alarming for all, from government-owned oil companies to century old gas-giants. In such situations, every dollar saved per unit is rewarded, as the stakes are simply too high. Process Optimization is one of the most cost-effective ways to improve profit margins and drive a company through prolonged market slumps.

Process Optimization is vital for improvements in output, efficient utilization of resources and increased plant life. It can be seen as a systematic analysis & upgradation of available industrial assets, and improvement of standard operating procedures. The implementation can vary from the smallest of changes such as inlet/operating temperature to the redesigning of assembly lines. In total, there are four major areas through which midstream process optimization may be improved:

Initial Process

Most modern plants & facilities are designed along the principle of highest possible efficiency but sometimes a few hidden errors & loopholes, dent the entire effort. Optimization may involve revisiting the original plans in search of flaws that may have an appreciable effect on the overall efficiency. For instance, a compressor station having three compressors may have increased maintenance cost in the face of lower demand. Initial process optimization would involve redesigning or rectifying the workings of the compressor so it can be equally profitable under lower load.

Furthermore, rerouting waste products which may act as a source of energy for other machines is also a great way to achieve optimization. For example, feeding generators with excess flare gas from a gas plant can help achieve lower electricity overheads.

Process Parameters & Constraints

As a plant or facility ages, its machinery faces greater inaccuracies, weaker controls and overwhelmed alarms. Wear & tear takes over rotary machinery while corrosion of underground components also becomes an issue. Optimizing the process parameters & constraints involves analyzing the process according to the plant’s conditions and reviewing the parameters to make the best use of available resources. Improved reliability & flexibility can be achieved by efficient management of equipment loads and their associated physical constraints.

A redesigned alarm management system can go a great way and help normalization of human resources in a better manner. Furthermore, such a system would also increase the longevity of the plant’s machinery and bring down regular maintenance costs through preemptive monitoring.

Equipment, Instruments & Devices

With the passage of time instruments & measurement devices lose their tuning. Sensors lose their accuracy and thus give incorrect readings regarding an industrial asset. This leads to lower process yields. Tuning instruments, depending on the frequency of its usage, can rectify this issue and result in greater throughputs. This would also help prevent bigger mishaps in the form of total equipment failures.

Human Interaction

At the end of the day, no matter how mechanized or automated a process becomes, it would require the final say of a human supervisor or operator. An operator is a necessity for any central control system, as he/she is well-equipped in dealing with the system’s intricacies & faults.

A regular, unavoidable overhead associated with any system is the maintenance cost. Standard maintenance procedures usually involve operators checking every single instrument, device or equipment for errors & faults. This procedure, while being effective are very resource-consuming, especially when human resources are better utilized with creative tasks. The solution to this problem is “Condition Based Monitoring & Maintenance”.

A relatively new term, the concept has great potential to bring down maintenance costs and regulation of resources. By using an entire array of sensors along with a data-mining & processing application, a plant can preemptively predict the failure of a device or equipment. This would mean that human operators wouldn’t need to scan through every single device, and would simply rectify the equipment most prone to failure.

In effect, you’ll be integrating the capabilities of modern technologies such as Internet of Things with conventional resources to optimize the working of your plant. This would allow the management to cut down any lagging resources while focusing more on productivity rather than worrying about equipment failure.

Interested in learning more? Speak to one of our experts!

Contact Us