Case study: Chemicals manufacturing

Increasing yield while reducing energy costs & emissions

Increasing yield while reducing energy costs & emissions

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Slide Increase ethylene yield
from 30% to 32%
Increase Naphtha
feed rate from
83 to 86 ton per hour
Reduce energy
costs by 1.7%
Reduce CO2
emissions by 1.54%
Greater
understanding of the
production process
Over €5 million
savings & extra profit
on a single line

The Challenge - conflicting KPIs 

Increasing yield while decreasing energy costs & emissions - mission impossible?

Like many chemical manufacturing plants, the team at this ethylene plant grappled with a number of conflicting objectives across their production process. From balancing their different yield targets to complying with emissions reduction targets and cutting energy costs.

These objectives were made particularly difficult not only by their conflicting relationships (e.g. increasing yield vs. reducing energy costs) but also by the highly dynamic external factors that had to be taken into consideration – from shifting market demands, to ever-rising energy prices and increasingly stringent emissions regulations.

To achieve global optimization across all their objectives, their team turned to Seebo. 

After connecting to the process data, the Seebo solution created a digital model of the entire production process. This enabled Seebo’s Process-Based Artificial Intelligence™ algorithms to understand the intricacies of their process and draw accurate insights from their data.

The decision was made to focus on the Naphtha steam cracker, and within just a few months of implementing the Seebo solution the team had stabilized their process and hit all their objectives – and in some cases even exceeded them.

Here’s how they did it…


The Challenge - conflicting KPIs 

Increasing yield while decreasing energy costs & emissions - mission impossible?

Like many chemical manufacturing plants, the team at this ethylene plant grappled with a number of conflicting objectives across their production process. From balancing their different yield targets to complying with emissions reduction targets and cutting energy costs.

These objectives were made particularly difficult not only by their conflicting relationships (e.g. increasing yield vs. reducing energy costs) but also by the highly dynamic external factors that had to be taken into consideration – from shifting market demands, to ever-rising energy prices and increasingly stringent emissions regulations.

To achieve global optimization across all their objectives, their team turned to Seebo. 

After connecting to the process data, the Seebo solution created a digital model of the entire production process. This enabled Seebo’s Process-Based Artificial Intelligence™ algorithms to understand the intricacies of their process and draw accurate insights from their data.

The decision was made to focus on the Naphtha steam cracker, and within just a few months of implementing the Seebo solution the team had stabilized their process and hit all their objectives – and in some cases even exceeded them.

Here’s how they did it…


Multidimensional Objective Model

Optimize multiple, conflicting objectives

One of the first things the Seebo solution did was to identify a multidimensional objective. This is a unified view of efficiency, which takes into account all the objectives and constraints on their process – and adapts in real-time to changes, both within the process itself and including external factors like weather conditions, raw material variances, and emissions regulations.


Multidimensional Objective Model

Optimize multiple, conflicting objectives

One of the first things the Seebo solution did was to identify a multidimensional objective. This is a unified view of efficiency, which takes into account all the objectives and constraints on their process – and adapts in real-time to changes, both within the process itself and including external factors like weather conditions, raw material variances, and emissions regulations.


Process Potential Identifier

Quantifying untapped potential within their process

Using Seebo’s multidimensional objective, their process experts continuously gain new insights into the untapped potential of the process, via a real-time view of their overall efficiency. 

With this unified view, they can now clearly see when their production process was operating more or less efficiently than average.

As with many plants, often the causes of higher or lower efficiency are already obvious. For example: seasonal changes, scheduled or unscheduled downtime, and so on. 

But using the Seebo solution, their process experts found that for 32% of the time their line was out-performing their average efficiency levels across all objectives, with no clear explanation – including higher yield and Naphtha feed rates, and lower emissions and energy costs!

This proved that there was a real potential for improvement. The challenge was – how could they best replicate the conditions that led to higher efficiency?


Process Potential Identifier

Quantifying untapped potential within their process

Using Seebo’s multidimensional objective, their process experts continuously gain new insights into the untapped potential of the process, via a real-time view of their overall efficiency. 

With this unified view, they can now clearly see when their production process was operating more or less efficiently than average.

As with many plants, often the causes of higher or lower efficiency are already obvious. For example: seasonal changes, scheduled or unscheduled downtime, and so on. 

But using the Seebo solution, their process experts found that for 32% of the time their line was out-performing their average efficiency levels across all objectives, with no clear explanation – including higher yield and Naphtha feed rates, and lower emissions and energy costs!

This proved that there was a real potential for improvement. The challenge was – how could they best replicate the conditions that led to higher efficiency?



Operating Envelope

Identifying the most important process parameters - and their optimal ranges

Next, the Seebo solution built an Operating Envelope, which detailed the precise process ranges and set points that would optimize all their objectives at any given time. 

Specifically:

  • Increase ethylene yield from 30% to 32%
  • Increase propylene yield from 14.5% to 16%
  • Increase Naphtha feed rate from 83 to 86 ton per hour

While at the same time:

  • Reduce energy costs by 1.7%
  • Reduce CO2 emissions by 1.54% (with existing fossil fuels and processes)

Seebo also revealed another surprising fact to the manufacturing team. Their process was already achieving or exceeding this envelope 17% of the time! This meant that the new Operating Envelope was even more realistic than they had imagined since their production process was clearly capable of it.

Crucially, this envelope is dynamic, so it can adapt to changing circumstances or objectives (e.g. new yield targets, higher energy costs, etc). The team also has the option to create multiple operating envelopes to cover different common scenarios vis-a-vis their objectives and processes.

The next challenge was to ensure that the process would remain within that envelope more often…


Operating Envelope

Identifying the most important process parameters - and their optimal ranges

Next, the Seebo solution built an Operating Envelope, which detailed the precise process ranges and set points that would optimize all their objectives at any given time. 

Specifically:

  • Increase ethylene yield from 30% to 32%
  • Increase propylene yield from 14.5% to 16%
  • Increase Naphtha feed rate from 83 to 86 ton per hour

While at the same time:

  • Reduce energy costs by 1.7%
  • Reduce CO2 emissions by 1.54% (with existing fossil fuels and processes)

Seebo also revealed another surprising fact to the manufacturing team. Their process was already achieving or exceeding this envelope 17% of the time! This meant that the new Operating Envelope was even more realistic than they had imagined since their production process was clearly capable of it.

Crucially, this envelope is dynamic, so it can adapt to changing circumstances or objectives (e.g. new yield targets, higher energy costs, etc). The team also has the option to create multiple operating envelopes to cover different common scenarios vis-a-vis their objectives and processes.

The next challenge was to ensure that the process would remain within that envelope more often…


Proactive alerts

Empower operators to prevent inefficiencies before they happen - with actionable AI

To ensure these ideal conditions are maintained across the process, the process experts then created Proactive Alerts, so the production team knows as soon as the process strays from the operating envelope, and what process parameter or parameters caused that to happen. 

Each Proactive Alert includes Standard Operating Procedures created by the manufacturing team, instructing operators on the precise adjustments and actions they must take to prevent inefficiencies.

This means operators know precisely how, where and when to act to prevent inefficiencies and continuously maintain the optimal process settings, even under dynamic conditions.


Proactive alerts

Empower operators to prevent inefficiencies before they happen - with actionable AI

To ensure these ideal conditions are maintained across the process, the process experts then created Proactive Alerts, so the production team knows as soon as the process strays from the operating envelope, and what process parameter or parameters caused that to happen. 

Each Proactive Alert includes Standard Operating Procedures created by the manufacturing team, instructing operators on the precise adjustments and actions they must take to prevent inefficiencies.

This means operators know precisely how, where and when to act to prevent inefficiencies and continuously maintain the optimal process settings, even under dynamic conditions.


Continuous improvement & process stability

Hitting their initial goals was one thing, but the ultimate aim is for continuous improvement in a highly dynamic environment, marketplace and world – not a one-time benefit. 

To meet this need, Seebo’s Process-Based AI continuously monitors the process and adapts to any changes that occur – both within the process itself, as well as outside factors.

In addition, the process experts can use Seebo’s Impact Analysis tool to monitor how changes to the process as a result of Seebo’s recommendations impact its performance over time. This enables them to refine their existing Proactive Alerts and add new ones, as well as to adjust their production objectives and constraints as appropriate.


Continuous improvement & process stability

Hitting their initial goals was one thing, but the ultimate aim is for continuous improvement in a highly dynamic environment, marketplace and world – not a one-time benefit. 

To meet this need, Seebo’s Process-Based AI continuously monitors the process and adapts to any changes that occur – both within the process itself, as well as outside factors.

In addition, the process experts can use Seebo’s Impact Analysis tool to monitor how changes to the process as a result of Seebo’s recommendations impact its performance over time. This enables them to refine their existing Proactive Alerts and add new ones, as well as to adjust their production objectives and constraints as appropriate.


The Result - Higher yield, lower energy costs & emissions 

2% higher throughput & 3.5% emissions reduction

Using the Seebo solution, the plant team was able to consistently hit all their objectives, and even surpass some of them:

  • Increase ethylene yield from 30% to 32%
  • Increase propylene yield from 14.5% to 16%
  • Increase Naphtha feed rate from 83 to 86 ton per hour
  • Reduce CO2 emissions by 1.54% (with existing fossil fuels and process)
  • They also exceeded their 1% energy efficiency target, successfully reducing energy costs by 1.7%

In total, the extra annual profits and energy savings added up to over €5 Million for this single process – all while significantly reducing their emissions levels.

The Result - Higher yield, lower energy costs & emissions 

2% higher throughput & 3.5% emissions reduction

Using the Seebo solution, the plant team was able to consistently hit all their objectives, and even surpass some of them:

  • Increase ethylene yield from 30% to 32%
  • Increase propylene yield from 14.5% to 16%
  • Increase Naphtha feed rate from 83 to 86 ton per hour
  • Reduce CO2 emissions by 1.54% (with existing fossil fuels and process)
  • They also exceeded their 1% energy efficiency target, successfully reducing energy costs by 1.7%

In total, the extra annual profits and energy savings added up to over €5 Million for this single process – all while significantly reducing their emissions levels.

Empower your teams to unlock the full potential of your process.

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