Reducing quality, throughput, emissions & energy losses with automated root cause analysis
Case study: Cement manufacturing
Download the case study
Reducing quality, throughput, emissions & energy losses with automated root cause analysis
Download the case study
Case study: Cement manufacturing
The Challenge:
Achieving kiln stability & optimization
Most cement manufacturers face regular production losses in quality, throughput, emissions and energy efficiency. Very often, the causes of these losses are driven by inefficiencies in the production process itself – and much of the time, these inefficiencies are related to the kiln.
Stabilizing & optimizing the kiln can reduce losses such as:
Interestingly, the kiln does sometimes achieve higher-than-average efficiency rates, so the potential for improvement is already there.
The question is: how can they increase the amount of time the kiln is operating at those levels? This, of course, can only be achieved by reducing the process inefficiencies that prevent the kiln from reaching that target range.
But the production processes related to the kiln are dynamic and complex, and each day is a new struggle to maintain the kiln at acceptable levels. Even with a team of experienced process engineers, equipped with analytics tools, finding the true root cause of kiln instability is extremely difficult.
The Challenge:
Achieving kiln stability & optimization
Most cement manufacturers face regular production losses in quality, throughput, emissions and energy efficiency. Very often, the causes of these losses are driven by inefficiencies in the production process itself – and much of the time, these inefficiencies are related to the kiln.
Stabilizing & optimizing the kiln can reduce losses such as:
Interestingly, the kiln does sometimes achieve higher-than-average efficiency rates, so the potential for improvement is already there.
The question is: how can they increase the amount of time the kiln is operating at those levels? This, of course, can only be achieved by reducing the process inefficiencies that prevent the kiln from reaching that target range.
But the production processes related to the kiln are dynamic and complex, and each day is a new struggle to maintain the kiln at acceptable levels. Even with a team of experienced process engineers, equipped with analytics tools, finding the true root cause of kiln instability is extremely difficult.
The Solution:
Identifying & preventing the hidden causes of process-driven losses
The Seebo solution enables process experts to identify the hidden causes of their production losses, and gain clear recommendations as to how to prevent those process inefficiencies.
Furthermore, production teams receive real-time alerts as soon as those inefficiencies are detected – enabling them to prevent losses before they occur.
The process inefficiencies Seebo identifies are often invisible to the human eye, in part because they are caused by a complex combination of behaviors among the hundreds or thousands of interrelated data tags on the line.
In this case, the Seebo solution discovered that when the Cyclone material temperature is above 800°, and at the same time the Kiln oxygen level was between 1.5% and 2%, the likelihood of a problem with the Kiln AMP increased very significantly.
(Read the full case study for more interesting findings).
This is a hugely important insight that the process experts could never have figured out on their own since both of those tags remained within the permitted range. It was only the unique combination of those two specific ranges of tag values that was causing the losses.
The Solution:
Identifying & preventing the hidden causes of process-driven losses
The Seebo solution enables process experts to identify the hidden causes of their production losses, and gain clear recommendations as to how to prevent those process inefficiencies.
Furthermore, production teams receive real-time alerts as soon as those inefficiencies are detected – enabling them to prevent losses before they occur.
The process inefficiencies Seebo identifies are often invisible to the human eye, in part because they are caused by a complex combination of behaviors among the hundreds or thousands of interrelated data tags on the line.
In this case, the Seebo solution discovered that when the Cyclone material temperature is above 800°, and at the same time the Kiln oxygen level was between 1.5% and 2%, the likelihood of a problem with the Kiln AMP increased very significantly.
(Read the full case study for more interesting findings).
This is a hugely important insight that the process experts could never have figured out on their own, since both of those tags remained within the permitted range. It was only the unique combination of those two specific ranges of tag values that was causing the losses.
The Result:
4.2% increase in clinker quality + 3.3% increase in kiln feed capacity =
5.6% reduction in energy cost per ton of clinker =
Greater kiln stability =
$780K
Extra profit on single line
$521K
In energy savings on a single line
11.9%
Lower NOx emissions
The Result:
4.2% increase in clinker quality + 3.3% increase in kiln feed capacity =
$780K
extra profit on a single line
5.6% reduction in energy cost per ton of clinker =
$521K
in energy savings on a single line
Greater kiln stability =
11.9%
lower NOx emissions
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