Experience with Digital Process Optimization of Zinc Roasting …
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increased water injection into the furnace in case of too high temperatures. Such simple operating instructions often lack proper consideration of cross-effects as well as
mid-term anticipation of operating effects. It does not serve necessary control requirements of today’s roasters which have undergone substantial technical evolution since
large-scale roasting technology adoption in the last decades.
The simple roasting concept of the past has become increasingly complicated with
a much wider variation of operating parameters. This necessitates advanced expert
systems combined with multivariable optimization to achieve desirable operating
conditions. It is apparent that a high number of process parameters must be taken
into consideration at once in order to achieve a desirable roaster operation. This is
a complex task that human operators cannot easily achieve. Modern optimization
systems connected to a traditional DCS can fulfill many of the control room operator
tasks, freeing up mental resources to shift operator focus from the simple monitoring
of the process more towards process analysis and emergency prevention. Additionally, digitized process know-how integrated in such systems can support operators in
their decision-making process and continuously make situation-dependent operating
decisions to improve stability, availability, and profitability of roasting plants.
If carried out appropriately, such optimizations can yield very desirable results
such as:
• Improved operational safety for human beings,
• Protection of downstream equipment, reducing the need for maintenance,
• Enhanced environmental performance due to in-spec operating windows,
• Increased throughput, pushing the plant to its limits,
• Improved and homogenized product quality by process stabilization.
Digital Evolutions in the Process Industry
In recent years, more digital approaches can be observed in the minerals processing industry. A general target of such approaches is optimization of process plant
performance.
More operating data of processes and equipment are collected than ever before.
Accordingly, a need for analysis and leverage approaches and tools arises. Intelligent
monitoring and analysis systems can open up the field for a wide range of advanced
control and optimization approaches.
Usually, the following drivers for digitalization can be observed [1]:
• Investment risk avoidance: Debottlenecking plant sections and equipment to
achieve maximum impact on performance with lowest risk involved
• Productivity challenge: Customer focus on optimizing the operation of existing
equipment and maximizing profits without high investment costs
• Shortage of skilled labor: Many production sites are in remote locations, making them an unattractive working place for operating personnel. Thus, a more
379
increased water injection into the furnace in case of too high temperatures. Such simple operating instructions often lack proper consideration of cross-effects as well as
mid-term anticipation of operating effects. It does not serve necessary control requirements of today’s roasters which have undergone substantial technical evolution since
large-scale roasting technology adoption in the last decades.
The simple roasting concept of the past has become increasingly complicated with
a much wider variation of operating parameters. This necessitates advanced expert
systems combined with multivariable optimization to achieve desirable operating
conditions. It is apparent that a high number of process parameters must be taken
into consideration at once in order to achieve a desirable roaster operation. This is
a complex task that human operators cannot easily achieve. Modern optimization
systems connected to a traditional DCS can fulfill many of the control room operator
tasks, freeing up mental resources to shift operator focus from the simple monitoring
of the process more towards process analysis and emergency prevention. Additionally, digitized process know-how integrated in such systems can support operators in
their decision-making process and continuously make situation-dependent operating
decisions to improve stability, availability, and profitability of roasting plants.
If carried out appropriately, such optimizations can yield very desirable results
such as:
• Improved operational safety for human beings,
• Protection of downstream equipment, reducing the need for maintenance,
• Enhanced environmental performance due to in-spec operating windows,
• Increased throughput, pushing the plant to its limits,
• Improved and homogenized product quality by process stabilization.
Digital Evolutions in the Process Industry
In recent years, more digital approaches can be observed in the minerals processing industry. A general target of such approaches is optimization of process plant
performance.
More operating data of processes and equipment are collected than ever before.
Accordingly, a need for analysis and leverage approaches and tools arises. Intelligent
monitoring and analysis systems can open up the field for a wide range of advanced
control and optimization approaches.
Usually, the following drivers for digitalization can be observed [1]:
• Investment risk avoidance: Debottlenecking plant sections and equipment to
achieve maximum impact on performance with lowest risk involved
• Productivity challenge: Customer focus on optimizing the operation of existing
equipment and maximizing profits without high investment costs
• Shortage of skilled labor: Many production sites are in remote locations, making them an unattractive working place for operating personnel. Thus, a more