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R. Schiemann et al.
autonomous operation with improved level of equipment monitoring can maximize
availability for a production site
• Sustainability: With environmental regulations becoming increasingly strict,
operators face the challenge of reducing their emissions to avoid financial penalties
• Declining ore grades: Plant operation at its highest efficiency faces greater
challenge with declining ore grades
• Technology push: Digitalization allows information to be made available in real
time, practically anywhere in the world, providing a solid basis for improved
decision-making supported by the experts.
The challenges mentioned above prevail especially in the metallurgical production
sector. Thus, there are many drivers for digital technologies to become more apparent.
It is anticipated that in the future, digitalization and digital technology innovations will play a key role in overcoming challenges in productivity, profitability, and
compliance with environmental regulations. Digital solutions will be able to provide
round-the-clock assistance to the operating personnel, thus facilitating proper processing of lower-grade ore types. As a problem-solution approach featuring relatively
low investment with comparatively large possible benefits, low investment risks and
quick return on investments can be expected.
Know-How and Data as a Source of Information in Digital
Systems
Digital solutions in the industry typically follow either a know-how-based or a databased approach. The two approaches have the common target of exploiting known
information in order to improve operating conditions with respect to profitability,
efficiency, environmental aspects, maintenance, and safety. Despite this common
target, the two methods are vastly different from each other. In this section, the key
differences between them are addressed.
By definition, the primary source of information is very different for the two
approaches. While know-how-based approaches draw their exploitable information
about physical phenomena from a human being’s knowledge and experience, databased approaches rely on evidence of these phenomena in a set of data measured
in the plant. This major methodical distinction gives rise to certain limitations to be
aware of.
Any conclusion drawn from previously acquired data can be due to apparent
correlations present in the data with no underlying causal relationship. This is a real
threat, especially in plant operations, because it can lead to false decisions and hence
to plant maloperation and potentially threatening plant availability. For example, if
the bed temperature of fluidized bed zinc roaster drops due to furnace overfeeding, a
R. Schiemann et al.
autonomous operation with improved level of equipment monitoring can maximize
availability for a production site
• Sustainability: With environmental regulations becoming increasingly strict,
operators face the challenge of reducing their emissions to avoid financial penalties
• Declining ore grades: Plant operation at its highest efficiency faces greater
challenge with declining ore grades
• Technology push: Digitalization allows information to be made available in real
time, practically anywhere in the world, providing a solid basis for improved
decision-making supported by the experts.
The challenges mentioned above prevail especially in the metallurgical production
sector. Thus, there are many drivers for digital technologies to become more apparent.
It is anticipated that in the future, digitalization and digital technology innovations will play a key role in overcoming challenges in productivity, profitability, and
compliance with environmental regulations. Digital solutions will be able to provide
round-the-clock assistance to the operating personnel, thus facilitating proper processing of lower-grade ore types. As a problem-solution approach featuring relatively
low investment with comparatively large possible benefits, low investment risks and
quick return on investments can be expected.
Know-How and Data as a Source of Information in Digital
Systems
Digital solutions in the industry typically follow either a know-how-based or a databased approach. The two approaches have the common target of exploiting known
information in order to improve operating conditions with respect to profitability,
efficiency, environmental aspects, maintenance, and safety. Despite this common
target, the two methods are vastly different from each other. In this section, the key
differences between them are addressed.
By definition, the primary source of information is very different for the two
approaches. While know-how-based approaches draw their exploitable information
about physical phenomena from a human being’s knowledge and experience, databased approaches rely on evidence of these phenomena in a set of data measured
in the plant. This major methodical distinction gives rise to certain limitations to be
aware of.
Any conclusion drawn from previously acquired data can be due to apparent
correlations present in the data with no underlying causal relationship. This is a real
threat, especially in plant operations, because it can lead to false decisions and hence
to plant maloperation and potentially threatening plant availability. For example, if
the bed temperature of fluidized bed zinc roaster drops due to furnace overfeeding, a