If I know what’s available, I can see what’s still missing for improvement.



The metals industry is characterized by a huge difference in the degree of automation and digitalization. Before thinking about “the perfect solution” or even about Industry 4.0 and the different possibilities of this technology, the evaluation of the as-is situation must be the starting point of every digitalization project.

In the metals industry, a frequently used approach for determining the actual state of the automation degree is based on the following systematization levels in the table below.

For more information see an excellent publication about “Levels of Automation in Manufacturing” (read more). The publication summarizes the different level of automation concepts and suggested a new definition and taxonomy to be used in manufacturing.

Data collectionRecording data as they occur – documents (reports) will be generated at some later time.
Event reportingCapturing information as events occur – documents are produced when and where required.
TrackingA continuous profile of event information for a series of operations or movements.
MonitoringDynamically comparing actual events to those planned. Alert messages are produced.
GuideProviding action alternatives, and capturing the course of action carried out.
ControlExecuting a control action when predefined event conditions occur.

State-of-the-art software integration must consider these six levels of systemization.

However, to go one step further, it is necessary to divide activities into physical and cognitive tasks, taking into account the cooperation between humans and technology.

A new and more holistic approach according to J. Frohm et al considers the distribution of tasks as two independent reference scales that refer to the two types of degree of automation. Each of these tasks can then be analyzed in seven steps, from manual control to fully automatic control:

Mechanical and Equipment



Totally manual
Completely manual work, no tools are used, only the muscle power of the operator is used.


Static hand tool
Manual work with support of static tool (e.g., adding material with shovel).


Flexible hand tool
Manual work supported by flexible tool (e.g., adjustable wrench).


Automated hand tool
Manual work with the support of automated tools.


Static machine / workstation
Automatic work by machine designed for a specific task.


Flexible machine / workstation
Automatic work by machine that can be reconfigured for different tasks.


Totally automatic
Completely automatic working, the machine solves any occurring deviations or problems by itself (e.g., autonomous systems).

Information and Control



Totally manual
The operator creates his own understanding of the situation and further develops his approach based on his previous experience and knowledge.


Decision Making
The operator is provided with information about what to do or suggestions on how to accomplish the tasks.


The user receives instructions on how to accomplish the task (e.g., checklists, manuals).


The technology question the execution, if the execution deviate from what the technology considers being suitable (e.g., verification before action).


The technology calls for the attention of the operator (user),
and gives suggestions for activities to be performed (e.g., alarm, warning).


The technology takes over and corrects its own actions when execution deviates from what the technology considered appropriate.


Totally automatic
All information and control are taken over by technology. The user / operator is no longer involved.


The advantage of using this approach over other analysis methods or classifications is that both the level of physical and cognitive support can be assessed. Since the two reference scales are independent of each other, the degree of automation of the equipment and the information control for physical and cognitive support can vary according to the needs of the individual. By using this approach as the basis for a measurement methodology, the potential of technology and automation in various types of human / machine systems can be estimated.



Based on our expertise and experience in combination with state-of-the-art procedure models describe above we offer to evaluate and describe the as-is situation. The result of this evaluation and analysis enables a much more efficient way to identify potential improvements. Additionally, it is the starting point of developing the big picture of a value adding software.

  • Evaluation of the current situation (as-is analysis)
  • Documentation of the degree of automation and digitalization
  • Recommendations of potential improvements and investments





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