The unicist ontology of automation implies a process that integrates systemic, operational and cognitive objects with quality assurance through automated processes or human control.

There are four different segments of automation: manual, semi-automated, automated and adaptive.

The ontology of automation and its segments will be described in conceptual terms.

Manual

Manual implies that the process is conditioned by the instruction individuals receive to develop their tasks.

The manual process implies that the operator makes the necessary controls and decisions to define if a process continues or not.

Manual processes are usually sustained by a strict “procedures handbook” to maximize the automation of human behavior to ensure the quality assurance process.

Semi-automated

It is a manual process that integrates automation with a high level of human participation in the work processes.

Human intervention occurs in pre-planned intermediate stages to define if the fulfillment of the stages is accepted as valid or invalid.

Semi-automatic includes strict manual operational control processes.

Automated

It implies a systemic automation process including automated quality assurance of the system.

It is based on maximizing efficiency to sustain effectiveness. It limits the role of efficacy to the system design.

The quality assurance is defined by the operational redundancies and the self-exclusion mechanisms of the system in case problems cannot be corrected using redundancies.

Adaptive

An adaptive automation works with the feedback of reality to manage the changes of the system.

It implies an intelligent automation that rules the functionality of the objectives to be achieved.

It includes redundancy and self-exclusion mechanisms to ensure quality.

But its intelligent process is based on its capacity to modify the system to deal with the environment.

The Architecture of Automation

The architecture of automation defines the structures of conceptual engineering. It can also be defined by the conceptual design of the automation system.

In operational terms, the architecture of automation is integrated by systemic objects that transform energy, operational objects that seek to generate value and robots that automate the work processes to optimize the energetic algorithm.

The objective of an automation process is the generation of value to be added to the participants of a “system”.

The transformation of the energy is sustained by a knowledge bank and a quality assurance model.

It is a system that learns from the feedback to improve the work processes while it is included in robots and systemic objects.

The knowledge banks that sustain the operation are generated by the members of the system. Therefore, the system is closed although it is open if the energy equation is considered.

Robotics

When talking about robotics we are using the word in its universal meaning including industrial, virtual, home o whatever the function of a robot might be.

Robotics uses a system that allows introducing information of reality, introducing conceptual operational structures to modify the knowledge the system has, making decisions and dealing with the feedback from reality.

The objective of a robot is to develop a work. This work needs to generate value with quality assurance which defines robots as paradigmatic objects.

Objects have a concept that is implicit in their function to generate value, working within the limits of their quality assurance.

When talking about third or fourth generation robots, they include a methodology that allows learning and operating based on pre-established controls and learning processes.

Quality Assurance

Robots need to have a quality assurance system with a redundant method to ensure their operation.

It is necessary then to have a self-excluding system to deactivate the robot when its work exceeds the operational parameters established to achieve its objective.

The redundant method has to be fully reliable and needs to trigger a self-exclusion automatism when redundancy cannot fulfill the working standards.

Classification of Robots:

First generation robots

They are robots with predefined operations that can only be reprogrammed by changing their hardware.

By definition a first generation robot has rigid parameters and quality assurance systems based on its exclusion when the operational limits are exceeded.

Second generation robots

They are robots that produce predefined operations but they can be reprogrammed changing their software.

They have the possibility of having quality assurance systems to generate operational alerts to adjust their functionality based on the feedback of their system and not only their operation. Second generation robots are “slaves” with inflexible programs to obtain fixed results based on the knowledge introduced by human programming.

Third generation robots

They are robots that have a learning capacity based on the measurement of the results produced. Based on this feedback they regulate the energy they use according to the power needed for each activity.

Learning is based on the restricted context they work with. Their learning systems will become improved based on the evolution of information technology.

Fourth generation robots

They are those robots that are able to integrate in an interdependent way with the context they work in. They have the capacity to learn from their own operational experience and from the feedback coming from other interrelated systems.

They develop a learning process based on the feedback to generate simulations until the knowledge is integrated in their system to generate a reliable operation.

Conclusion

The function of robots is to work and generate value. That is why they are homologous to human work. Each generation of robots develops work in a different way.