Purpose of Review This paper provides an overview of the role of humans and robots in smart factories, their connection to Industry 4.0, and which progress they make when it comes to related technologies. Recent Findings The current study shows that a decade was not enough to provide a reference implementation or application of Industry 4.0, like smart factories. In 2011, Industry 4.0 was mentioned for the first time in the scientific community. Industry 4.0 arrived with many new enabling technologies and buzzwords, e.g., Internet of Things (IoT), Cyber-Physical Systems (CPS), and Digital Twins (DT). Summary This paper first defines smart factories and smart manufacturing in relation to the role of humans and robots. Followed by an overview of selected technologies in smart factories. Concluded by future prospects and its' relation to smart manufacturing.

Collaborative Robots provide many possibilities, when it comes to Human-Robot Collaboration. Until now, these approaches are usually custom made, sensor-integrated solutions, where the robot's safety controller ensures the safety of the human worker. These solutions are according to today's rules and standards. We propose to extend these solutions with including Virtual Realty as a sensor and to provide comfort features to the operator. In order to create cooperation between human and industrial robot in our experiments, we propose to have a simple nut screwing operation as an example, where the industrial robot does the hard part. With sharing the task in such manner, we will ensure that the robot is doing the hard and monotonous work, while the worker benefits from the task sharing. Results are demonstrated through simulation and in reality also.

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The paper presents a complete multimedia educational program of DC servo drive for distant learning. The program contains three parts: animation, simulation and internet-based measurement. The animation program gives the operation of DC motors as well as its time-and frequency-domain equations, transfer functions and the theoretical background necessary to design a controller for DC servo motors. The simulation model of the DC servo motor and the controller can be designed by the students based on the animation program. The students can also test their controllers by the internet based measurement, which is the most important part from engineering point of view. The exercises the students can do are programming the D/A and A/D cards of the embedded system and to design different types of controllers. First, a simple PI controller can be designed, but advanced students can also design more sophisticated controllers such as the sliding mode controller. After the measurement is executed, the students can download the measured data and compare them to the simulation results.

The current and most important request for industrial automation is from Small and Mediumsized Enterprisess (SMEs). This is due to the fact that the SMEs need to increase their competitiveness to withstand the trend of outsourcing to low-cost countries. However, there are good examples of the strong competitiveness of the European SMEs, when they are able to utilize industrial automation for repetitive work, while utilizing the human labor for tasks requiring human skills, like sensing, flexibility, and cognitive skills. The Intelligent Factory Space (IFS) concept represents a framework for interaction between human and an automated system (digital factory). The IFS is composed of multiple layers (representing different services for the human user) and many modular components, which can be extended to the users' requirements. The IFS relies on industrial standards to communicate with existing machines while using novel two-way communication possibilities to feedback to the human user. In this paper, the general concept for the IFS is presented along with a reference implementation, where the concept is implemented in the situation of the human-robot collaboration.INDEX TERMS Cyber-physical systems, industrial cyber-physical systems, flexible manufacturing systems, intelligent shopfloor, connectivity, interoperability.

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Driven by the need for higher -flexibility and -speed during initial programming and path adjustments, new robot programming methodologies quickly arises. The traditional "Teach" and "Offline" programming methodologies have distinct weaknesses in machining applications. "Teach" programming is time consuming when used on freeform surfaces or in areas with limited visibility /accessibility. Also, "Teach" programming only relates to the real work-piece and there is no connection to the ideal CAD model of the work-piece. Vice versa during offline programming there is no knowledge about the real work-piece, only the ideal CAD model is used. To be able to relate to both the real-and ideal-model of the work-piece is especially important in machining operations where the difference between the models often represents the necessary material removal . In this chapter an introduction to a programming methodology especially targeted for machining applications is given. This methodology use a single camera combined with image processing algorithms like edge-and colour-detection, combines information of the real and ideal work-piece and represents a human friendly and effective approach for robot programming in machining operations.

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