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.

Today, in production engineering we have already taken into usage complex virtual representations of the manufacturing environment were we can program, simulate, analyse and optimise key performances. Such systems are mainly working through keyboard/ mouse input while user feedback normally are direct visual through computer screen and text files. Such communication only relays on a limited spectre of our senses and the keyboard/mouse/screen systems cannot be said to be very human friendly, especially when the operator is expected to operate ldquoout of officerdquo in a unstructured, maybe dangerous or dirty, environment. In the near future we expect to see more advanced input/output devices like motion capturing and speech input systems while feedback will not be visual alone but include several other human senses. Combinatorial sensory information, interpreted by the human brain, becomes very handy when a stand alone sense is not enough to interpret the actual situation. Imitation of senses and feedback from virtual reality environments always meant a great problem. Realization of two (sight and hearing) out of the five human senses is indispensable. Simulation of these two senses is not complex issue; on the contrary the other three are quite challenging. This paper describes the development of a vibro-tactile glove which can provide sensory feedback from a virtual environment, either as a stand alone system but most important in combination with sight and audio feedback systems. Instead of implementing real force feedback, the focus is on tactile sensing, as an alternative way of achieving the same feedback. The glove contains six vibration motors on different locations on the hand. These locations include all five fingers, and the palm. Communication with the glove is wireless, enabling free movement for the user. The system is low cost and very small sized which allows for combining it with advanced input devices like a motion capturing suit.

This paper presents our experience with a complete multimedia educational program of dc servo drives for distant learning. The program contains three parts: animation, simulation, and Internet-based measurement. The animation program helps to understand 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 through the Internet-based measurement, which is the most important part from an engineering point of view. Students can then perform various exercises such as programming the D/A and A/D cards in the embedded system and designing 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 measurements are 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 Medium sized Enterprisess (SMEs). This is due to the fact that 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 European SMEs, when they are able to utilize industrial automation for repetitive work, while utilizing human labour 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. 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 IFS is presented along with a reference implementation, where the concept is implemented in the situation of human-robot collaboration.

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.

Programming of industrial robots is normally carried out via so-called "Teach" or "Offline" programming methodologies. Both methodologies have associated weaknesses like a high time consumption for programming on sculptured surfaces (especially "Teach"), and both methodologies cannot, at the same time, carry information of the real work piece and the ideal work piece (CAD-model). To be able to see both the real and ideal world is especially important when the industrial robot is used in manufacturing processes like machining, grinding, deburring etc. where the difference between the real and ideal world represents the material removal. This paper presents a new vision based programming methodology which combines information of the real and ideal world, especially adapted for robot grinding and deburring operations. Further, the presented methodology is especially developed with simplicity in mind when it comes to man-machine communication. Thus, a standard marker pen can be used by the operator to draw the robot path directly onto the work piece. This line is captured by a vision system and finally leads to the generation of the robot path. The presented methodology is a further development of the previous work of the authors as presented (Solvang et al., 2007 and Sziebig, 2007), especially concerning optimization of the robot tool positioning with respect to a work piece surface.