Empowering Humans in a Cyber-Physical Production System: Human-in-the-loop Perspective (original) (raw)
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Human workers are envisioned to work alongside robots and other intelligent factory modules, and fulfill supervision tasks in future smart factories. Technological developments, during the last few years, in the field of smart factory automation have introduced the concept of cyber-physical systems, which further expanded to cyber-physical production systems. In this context, the role of collaborative robots is significant and depends largely on the advanced capabilities of collision detection, impedance control, and learning new tasks based on artificial intelligence. The system components, collaborative robots, and humans need to communicate for collective decision-making. This requires processing of shared information keeping in consideration the available knowledge, reasoning, and flexible systems that are resilient to the real-time dynamic changes on the industry floor as well as within the communication and computer network infrastructure. This article presents an ontology-bas...
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Even though full autonomy in Cyber-Physical Systems (CPSs) is a challenge that has been confronted in different application domains and industrial sectors, the current scenario still requires human intervention in these autonomous systems in order to accomplish tasks that are better performed with human-in-the-loop. Humans, machines, and software systems are required to interact and understand each other in order to work together in an effective and robust way. This human integration introduces an important number of challenges and problems to be solved in order to achieve seamless and solid participation. To manage this complexity, appropriate techniques and methods must be used to help CPS developers analyze and design this kind of human-in-the-loop integration. The goal of this paper is to identify the technological challenges and limitations of integrating humans into the CPSs autonomy loop and to break new ground for design solutions in order to develop what we call HiL-ACPS systems. This work defines a conceptual framework to characterize the cooperation between humans and autonomous CPSs and provides techniques for applying the framework in order to design proper human integration. The emergent autonomous car domain is considered as a running example. It covers some of the current limitations of involving drivers into the autonomous functionalities. Finally, to validate the proposal, an autonomous car prototype was built applying the conceptual framework. This prototype was evaluated to check whether the human integration implemented behaves as defined in its specification.
Cooperative Human-Machine Interaction in Industrial Environments
2018 13th APCA International Conference on Control and Soft Computing (CONTROLO), 2018
Despite the existence of various solutions in the industrial domain for cooperation between robots and humans, they tend to focus mainly on safety issues with very few advances in the adaptation of industrial equipment to the characteristics of the operator and his way of working. For several years, adaptation in a human-robot collaboration environment was single sided, as only the operator adapts his working operations facing the robot characteristics, which leads to high levels of stress and fatigue of the human operator. Nowadays, the paradigm is changing towards the adaptation of human operator to industrial equipment and vise versa. The adaptation of a robot to the human is achieved by enabling the machine to learn the physical and psychological characteristics of each operator, in order to create a working profile for each individual. Thus, the main objective is to analyze the relationship between human operators and robots in an industrial environment, and therefore explore human-machine collaboration by correlating sensorial data from all the entities involved in the process. With this in mind, by performing sensor fusion and data analysis representing actions and biometric signals from the human operator, industrial robots will be empowered of self-adaptation capabilities. In this dissertation, an industrial collaborative environment is achieved using a Cyber-Physical Production System (CPPS). This CPPS consists in three main parts, namely sensing and actuating equipment, logical entities called Smart Components and a Cloud infrastructure. Sensing devices are based on biometric sensors-BITalino's ECG and EDA-and a vision system-Kinect-in order to monitor the human operator working profile. A robotic arm is used as actuating device. Each equipment is virtualized into an agent-based representation, based on the Smart Component concept, which communicate sensor data with a Cloud infrastructure responsible for data processing and decision making. Sensor data is analyzed in order to infer levels of stress and fatigue through a fuzzy logic system. Decision making is based on the MAPE-K architecture, enabling the robotic arm self-adaptation. Results from human subject tests are presented here to validate the proposed methodology, proving that the system can detect stress with an accuracy of 77,6% and fatigue with an accuracy of 70%, as well as detect the subject's position and movement with a true positive rate of 70,7%. Facing the movement and levels of stress and fatigue of the human operator, the robotic arm should be able to change autonomously it's task execution, namely speed of its movement and the correct operation according to the habits of the operator. i ii First of all I would like to thank Professor Gil Manuel Gonçalves, my supervisor, for the guidance and follow-up of the work done, for all the suggestions and corrections, and for giving me the basis for this work to be possible. The biggest thanks to Rui Pinto and João Reis, for being the co-supervisors every student hopes for and even more, for guiding me and helping me in every occasion with the greatest patience in the world and doing all that with a good sense of humor. Without you, this dissertation would not be half of what it is.
2019
The 4th industrial revolution (Industry 4.0) heavily relying on the concept of Cyber-Physical Systems (CPS) has transformed the manufacturing industry into an intelligent environment. Advances in manufacturing and automation industries created hyper-connected industrial ecosystems that are not limited to smart production but also facilitate organizational integration. Hence, fostering the creation of collaborative, networked and intelligent industries. One of the emerging advances in the digital transformation of industries is the creation of environments where humans work in close collaboration with sensor enabled smart machines and robots. Particularly the close involvement of humans in such smart environments challenges system designed methodologies mainly because human aspects are not considered in CPS design frameworks. In this paper, we present an approach to support this aspect of Industry 4.0 taking a Cyber-Physical-Social System (CPSS) paradigm to incorporate human aspects with the existing notion of CPS. We propose a meta-model of CPSS that can serve as a framework to design systems involving human and CPS collaboration.
Enabling the human in the loop: Linked data and knowledge in industrial cyber-physical systems
Annual Reviews in Control
Industrial Cyber-Physical Systems have benefitted substantially from the introduction of a range of technology enablers. These include web-based and semantic computing, ubiquitous sensing, internet of things (IoT) with multi-connectivity, advanced computing architectures and digital platforms, coupled with edge or cloud side data management and analytics, and have contributed to shaping up enhanced or new data value chains in manufacturing. While parts of such data flows are increasingly automated, there is now a greater demand for more effectively integrating, rather than eliminating, human cognitive capabilities in the loop of production related processes. Human integration in Cyber-Physical environments can already be digitally supported in various ways. However, incorporating human skills and tangible knowledge requires approaches and technological solutions that facilitate the engagement of personnel within technical systems in ways that take advantage or amplify their cognitive capabilities to achieve more effective sociotechnical systems. After analysing related research, this paper introduces a novel viewpoint for enabling human in the loop engagement linked to cognitive capabilities and highlighting the role of context information management in industrial systems. Furthermore, it presents examples of technology enablers for placing the human in the loop at selected application cases relevant to production environments. Such placement benefits from the joint management of linked maintenance data and knowledge, expands the power of machine learning for asset awareness with embedded event detection, and facilitates IoT-driven analytics for product lifecycle management.
Engineering Human-in-the-Loop Interactions in Cyber-Physical Systems
Information and Software Technology, 2020
Context: Cyber-Physical Systems (CPSs) are gradually and widely introducing autonomous capabilities into everything. However, human participation is required to accomplish tasks that are better performed with humans (often called human-in-the-loop). In this way, human-in-the-loop solutions have the potential to handle complex tasks in unstructured environments, by combining the cognitive skills of humans with autonomous systems behaviors. Objective: The objective of this paper is to provide appropriate techniques and methods to help designers analyze and design human-in-the-loop solutions. These solutions require interactions that engage the human, provide natural and understandable collaboration, and avoid disturbing the human in order to improve human experience. Method: We have analyzed several works that identified different requirements and critical factors that are relevant to the design of human-in-the-loop solutions. Based on these works, we have defined a set of design principles that are used to build our proposal. Fast-prototyping techniques have been applied to simulate the designed human-in-the-loop solutions and validate them. Results: We have identified the technological challenges of designing human-in-the-loop CPSs and have provided a method that helps designers to identify and specify how the human and the system should work together, focusing on the control strategies and interactions required. Conclusions: The use of our approach facilitates the design of human-in-the-loop solutions. Our method is practical at earlier stages of the software life cycle since it allows domain experts to focus on the problem and not on the solution.
Towards human-centered cyber-physical systems
2016
In this paper we present a new CPS model that considers humans as holistic beings, where mind and body operate as a whole and characteristics like creativity and empathy emerge. These characteristics influence the way humans interact and collaborate with technical systems. Our vision is to integrate humans as holistic beings within CPS in order to move towards a humanmachine symbiosis. This paper outlines a model for human-centered cyber-physical systems (HCPSs) that is based on our holistic system model URANOS. The model integrates human skills and values to make them accessible to the technical system, similarly to the way they are accessible to humans in human-to-human interaction. The goal is to reinforce the human being in his feeling of being in control of his life experience in a world of smart technologies. It could also help to reduce human bio-costs like stress, job fears, etc. The proposed model is illustrated by the case study of smart industrial machines, dedicated machines for smart factories, where we test the human integration through conversation.