Trusted Artificial Intelligence in Manufacturing; Trusted Artificial Intelligence in Manufacturing

The successful deployment of AI solutions in manufacturing environments hinges on their security, safety and reliability which becomes more challenging in settings where multiple AI systems (e.g., industrial robots, robotic cells, Deep Neural Networks (DNNs)) interact as atomic systems and with humans. To guarantee the safe and reliable operation of AI systems in the shopfloor, there is a need to address many challenges in the scope of complex, heterogeneous, dynamic and unpredictable environments. Specifically, data reliability, human machine interaction, security, transparency and explainability challenges need to be addressed at the same time. Recent advances in AI research (e.g., in deep neural networks security and explainable AI (XAI) systems), coupled with novel research outcomes in the formal specification and verification of AI systems provide a sound basis for safe and reliable AI deployments in production lines. Moreover, the legal and regulatory dimension of safe and reliable AI solutions in production lines must be considered as well. To address some of the above listed challenges, fifteen European Organizations collaborate in the scope of the STAR project, a research initiative funded by the European Commission in the scope of its H2020 program (Grant Agreement Number: 956573). STAR researches, develops, and validates novel technologies that enable AI systems to acquire knowledge in order to take timely and safe decisions in dynamic and unpredictable environments. Moreover, the project researches and delivers approaches that enable AI systems to confront sophisticated adversaries and to remain robust against security attacks. This book is co-authored by the STAR consortium members and provides a review of technologies, techniques and systems for trusted, ethical, and secure AI in manufacturing. The different chapters of the book cover systems and technologies for industrial data reliability, responsible and transparent artificial intelligence systems, human centered manufacturing systems such as human-centred digital twins, cyber-defence in AI systems, simulated reality systems, human robot collaboration systems, as well as automated mobile robots for manufacturing environments. A variety of cutting-edge AI technologies are employed by these systems including deep neural networks, reinforcement learning systems, and explainable artificial intelligence systems. Furthermore, relevant standards and applicable regulations are discussed. Beyond reviewing state of the art standards and technologies, the book illustrates how the STAR research goes beyond the state of the art, towards enabling and showcasing human-centred technologies in production lines. Emphasis is put on dynamic human in the loop scenarios, where ethical, transparent, and trusted AI systems co-exist with human workers. The book is made available as an open access publication, which could make it broadly and freely available to the AI and smart manufacturing communities

Improvement of Continuous Integration Workflow with User Research

In a fast-paced, continuously changing IT industry, it is important for organizations to deliver their products both quickly and with high quality. Continuous practices help achieve that. Specifically, Continuous Integration (CI) aims at submitting code frequently and consistently, checking every new piece of code with automated tests. Therefore, software malfunctions are caught early. At the same time, improper implementation of CI can hinder the development process. Thus, a proper CI assessment is required. The work utilizes a survey to gather employee feedback regarding CI, and then analyzes it with a thematic matrix. Even though employees' general attitude towards CI is positive, they highlight its instability, slowness, lack of documentation, and unclear error messages, among other findings. Additionally, the study revealed deep-rooted issues like shortage of employees and no communication channel between developers and the CI team. In the end, we produced a CI improvement plan with a list of tasks to implement to achieve user goals of the employees

Human Machine Interaction

In this book, the reader will find a set of papers divided into two sections. The first section presents different proposals focused on the human-machine interaction development process. The second section is devoted to different aspects of interaction, with a special emphasis on the physical interaction

Performance Analysis of a Cooperative Search Algorithm for Multiple Unmanned Aerial Vehicles under Limited Communication Conditions

This research investigates the impacts of realistic wireless communications upon a group of unmanned aerial vehicles (UAVs) utilizing a distributed search algorithm. The UAVs are used to survey an area for mobile targets and they require communication to cooperatively locate the targets. The mobile targets do not continually radiate energy, which exacerbates the search effort; a UAV could fly directly over a target and not detect it. A simulation of cooperative UAVs is implemented using the OPNET Modeler network simulation tool. The search performance of a group of UAVs is observed when communication range, data rate, and the number of UAVs are varied. The performance is evaluated based on the total time it takes for the UAVs to completely detect all the targets in a given search area, the number of times internal areas are scanned, the amount of communication throughput achieved, the network traffic generated, network latency, and number of network collisions. The results indicate that the number of UAVs was found to have the greatest impact on the group\u27s ability to search an area, implying that the data shared between the UAVs provides little benefit to the search algorithm. In addition, it was found that a network with a 100 Kbps or faster data rate should allow for minimal congestion and a large degree of scalability. The findings demonstrate that the proposed four-stage search algorithm should operate reasonably well under realistic conditions

Toward Super-Creativity

What is super creativity? From the simple creation of a meal to the most sophisticated artificial intelligence system, the human brain is capable of responding to the most diverse challenges and problems in increasingly creative and innovative ways. This book is an attempt to define super creativity by examining creativity in humans, machines, and human-machine interactions. Organized into three sections, the volume covers such topics as increasing personal creativity, the impact of artificial intelligence and digital devices, and the interaction of humans and machines in fields such as healthcare and economics