A Fuzzy Logic based system for Mixed Reality assistance of remote workforce

The recent years have witnessed an increase in the use of augmented and virtual reality systems, changing the way we interact with our environments. Such systems are commonly associated with advertising, entertainment, medicine, training and education. However, with the increasing acceptance and availability of mobile and wearable devices (e.g. head-mounted displays (HMD)), the use of these technologies is moving towards professional and industrial environments, where they would be able to support employees in their daily tasks, increasing customer satisfaction and reducing business costs. This paper presents an innovative Mixed Reality (MR) system to assist field workforce in remote locations. As part of the overall implementation, the MR system uses fuzzy logic mechanisms to improve accuracy in user tracking and object monitoring, allowing the correct representation of users and objects in the Graphical User Interfaces (GUIs), and improving the experience for users

Furthering Service 4.0: Harnessing Intelligent Immersive Environments and Systems

With the increasing complexity of service operations in different industries and more advanced uses of specialized equipment and procedures, the great current challenge for companies is to increase employees' expertise and their ability to maintain and improve service quality. In this regard, Service 4.0 aims to support and promote innovation in service operations using emergent technology. Current technological innovations present a significant opportunity to provide on-site, real-time support for field service professionals in many areas

IMMERSIVE, INTEROPERABLE AND INTUITIVE MIXED REALITY FOR SERVICE IN INDUSTRIAL PLANTS

The authors propose an innovative Mixed Reality solution representing an immersive intuitive and interoperable environment to support service in industrial plants. These methodologies are related to concepts of Industry 4.0. Solutions based on a mix of VR and AR (Virtual and Augmented Reality ) with special attention to the maintenance of industrial machines; indeed the authors propose an overview of this approach and other synergistic techniques. Moreover, alternative instruments are presented and their specific advantages and disadvantages are described. Particularly, the approach is based on the SPIDER, an advanced interoperable interactive CAVE developed by the authors which supports cooperative work of several users involved in training, troubleshooting and supervision are proposed. Last but not least, an overview of projects using same techniques in other fields, such as construction, risk assessment, Virtual Prototyping and Simulation Based Design is presented

Industry 5.0 for sustainable reliability centered maintenance

Industry 5.0 is based on the idea of merging sustainable development goals and digitalization provisions from the fourth industrial revolution through human-centric solutions, bio-inspired technologies, and cyber safe data transmission. Industries are yet the most significant drivers of the integrated sustainability development (economic, environmental, and social) over the design, manufacturing, operation and disposal of products and services. This research investigates Industry 5.0 indicators that are required to achieve sustainable reliability centered maintenance (RCM) for high-value equipment. The research work examines the feasibility of a correlation between sustainable indicators between operation and maintenance phases using fuzzy logic. The fuzzy approach is implemented to measure the impact of RCM technical indicators on sustainability. A broader recommendation to improve sustainable RCM is presented through an academic survey.Cranfield Universit

An Explainable AI Approach to Process Data in Mixed Reality Environments for Field Service Operations

Digital Twins is a concept that describes how physical objects can be represented and connected to the virtual world, the main goal of a Digital Twin is to centralise all the available information of an object of interest in a single virtual model. The Digital Twin consist of three main components: the physical object, a virtual representation of that object (typically a 3D model), and a real-time connection between both objects so that any change can be communicated to the other part. The possibility of understanding, visualising, and interacting with physical objects through a virtual environment is, at a very high level, the main benefit of using Digital Twins. The adoption of this concept has grown a lot in the recent years in industries such as the manufacturing, construction, health, and energy. Utility companies in the telecommunication industry, water services, and gas services are still falling behind in the adoption of these new concepts. The potential benefit for these sectors is huge where some of these benefits are real-time remote monitoring, predictive maintenance, scenario and risk assessment, better collaboration between stakeholders (internal and external), and better documentation. Existing Mixed Reality, Virtual Reality and Augmented Reality technologies can help with the interaction and visualisation of the virtual twin. The different levels of reality in combination with the digital twins will help with different tasks, for example, Virtual Reality is useful for remote tasks were most of the interaction happens with the virtual twin and Augmented Reality will help bringing the virtual twin and all its information to onsite tasks to help field engineers. However, there are different challenges when trying to connect all the different components and some of these challenges did slow down the adoption of these technologies by the utility companies. The research work in this thesis will focus on two main challenges: the cost of creating these digital twins from existing sources of information and the lack of an explainable AI approach that can be used as an enabler for the interaction between human and Digital Twin in the mixed reality environment. To address the challenge of automating the creation of digital representations at a low cost, two interval type-2 Fuzzy Rule-based Systems are presented as the best explainable AI alternatives to the opaque AI models for processing images and extracting information of the objects of interest. One of them was used to extract information about trees in a satellite image and generate a 3D representation of the geographic area combined with terrain data. This will be used for remote scenario and risk assessment and prediction of the telecommunication equipment getting damaged by natural elements like trees. The proposed approach achieved an 86.90% of accuracy, 3.5% better than the type-1 but 3.0% worse than the opaque Multilayer Perceptron model. The second interval type-2 Fuzzy Rule-based System is an explainable AI model that incorporates the use of context information in its rule to process 2D floor plan images, identify elements of interest and create a 3D digital representation of the building floors. This will benefit the telecommunication company by automating, at a low cost, the process of creating a more detailed in-building map with the telecommunication assets and improve the collaboration with external stakeholders like contractors for maintenance tasks or construction companies for any works in the building. The proposed method achieved a 97.5% Intersection over Union metric value which was comparable to the 99.3% Intersection over Union of the opaque Convolutional Neural Network model, however our proposed solution is highly interpretable and augmentable by human experts which cannot be achieved via opaque box AI models. Additionally, another interval type-2 Fuzzy Rule-based System for hand gesture classification is also presented in this thesis. This rule-based system achieved a 96.4% accuracy, and it is an easily adjustable model that can be modified to include more hand gestures, the opaque model alternative, a K-Nearest Neighbour algorithm achieved a 98.9% accuracy, however, this model cannot be easily modified by a human expert and re-training is needed which results in a cost of time. This hand gesture recognition model, alongside another fuzzy rule-based system, will help to address the challenge of the interaction between human and digital twin objects in Mixed Reality environments

Implementing Industry 4.0 in SMEs

This open access book addresses the practical challenges that Industry 4.0 presents for SMEs. While large companies are already responding to the changes resulting from the fourth industrial revolution , small businesses are in danger of falling behind due to the lack of examples, best practices and established methods and tools. Following on from the publication of the previous book ‘Industry 4.0 for SMEs: Challenges, Opportunities and Requirements’, the authors offer in this new book innovative results from research on smart manufacturing, smart logistics and managerial models for SMEs. Based on a large scale EU-funded research project involving seven academic institutions from three continents and a network of over fifty small and medium sized enterprises, the book reveals the methods and tools required to support the successful implementation of Industry 4.0 along with practical examples

Enterprise, project and workforce selection models for industry 4.0.

Abstract Enterprise, project, and workforce selection models for Industry 4.0. Rupinder Kaur The German federal government first coined industry 4.0 in 2011. Industry 4.0 involves the use of advanced technologies such as cyber-physical system, internet of things, cloud computing, and cognitive computing with the aim to revolutionize the current manufacturing practices. Automation and exchange of big data and key characteristics of Industry 4.0. Due to its numerous benefits, industries are readily investing in Industry 4.0, but this implementation is an uphill struggle. In this thesis, we address three key problems related to Industry 4.0 implementation namely Enterprise selection, Project selection and Workforce selection. The first problem involves identification of enterprises suitable for Industry 4.0 implementation. The second problem involves prioritization and selection of Industry 4.0 projects for the chosen digital enterprises. The third and last problem involves workforce selection and assignment for execution of the identified Industry 4.0 projects. Multicriteria solution approaches based on TOPSIS and Genetic Algorithms are proposed to address these problems. Industry experts are involved to prioritize the criteria used for enterprise, project and workforce selection. Numerical applications are provided. The proposed work is innovative and can be useful to manufacturing and service organizations interested in implementing Industry 4.0 projects for performance improvement

Fuzzy-based user modelling for motivation assessment in programming learning adaptive web-based education systems

Learning programming is not an easy task and students often find this subject difficult to understand and pass. One way to improve students’ knowledge in programming is by using Intelligent Tutoring System (ITS) through Adaptive Web-Based Education Systems (AWBESs). The objective of ITS is to provide a personalized tutoring that is tailored to the student’s needs. User modelling is one of the key factors that can meet the ITS intended objectives. From the literature, it was discovered that motivation stands out as one of the critical students’ characteristics that need to be considered when designing a user model. However, from the previous studies, it was discovered that almost all the researchers and educators constructed the user model based on knowledge and skills as students’ characteristics. Thus, the aim of this study is to develop a user model based on students’ motivation known as the Motivation Assessment Model. This is a model that is able to assess students’ motivation level and deliver tutorial materials accordingly. The Motivation Assessment Model was developed based on Self-Efficacy theory that contributes to the fundamental motivation factor which influences students’ motivation during the learning process. Furthermore, to assess the motivation level, fuzzy logic technique was applied. A tutoring system was then developed based on the proposed model using ITS architecture and ADDIE instructional design model. In order to determine students’ knowledge level after using the tutoring system, pre- and post-tests were conducted on the controlled group and experimental group (30 and 31 students). The learning achievements between experimental group (mean = 3.00) and control group (mean = 2.00) indicated that the tutoring system is significantly more effective in improving students’ knowledge level compared to the traditional approach. A usability evaluation was also conducted whereby the effectiveness was evaluated at the number of errors (7.5%) and completion rate (86.5%); efficiency (mean = 4.85); satisfaction evaluated at task level (mean = 6.77) and test level (mean = 83.55). As a conclusion, the overall tutoring system usability results are accepted by students in the experimental group. The research contribution to knowledge is the development of the proposed Motivation Assessment Model for ITS

Technology 2003: The Fourth National Technology Transfer Conference and Exposition, volume 2

Proceedings from symposia of the Technology 2003 Conference and Exposition, Dec. 7-9, 1993, Anaheim, CA, are presented. Volume 2 features papers on artificial intelligence, CAD&E, computer hardware, computer software, information management, photonics, robotics, test and measurement, video and imaging, and virtual reality/simulation