User-Friendly MES Interfaces:Recommendations for an AI-Based Chatbot Assistance in Industry 4.0 Shop Floors

The purpose of this paper is to study an Industry 4.0 scenario of ‘technical assistance’ and use manufacturing execution systems (MES) to address the need for easy information extraction on the shop floor. We identify specific requirements for a user-friendly MES interface to develop (and test) an approach for technical assistance and introduce a chatbot with a prediction system as an interface layer for MES. The chatbot is aimed at production coordination by assisting the shop floor workforce and learn from their inputs, thus acting as an intelligent assistant. We programmed a prototype chatbot as a proof of concept, where the new interface layer provided live updates related to production in natural language and added predictive power to MES. The results indicate that the chatbot interface for MES is beneficial to the shop floor workforce and provides easy information extraction, compared to the traditional search techniques. The paper contributes to the manufacturing information systems field and demonstrates a human-AI collaboration system in a factory. In particular, this paper recommends the manner in which MES based technical assistance systems can be developed for the purpose of easy information retrieval

The role of Computer Aided Process Engineering in physiology and clinical medicine

This paper discusses the potential role for Computer Aided Process Engineering (CAPE) in developing engineering analysis and design approaches to biological systems across multiple levels—cell signalling networks, gene, protein and metabolic networks, cellular systems, through to physiological systems. The 21st Century challenge in the Life Sciences is to bring together widely dispersed models and knowledge in order to enable a system-wide understanding of these complex systems. This systems level understanding should have broad clinical benefits. Computer Aided Process Engineering can bring systems approaches to (i) improving understanding of these complex chemical and physical (particularly molecular transport in complex flow regimes) interactions at multiple scales in living systems, (ii) analysis of these models to help to identify critical missing information and to explore the consequences on major output variables resulting from disturbances to the system, and (iii) ‘design’ potential interventions in in vivo systems which can have significant beneficial, or potentially harmful, effects which need to be understood. This paper develops these three themes drawing on recent projects at UCL. The first project has modeled the effects of blood flow on endothelial cells lining arteries, taking into account cell shape change resulting in changes in the cell skeleton which cause consequent chemical changes. A second is a project which is building an in silico model of the human liver, tieing together models from the molecular level to the liver. The composite model models glucose regulation in the liver and associated organs. Both projects involve molecular transport, chemical reactions, and complex multiscale systems, tackled by approaches from CAPE. Chemical Engineers solve multiple scale problems in manufacturing processes – from molecular scale through unit operations scale to plant-wide and enterprise wide systems – so have an appropriate skill set for tackling problems in physiology and clinical medicine, in collaboration with life and clinical scientists

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

On inferring intentions in shared tasks for industrial collaborative robots

Inferring human operators' actions in shared collaborative tasks, plays a crucial role in enhancing the cognitive capabilities of industrial robots. In all these incipient collaborative robotic applications, humans and robots not only should share space but also forces and the execution of a task. In this article, we present a robotic system which is able to identify different human's intentions and to adapt its behavior consequently, only by means of force data. In order to accomplish this aim, three major contributions are presented: (a) force-based operator's intent recognition, (b) force-based dataset of physical human-robot interaction and (c) validation of the whole system in a scenario inspired by a realistic industrial application. This work is an important step towards a more natural and user-friendly manner of physical human-robot interaction in scenarios where humans and robots collaborate in the accomplishment of a task.Peer ReviewedPostprint (published version

The Application of Mixed Reality Within Civil Nuclear Manufacturing and Operational Environments

This thesis documents the design and application of Mixed Reality (MR) within a nuclear manufacturing cell through the creation of a Digitally Assisted Assembly Cell (DAAC). The DAAC is a proof of concept system, combining full body tracking within a room sized environment and bi-directional feedback mechanism to allow communication between users within the Virtual Environment (VE) and a manufacturing cell. This allows for training, remote assistance, delivery of work instructions, and data capture within a manufacturing cell. The research underpinning the DAAC encompasses four main areas; the nuclear industry, Virtual Reality (VR) and MR technology, MR within manufacturing, and finally the 4 th Industrial Revolution (IR4.0). Using an array of Kinect sensors, the DAAC was designed to capture user movements within a real manufacturing cell, which can be transferred in real time to a VE, creating a digital twin of the real cell. Users can interact with each other via digital assets and laser pointers projected into the cell, accompanied by a built-in Voice over Internet Protocol (VoIP) system. This allows for the capture of implicit knowledge from operators within the real manufacturing cell, as well as transfer of that knowledge to future operators. Additionally, users can connect to the VE from anywhere in the world. In this way, experts are able to communicate with the users in the real manufacturing cell and assist with their training. The human tracking data fills an identified gap in the IR4.0 network of Cyber Physical System (CPS), and could allow for future optimisations within manufacturing systems, Material Resource Planning (MRP) and Enterprise Resource Planning (ERP). This project is a demonstration of how MR could prove valuable within nuclear manufacture. The DAAC is designed to be low cost. It is hoped this will allow for its use by groups who have traditionally been priced out of MR technology. This could help Small to Medium Enterprises (SMEs) close the double digital divide between themselves and larger global corporations. For larger corporations it offers the benefit of being low cost, and, is consequently, easier to roll out across the value chain. Skills developed in one area can also be transferred to others across the internet, as users from one manufacturing cell can watch and communicate with those in another. However, as a proof of concept, the DAAC is at Technology Readiness Level (TRL) five or six and, prior to its wider application, further testing is required to asses and improve the technology. The work was patented in both the UK (S. R EDDISH et al., 2017a), the US (S. R EDDISH et al., 2017b) and China (S. R EDDISH et al., 2017c). The patents are owned by Rolls-Royce and cover the methods of bi-directional feedback from which users can interact from the digital to the real and vice versa. Stephen Reddish Mixed Mode Realities in Nuclear Manufacturing Key words: Mixed Mode Reality, Virtual Reality, Augmented Reality, Nuclear, Manufacture, Digital Twin, Cyber Physical Syste

Digital technologies review for manufacturing processes

It is apparent the industrial processes transformations caused by industry 4.0 are in advance in some countries like China, Japan, Germany and United States. But, in return, the developing countries, as the emergent Brazil, seem like to have a long way to achieve digital era. Considering manufacturing processes as the starting point the rise of industry 4.0, this research aims to show a review about the most important technologies used in smart manufacturing, including the main challenges to implement it at Brazil. The papers were collected from Web of Science (WoS), comprising 114 articles and 2 books to underpin this study. This exploratory research resulted in the presentation of some challenges faced by Brazilian industry to join the new industrial era, such as poor technological infrastructure, besides lack of investment in technologies and training of qualified people. Even though the primary motivation of this research was to present a panorama of smart manufacturing for Brazil, this study results contributes to the most of emergent countries, bringing together general concepts and addressing practical applications developed by several researchers from the international academic community

Hands-on learning modules for upskilling in industry 4.0 technologies

The Industry 4.0 (I4.0) advent is re-shaping the way systems and processes operate by considering Cyber- Physical Systems combined with a plethora of emergent Information and Communication Technologies (ICT), e.g., Internet of Things (IoT), Artificial Intelligence, Cloud Computing and Intelligent Robotics. However, the emergence of such disruptive technologies strongly establishes a demand for upskilling and requalification of active professionals and young undergraduate students. This means that the wide adoption of the 14.0 systems and related tech-nologies is dependent on the efficient implementation of lifelong learning and training initiatives that address these challenges. Having this in mind, this paper describes the implementation of a series of short learning modules and hackathons that relies on a strong hands-on practical experimentation, regarding the upskilling in emergent ICT technologies, particularly focusing on IoT, mobile robotics and Multi-agent Systems. The preliminary efforts contributed to qualify undergraduate students and active professionals in disruptive ICT, with the attendees' feedback illustrating the importance of these kind of short and hands-on learning modules to address towards the continuous demands associated to the diaital transformation.info:eu-repo/semantics/publishedVersio