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

A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future

In the context of Industry 4.0, a growing use is being made of simulation-based decision-support tools commonly named Digital Twins. Digital Twins are replicas of the physical manufacturing assets, providing means for the monitoring and control of individual assets. Although extensive research on Digital Twins and their applications has been carried out, the majority of existing approaches are asset specific. Little consideration is made of human factors and interdependencies between different production assets are commonly ignored. In this paper, we address those limitations and propose innovations for cognitive modeling and co-simulation which may unleash novel uses of Digital Twins in Factories of the Future. We introduce a holistic Digital Twin approach, in which the factory is not represented by a set of separated Digital Twins but by a comprehensive modeling and simulation capacity embracing the full manufacturing process including external network dependencies. Furthermore, we introduce novel approaches for integrating models of human behavior and capacities for security testing with Digital Twins and show how the holistic Digital Twin can enable new services for the optimization and resilience of Factories of the Future. To illustrate this approach, we introduce a specific use-case implemented in field of Aerospace System Manufacturing.The present work was developed under the EUREKA–ITEA3 Project CyberFactory#1 (ITEA-17032), co-funded by Project CyberFactory#1PT (ANI|P2020 40124), from FEDER Funds through NORTE2020 program and from National Funds through FCT under the project UID/EEA/00760/2019 and by the Federal Ministry of Education and Research (BMBF, Germany, funding No. 01IS18061C).info:eu-repo/semantics/publishedVersio

Free-Form: The Adversarial Role of Materials in Automation

Beyond allowing students to create physical models of complex geometry they would be unable to produce by hand, how can 3D-printing become relevant to studio and in practice? This paper will discuss the underlying dilemma confronting materials in studio education, particularly in the United States. Materials are, in many ways, foreign to the studio process, and this is compounded by the addition of a “foreign” technology, such as computer-aided manufacturing. Materials are more often seen as an aesthetic selection, and their adversarial role (the way in which materials can be unpredictable, counterproductive, and even belligerent) in construction is not essential or deep learning in the studio environment. Design-build education models often seek to confront this dilemma, particularly if they are more focused on research into materials and their fabrication, but even fewer programs utilize technology such as 3D-printing, again because it can be seen as difficult enough to teach students simple manufacturing processes. This paper will discuss five schools pioneering the potential of these tools: the ETH Zurich, the University of Stuttgart, MIT, the Bartlett, and Sci-Arc. While these schools have generated provocative research and compelling full-scale installations, there is also a distinct gap between this research and its dissemination/assimilation into mainstream practice. This paper seeks to understand the gap between possibility and pragmatics by studying these innovative schools’ methodologies and the ways in which their outcomes manifest in studio/practice. In summary, 3D-printing can offer the same potential as any other tool utilized in a design-build studio. It forces students to grapple with a material understanding they can choose to ignore on paper and in a virtual environment. By more literally understanding the conversion of a three-dimensional virtual solid into a sequence of coordinates (the g-code), the mystique of the technology is made equal to that of the wood stud

How is VR used to support training in industry? The INTUITION network of excellence working group on education and training

INTUITION is the European Network of Excellence on virtual reality and virtual environments applications for future workspaces. The purpose of the network is to gather expertise from partner members and determine the future research agenda for the development and use of virtual reality (VR) technologies. The working group on Education and Training (WG2.9) is specifically focused on understanding how VR is being used to support learning in educational and industrial contexts. This paper presents four case examples of VR technology currently in use or development for training in industry. Conclusions are drawn concerning future development of VR training applications and barriers that need to be overcome

Telefacturing Based Distributed Manufacturing Environment for Optimal Manufacturing Service by Enhancing the Interoperability in the Hubs

Recent happenings are surrounding the manufacturing sector leading to intense progress towards the development of effective distributed collaborative manufacturing environments. This evolving collaborative manufacturing not only focuses on digitalisation of this environment but also necessitates service-dependent manufacturing system that offers an uninterrupted approach to a number of diverse, complicated, dynamic manufacturing operations management systems at a common work place (hub). This research presents a novel telefacturing based distributed manufacturing environment for recommending the manufacturing services based on the user preferences. The first step in this direction is to deploy the most advanced tools and techniques, that is, Ontology-based Protege 5.0 software for transforming the huge stored knowledge/information into XML schema of Ontology Language (OWL) documents and Integration of Process Planning and Scheduling (IPPS) for multijobs in a collaborative manufacturing system. Thereafter, we also investigate the possibilities of allocation of skilled workers to the best feasible operations sequence. In this context, a mathematical model is formulated for the considered objectives, that is, minimization of makespan and total training cost of the workers. With an evolutionary algorithm and developed heuristic algorithm, the performance of the proposed manufacturing system has been improved. Finally, to manifest the capability of the proposed approach, an illustrative example from the real-time manufacturing industry is validated for optimal service recommendation.This work has been supported by by COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

Digital Machines, Space, And Time: Towards A Behavioral Perspective Of Flexible Manufacturing

Recently, the diffusion of digital machines has further enhanced firms’ manufacturing flexibility, but also opened questions on potential challenges and implications in the production process. To respond to these timely issues, we adopt a behavioral perspective and comparatively explore how four different types of digital machines—characterized by increasing degrees of manufacturing flexibility—affect the perception and use of space and time for routines within the production plant. We qualitatively observe and compare 45 digital manufacturing machines, sampled across 14 firms in the British and Italian motorsport industry. A model emerges where four key mechanisms reshape the ‘space-machine’ and ‘time-machine’ routines. Such mechanisms mediate the relationship between manufacturing flexibility and firm performance. Further, we show how increasing digitalization in the manufacturing process enhances the establishment of new routines as flexible machines get introduced in the production. Finally, we discuss the theoretical and practical implications related to fostering a behavioral perspective in innovation and operations management studies

Sensor data-based decision making

Increasing globalization and growing industrial system complexity has amplified the interest in the use of information provided by sensors as a means of improving overall manufacturing system performance and maintainability. However, utilization of sensors can only be effective if the real-time data can be integrated into the necessary business processes, such as production planning, scheduling and execution systems. This integration requires the development of intelligent decision making models that can effectively process the sensor data into information and suggest appropriate actions. To be able to improve the performance of a system, the health of the system also needs to be maintained. In many cases a single sensor type cannot provide sufficient information for complex decision making including diagnostics and prognostics of a system. Therefore, a combination of sensors should be used in an integrated manner in order to achieve desired performance levels. Sensor generated data need to be processed into information through the use of appropriate decision making models in order to improve overall performance. In this dissertation, which is presented as a collection of five journal papers, several reactive and proactive decision making models that utilize data from single and multi-sensor environments are developed. The first paper presents a testbed architecture for Auto-ID systems. An adaptive inventory management model which utilizes real-time RFID data is developed in the second paper. In the third paper, a complete hardware and inventory management solution, which involves the integration of RFID sensors into an extremely low temperature industrial freezer, is presented. The last two papers in the dissertation deal with diagnostic and prognostic decision making models in order to assure the healthy operation of a manufacturing system and its components. In the fourth paper a Mahalanobis-Taguchi System (MTS) based prognostics tool is developed and it is used to estimate the remaining useful life of rolling element bearings using data acquired from vibration sensors. In the final paper, an MTS based prognostics tool is developed for a centrifugal water pump, which fuses information from multiple types of sensors in order to take diagnostic and prognostics decisions for the pump and its components --Abstract, page iv

3D-based Advanced Machine Service Support

In the face of today's unpredictable and fluctuating global market, there have been trends in industry towards wider adoption of more advanced and flexible new generation manufacturing systems. These have brought about new challenges to manufacturing equipment builders/suppliers in respect of satisfying ever-increasing customers' requirements for such advanced manufacturing systems. To stay competitive, in addition to supplying high quality equipment, machine builders/suppliers must also be capable of providing their customers with cost-effective, efficient and comprehensive service support, throughout the equipment's lifecycle. This research study has been motivated by the relatively unexplored potential of integrating 3D virtual technology with various machine service support tools/techniques to address the aforementioned challenges. The hypothesis formulated for this study is that a 3D-based virtual environment can be used as an integration platform to improve service support for new generation manufacturing systems. In order to ensure the rigour of the study, it has been initiated with a two-stage (iterative) literature review, consisting of: a preliminary review for the identification of practical problems/main issues related to the area of machine service support and in-depth reviews for the identification of research problems/questions and potential solutions. These were then followed by iterations of intensive research activities, consisting of: requirements identification, concept development, prototype implementation, testing and exploration, reflection and feedback. The process has been repeated and revised continuously until satisfactory results, required for answering the identified research problems/questions, were obtained. The main focus of this study is exploring how a 3D-based virtual environment can be used as an integration platform for supporting a more cost-effective and comprehensive strategy for improving service support for new generation manufacturing systems. One of the main outcomes of this study is the proposal of a conceptual framework for a novel 3D-based advanced machine service support strategy and a reference architecture for a corresponding service support system, for allowing machine builders/suppliers to: (1) provide more cost-effective remote machine maintenance support, and (2) provide more efficient and comprehensive extended service support during the equipment's life cycle. The proposed service support strategy advocates the tight integration of conventional (consisting of mainly machine monitoring, diagnostics, prognostics and maintenance action decision support) and extended (consisting of mainly machine re-configuration, upgrade and expansion support) service support functions. The proposed service support system is based on the integration of a 3D-based virtual environment with the equipment control system, a re-configurable automated service support system, coupled with a maintenance-support-tool/strategy support environment and an equipment re-configuration/upgrade/expansion support environment, in a network/lntenet framework. The basic concepts, potential benefits and limitations of the proposed strategy/ system have been explored via a prototype based on a laboratory-scale test bed. The prototype consists of a set of integrated modular network-ready software tools consisting of: (1) an integrated 20/30 visualisation and analysis module, (2) support tools library modules, (3) communication modules and (4) a set of modular and re-configurable automated data logging, maintenance and re-configuration support modules. A number of test cases based on various machine service support scenarios, have been conducted using the prototype. The experimentation has shown the potential and feasibility (technical implementation aspects) of the proposed 3D-based approach. This research study has made an original contribution to knowledge in the field of machine service support. It has contributed a novel approach of using a 3D-based virtual environment as an integration platform for improving the capability of machine builders/suppliers in providing more cost-effective and comprehensive machine service support for complex new generation manufacturing systems. Several important findings have resulted from this work in particular with respect to how various 20/30 visualisation environments are integrated with machine service support tools/techniques for improving service support for complex manufacturing systems. A number of aspects have also been identified for future work