9,281 research outputs found

    Energy-efficient through-life smart design, manufacturing and operation of ships in an industry 4.0 environment

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    Energy efficiency is an important factor in the marine industry to help reduce manufacturing and operational costs as well as the impact on the environment. In the face of global competition and cost-effectiveness, ship builders and operators today require a major overhaul in the entire ship design, manufacturing and operation process to achieve these goals. This paper highlights smart design, manufacturing and operation as the way forward in an industry 4.0 (i4) era from designing for better energy efficiency to more intelligent ships and smart operation through-life. The paper (i) draws parallels between ship design, manufacturing and operation processes, (ii) identifies key challenges facing such a temporal (lifecycle) as opposed to spatial (mass) products, (iii) proposes a closed-loop ship lifecycle framework and (iv) outlines potential future directions in smart design, manufacturing and operation of ships in an industry 4.0 value chain so as to achieve more energy-efficient vessels. Through computational intelligence and cyber-physical integration, we envision that industry 4.0 can revolutionise ship design, manufacturing and operations in a smart product through-life process in the near future

    Development of an Extended Product Lifecycle Management through Service Oriented Architecture.

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    Organised by: Cranfield UniversityThe aim of this work is to define new business opportunities through the concept of Extended Product Lifecycle Management (ExtPLM), analysing its potential implementation within a Service Oriented Architecture. ExtPLM merges the concepts of Extended Product, Avatar and PLM. It aims at allowing a closer interaction between enterprises and their customers, who are integrated in all phases of the life cycle, creating new technical functionalities and services, improving both the practical (e.g. improving usage, improving safety, allowing predictive maintenance) and the emotional side (e.g. extreme customization) of the product.Mori Seiki – The Machine Tool Company; BAE Systems; S4T – Support Service Solutions: Strategy and Transitio

    Generic PLM system for SMEs: Application to an equipment manufacturer

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    For several years, digital engineering has increasingly taken a more important place in the strategic issues of mechanical engineering companies. Our proposition is an approach that enables technical data to be managed and used throughout the product life-cycle. This approach aims to provide assistance for costing, development and industrialization of the product, and for the capitalization, the reuse and the extension of fundamental knowledge. This approach has been experimented within several companies. This paper presents the case in a company environment that designs and produces families of ship equipment parts

    Product lifecycle management in degree level teaching with Teamcenter PLM software

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    Despite the situation that product lifecycle management is heavily used in Finnish manufacturing industry, some Finnish educational institutions have not implemented practical PLM system functionalities into educational program. Common situation among educational institutions is that PLM training is mainly theoretical. Even when PLM software is implemented it is mainly used as data storage system. However, PLM system is much more than data storage. The lack of effective product lifecycle management training environment influences negatively to graduated students PLM skills. Increased communication, control of processes and single source of information are main benefits of a PLM system. This research studies the most relevant focus areas in Product lifecycle Management theoretical and practical teaching based on the requirements gathered from Finnish Manufacturing Industry. This research is focusing on the most important theoretical PLM focus areas, but also the most common practical PLM applications, processes and use cases in Finnish manufacturing industry. Based on the requirements of Finnish Manufacturing Industry, Teamcenter PLM software is implemented and configured to support practical degree level teaching. Research clarifies the current PLM knowledge of graduated students and gives recommendations about degree level PLM teaching arrangements. Both theoretical and practical teaching are considered. Based on the findings gathered from 35 Finnish manufacturing companies, relevant PLM use cases, processes and application are implemented to support Product Lifecycle management education with Teamcenter PLM software. Furthermore, the importance of different theoretical PLM topics is clarified based on the opinions of PLM professionals. This study utilizes design science research method to gather empirical data from different manufacturing companies. The foundation of PLM research presented in literature review provides the framework for this study. These studies provide the background information about PLM and how the implementation of PLM system can provide business benefits. This research proposes configured Teamcenter PLM environment for Finnish educational institutions to serve as a foundation of PLM system. Furthermore, the suggested PLM artifact is demonstrated, evaluated and communicated to specified target audience.Tuotteen elinkaaren hallinnan kÀyttö Suomalaisessa valmistavassa teollisuudessa on lisÀÀntynyt viime vuosina merkittÀvÀsti. KÀytön laajentumisesta huolimatta Suomen korkeakoulut eivÀt ole vielÀ tÀysin ottaneet kÀyttöön ohjelmistopohjaista kÀytÀnnön opetusta. Yleinen tilanne on, ettÀ tuotteen elinkaaren hallintaa opetataan vain teoria tasolla, ja vaikka tuotetiedonhallinta ohjelmisto olisikin kÀyttöönotettu, se toimii pÀÀasiassa datan tallennuspaikkana. Tuotteen elinkaaren hallinta ohjelmiston opetuksen puute vaikuttaa negatiivisesti valmistuvien opiskelijoiden PLM osaamiseen. PLM jÀrjestelmÀn etuja ovat lisÀÀntynyt kommunikaatio, kontrolloidut prosessit ja yhteinen tiedonlÀhde. TÀmÀ tutkimus keskittyy löytÀmÀÀn merkityksellisimmÀt fokus alueet tuotteen elinkaaren hallinnan teoria opetuksessa ja kÀytÀnnön opetuksessa. Tulokset perustuvat aineistoon joka on kerÀtty Suomalaisen valmistavan teollisuuden PLM asiantuntijoilta. TÀmÀ tutkimus keskittyy merkittÀvimpiin ja tÀrkeimpiin PLM teoria alueisiin, mutta myös Suomen valmistavassa teollisuudessa kÀytetyimpiin PLM jÀrjestelmÀn aplikaatioihin, prosesseihin ja kÀyttötapauksiin. Teamcenter PLM jÀrjestelmÀ kÀyttöönotetaan ja konfiguroidaan tukemaan korkeakoulu opetusta. Tutkimuksessa selvitetÀÀn tÀmÀn hetkinen valmistuvien opiskelijoiden tietÀmys ja annetaan suosituksia kuinka PLM opetus tulisi jÀrjestÀÀ Suomen korkeakouluissa. SekÀ teoria opetus, ettÀ kÀytÀnnön opetus on huomioitu tukimuksessa. TÀrkeimmÀt Teamcenter PLM jÀrjestelmÀn ominaisuudet kÀyttöönotetaan ja konfiguroidaan opetuksen tueksi. JÀrjestelmÀn vaatimukset perustuvat 35:een Suomen valmistavassa teollisuudessa toimivan yrityksen vaatimuksiin. TÀrkeimmÀt Teamcenter PLM ohjelmiston ominaisuudet, prosessit ja kÀyttötapaukset huomioidaan tutkimuksessa. Teoreettisen opetuksen tÀrkeimmÀt osa-alueet selvitetÀÀn kyselyn avulla Suomen valmistavan teollisuuden PLM asiantuntijoilta. Tutkimuksessa hyödynnetÀÀn Design Science Research metodia. Tutkimuksen lÀhtökohtana on kirjallisuus analyysi, joka antaa taustatietoa tukimukselle. TÀssÀ tutkimuksessa annetaan suosituksia PLM opetuksen jÀrjestÀmisestÀ Suomen korkeakouluissa, sekÀ suositellaan Teamcenter PLM ohjelmiston kÀyttöönottoa ja konfigurointia tukemaan tuotteen elinkaaren hallinnan opetusta

    An Intelligent Knowledge Management System from a Semantic Perspective

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    Knowledge Management Systems (KMS) are important tools by which organizations can better use information and, more importantly, manage knowledge. Unlike other strategies, knowledge management (KM) is difficult to define because it encompasses a range of concepts, management tasks, technologies, and organizational practices, all of which come under the umbrella of the information management. Semantic approaches allow easier and more efficient training, maintenance, and support knowledge. Current ICT markets are dominated by relational databases and document-centric information technologies, procedural algorithmic programming paradigms, and stack architecture. A key driver of global economic expansion in the coming decade is the build-out of broadband telecommunications and the deployment of intelligent services bundling. This paper introduces the main characteristics of an Intelligent Knowledge Management System as a multiagent system used in a Learning Control Problem (IKMSLCP), from a semantic perspective. We describe an intelligent KM framework, allowing the observer (a human agent) to learn from experience. This framework makes the system dynamic (flexible and adaptable) so it evolves, guaranteeing high levels of stability when performing his domain problem P. To capture by the agent who learn the control knowledge for solving a task-allocation problem, the control expert system uses at any time, an internal fuzzy knowledge model of the (business) process based on the last knowledge model.knowledge management, fuzzy control, semantic technologies, computational intelligence

    Enterprise modelling : building a product lifecycle (PLM) model as a component of the integrated vision of the enterprise

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    Enterprise modelling has proved to be an efficient tool to study organisations structure and facilitate decision making. The enterprise is a complex system that is required to use its processes to generate value in a given environment (concurrent, market, suppliers and humanity). We focus on three management disciplines: Product Lifecycle Management (PLM), Supply Chain Management (SCM) and Customer Relationship Management (CRM). These business processes are so intertwined that the enterprise has to concentrate on the three to attain its economic objectives. To enhance the development of PLM, SCM and CRM models, the enterprise needs to capitalise the knowledge necessary to adapt and apply modelling techniques. Knowledge Management (KM) is a key factor to give a unified enterprise vision. Firstly, we propose an integrated enterprise model depicting the interactions between PLM, SCM, CRM and KM models. But a state of the art showed that PLM models are scarce. Most of the PLM models found depends strongly on the particular case studied and can not be used with other enterprises. After defining the most important components of the PLM vision, we propose to organise these components into a formalised way. The study of SCM and CRM models proved to be helpful to structure these components. Finally the validation methodology that is to be established in our coming research works is not only to be used with the PLM model presented in this paper but with SCM and CRM models also.Product Lifecycle Management (PLM), Enterprise modelling, Enterprise systems

    Identifying smart design attributes for Industry 4.0 customization using a clustering Genetic Algorithm

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    Industry 4.0 aims at achieving mass customization at a mass production cost. A key component to realizing this is accurate prediction of customer needs and wants, which is however a challenging issue due to the lack of smart analytics tools. This paper investigates this issue in depth and then develops a predictive analytic framework for integrating cloud computing, big data analysis, business informatics, communication technologies, and digital industrial production systems. Computational intelligence in the form of a cluster k-means approach is used to manage relevant big data for feeding potential customer needs and wants to smart designs for targeted productivity and customized mass production. The identification of patterns from big data is achieved with cluster k-means and with the selection of optimal attributes using genetic algorithms. A car customization case study shows how it may be applied and where to assign new clusters with growing knowledge of customer needs and wants. This approach offer a number of features suitable to smart design in realizing Industry 4.0

    Towards Digital Twin-enabled DevOps for CPS providing Architecture-Based Service Adaptation & Verification at Runtime

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    Industrial Product-Service Systems (IPSS) denote a service-oriented (SO) way of providing access to CPS capabilities. The design of such systems bears high risk due to uncertainty in requirements related to service function and behavior, operation environments, and evolving customer needs. Such risks and uncertainties are well known in the IT sector, where DevOps principles ensure continuous system improvement through reliable and frequent delivery processes. A modular and SO system architecture complements these processes to facilitate IT system adaptation and evolution. This work proposes a method to use and extend the Digital Twins (DTs) of IPSS assets for enabling the continuous optimization of CPS service delivery and the latter's adaptation to changing needs and environments. This reduces uncertainty during design and operations by assuring IPSS integrity and availability, especially for design and service adaptations at CPS runtime. The method builds on transferring IT DevOps principles to DT-enabled CPS IPSS. The chosen design approach integrates, reuses, and aligns the DT processing and communication resources with DevOps requirements derived from literature. We use these requirements to propose a DT-enabled self-adaptive CPS model, which guides the realization of DT-enabled DevOps in CPS IPSS. We further propose detailed design models for operation-critical DTs that integrate CPS closed-loop control and architecture-based CPS adaptation. This integrated approach enables the implementation of A/B testing as a use case and central concept to enable CPS IPSS service adaptation and reconfiguration. The self-adaptive CPS model and DT design concept have been validated in an evaluation environment for operation-critical CPS IPSS. The demonstrator achieved sub-millisecond cycle times during service A/B testing at runtime without causing CPS operation interferences and downtime.Comment: Final published version appearing in 17th Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2022

    An Ontological Approach to Representing the Product Life Cycle

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    The ability to access and share data is key to optimizing and streamlining any industrial production process. Unfortunately, the manufacturing industry is stymied by a lack of interoperability among the systems by which data are produced and managed, and this is true both within and across organizations. In this paper, we describe our work to address this problem through the creation of a suite of modular ontologies representing the product life cycle and its successive phases, from design to end of life. We call this suite the Product Life Cycle (PLC) Ontologies. The suite extends proximately from The Common Core Ontologies (CCO) used widely in defense and intelligence circles, and ultimately from the Basic Formal Ontology (BFO), which serves as top level ontology for the CCO and for some 300 further ontologies. The PLC Ontologies were developed together, but they have been factored to cover particular domains such as design, manufacturing processes, and tools. We argue that these ontologies, when used together with standard public domain alignment and browsing tools created within the context of the Semantic Web, may offer a low-cost approach to solving increasingly costly problems of data management in the manufacturing industry

    Value Generation in the Product Lifecycle with Digital Twins: Status Quo in Swiss Companies

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    Value generation with digital twins along the phases of the product lifecycle affects different processes from a company's internal perspective. The present study investigated in which phases of the product lifecycle and processes swiss companies seek to generate what value contribution. The results of the survey of 103 companies show that only 47% of the companies surveyed are applying or planning to apply digital twins. The motivation primarily lies in increasing efficiency (79%) or in building competitive advantage (63%). These companies clearly recognize the potential of digital twins to create value in the Beginning-of-Life-phase (79%) and in the Middle-of-Life-phase (60%). In contrest, the use in the End-of-Life-phase (15%) is subordinate. The companies seek to generate value with digital twins by offering qualitatively better products and services in a shorter time or with higher availability. Cost savings seem secondary and overestimated by companies before they apply digital twins
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