32,781 research outputs found

    Data-driven through-life costing to support product lifecycle management solutions in innovative product development

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    Innovative product usually refers to product that comprises of creativity and new ideas. In the development of such a new product, there is often a lack of historical knowledge and data available to be used to perform cost estimation accurately. This is due to the fact that traditional cost estimation methods are used to predict costs only after a product model has been built, and not at an early design stage when there is little data and information available. In light of this, original equipment manufacturers are also facing critical challenges of becoming globally competitive and increasing demands from customer for continuous innovation. To alleviate these situations this research has identified a new approach to cost modelling with the inclusion of product lifecycle management solutions to address innovative product development.The aim of this paper, therefore, is to discuss methods of developing an extended-enterprise data-driven through-life cost estimating method for innovative product development

    Integration of experience feedback into the product lifecycle: an approach to best respond to the bidding process

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    Bidding process allows a client to choose a bidder to realize an embodiment of work, supply or service. From the bidder point of view, there are several obvious risks when responding because he bets on a future development that hasn’t been yet realized. We propose to assist the bidder with decision support tools based on past experiences to detect, report and minimize these potential risks. In this paper, we present the definition of a conceptual architecture to integrate experience feedback into the product lifecycle taking into account all stages of product lifecycle to best respond new bidding processes

    A service oriented approach for guidelines-based clinical decision support using BPMN

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    Evidence-based medical practice requires that clinical guidelines need to be documented in such a way that they represent a clinical workflow in its most accessible form. In order to optimize clinical processes to improve clinical outcomes, we propose a Service Oriented Architecture (SOA) based approach for implementing clinical guidelines that can be accessed from an Electronic Health Record (EHR) application with a Web Services enabled communication mechanism with the Enterprise Service Bus. We have used Business Process Modelling Notation (BPMN) for modelling and presenting the clinical pathway in the form of a workflow. The aim of this study is to produce spontaneous alerts in the healthcare workflow in the diagnosis of Chronic Obstructive Pulmonary Disease (COPD). The use of BPMN as a tool to automate clinical guidelines has not been previously employed for providing Clinical Decision Support (CDS)

    Problem solving methods as Lessons Learned System instrumentation into a PLM tool

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    Among the continuous improvement tools of the performance in enterprise, the experience feedback represents undoubtedly an effective lever of progress by offering important prospects for a progression in almost all the industrial sectors. However, several reserves to its use slow down the diffusion of its employment. We are interested in the installation of experience feedback system in a partner enterprise. In this paper, we propose an instrumentation of a Lessons Learned System (LLS) by problem solving methods (PSM) and its integration with a product lifecycle management (PLM). These proposals support an improvement of LLS performance and a facility of his application

    Integrated product relationships management : a model to enable concurrent product design and assembly sequence planning

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    The paper describes a novel approach to product relationships management in the context of concurrent engineering and product lifecycle management (PLM). Current industrial practices in product data management and manufacturing process management systems require better efficiency, flexibility, and sensitivity in managing product information at various levels of abstraction throughout its lifecycle. The aim of the proposed work is to manage vital yet complex and inherent product relationship information to enable concurrent product design and assembly sequence planning. Indeed, the definition of the product with its assembly sequence requires the management and the understanding of the numerous product relationships, ensuring consistency between the product and its components. This main objective stresses the relational design paradigm by focusing on product relationships along its lifecycle. This paper gives the detailed description of the background and models which highlight the need for a more efficient PLM approach. The proposed theoretical approach is then described in detail. A separate paper will focus on the implementation of the proposed approach in a PLM-based application, and an in-depth case study to evaluate the implementation of the novel approach will also be given

    Practitioner requirements for integrated Knowledge-Based Engineering in Product Lifecycle Management.

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    The effective management of knowledge as capital is considered essential to the success of engineering product/service systems. As Knowledge Management (KM) and Product Lifecycle Management (PLM) practice gain industrial adoption, the question of functional overlaps between both the approaches becomes evident. This article explores the interoperability between PLM and Knowledge-Based Engineering (KBE) as a strategy for engineering KM. The opinion of key KBE/PLM practitioners are systematically captured and analysed. A set of ranked business functionalities to be fulfiled by the KBE/PLM systems integration is elicited. The article provides insights for the researchers and the practitioners playing both the user and development roles on the future needs for knowledge systems based on PLM

    Overview of Remaining Useful Life prediction techniques in Through-life Engineering Services

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    Through-life Engineering Services (TES) are essential in the manufacture and servicing of complex engineering products. TES improves support services by providing prognosis of run-to-failure and time-to-failure on-demand data for better decision making. The concept of Remaining Useful Life (RUL) is utilised to predict life-span of components (of a service system) with the purpose of minimising catastrophic failure events in both manufacturing and service sectors. The purpose of this paper is to identify failure mechanisms and emphasise the failure events prediction approaches that can effectively reduce uncertainties. It will demonstrate the classification of techniques used in RUL prediction for optimisation of products’ future use based on current products in-service with regards to predictability, availability and reliability. It presents a mapping of degradation mechanisms against techniques for knowledge acquisition with the objective of presenting to designers and manufacturers ways to improve the life-span of components

    Data mining based cyber-attack detection

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    Evaluation of Cognitive Architectures for Cyber-Physical Production Systems

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    Cyber-physical production systems (CPPS) integrate physical and computational resources due to increasingly available sensors and processing power. This enables the usage of data, to create additional benefit, such as condition monitoring or optimization. These capabilities can lead to cognition, such that the system is able to adapt independently to changing circumstances by learning from additional sensors information. Developing a reference architecture for the design of CPPS and standardization of machines and software interfaces is crucial to enable compatibility of data usage between different machine models and vendors. This paper analysis existing reference architecture regarding their cognitive abilities, based on requirements that are derived from three different use cases. The results from the evaluation of the reference architectures, which include two instances that stem from the field of cognitive science, reveal a gap in the applicability of the architectures regarding the generalizability and the level of abstraction. While reference architectures from the field of automation are suitable to address use case specific requirements, and do not address the general requirements, especially w.r.t. adaptability, the examples from the field of cognitive science are well usable to reach a high level of adaption and cognition. It is desirable to merge advantages of both classes of architectures to address challenges in the field of CPPS in Industrie 4.0
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