An Ontology-Based Approach for Closed-Loop Product Lifecycle Management

The main goal of the Product Lifecycle Management (PLM) is the management of all the data associated to a product during its lifecycle. Lifecycle data is being generated by events and actions (of various lifecycle agents which are humans and/or software systems) and it is distributed along the product's lifecycle phases: Beginning of Life (BOL) including design and manufacturing, Middle of Life (MOL) including usage and maintenance and End of Life (EOL) including recycling, disposal or other options. Closed-Loop PLM extends the meaning of PLM in order to close the loop of the information among the different lifecycle phases. The idea is that information of MOL could be used at the EOL stage to support deciding the most appropriate EOL option (especially to make decision for re-manufacturing and re-use) and combined with the EOL information it could be used as feedback in the BOL for improving the new generations of the product. Several PLM models have been developed utilising various technologies and methods towards providing aspects of the Closed-Loop PLM concept. Ontologies are rapidly becoming popular in various research fields. There is a tendency both in converting existing models into ontology-based models, and in creating new ontology-based models from scratch. The aim of this dissertation is to include the advantages and features provided by the ontologies into PLM models towards achieving Closed-Loop PLM. Hence, an ontology model of a Product Data and Knowledge Management Semantic Object Model for PLM has been developed. The transformation process of the model into an ontology-based one, using Web Ontology Language-Description Logic (OWL-DL), is described in detail. The background and the motives for converting existing PLM models to ontologies are also provided. The new model facilitates several of the OWL-DL capabilities, while maintaining previously achieved characteristics. Furthermore, case studies based on various application scenarios, are presented. These case studies deal with data integration and interoperability problems, in which a significant number of reasoning capabilities is implemented, and highlight the utilisation of the developed model. Moreover, in this work, a generic concept has been developed, tackling the time treatment in PLM models. Time is the only fundamental dimension which exists along the entire life of an artefact and it affects all artefacts and their qualities. Most commonly in PLM models, time is an attribute in parts such as "activities" and "events" or is a separate part of the model ("four dimensional models"). In this work the concept is that time should not be one part of the model, but it should be the basis of the model, and all other elements should be parts of it. Thus, we introduce the "Duration of Time concept". According to this concept all aspects and elements of a model are parts of time. Case studies demonstrate the applicability and the advantages of the concept in comparison to existing methodologies

An Ontology-based model for providing Semantic Maintenance.

International audienceMaintenance is becoming more and more crucial in Asset Lifecycle Management information models. Issues such as collecting, handling and using the asset data produced during its lifecycle in a lean and efficient manner are on top of today's research. Customer satisfaction, compliance with environmental friendly legislation, product quality, high performance and reliability are only a few of the benefits improved maintenance methods and tools may provide to enterprises. In this work we combine the benefits of two previous developed models and we develop a model for Semantic Maintenance. The first model we are based on is the PROMISE semantic object model which was made for supporting Closed-Loop Product Lifecycle Management. The second model is the semantic model of e-maintenance developed in PROTEUS project. The new model described in this paper is named “SMAC-Model”. Its aim is to provide advanced maintenance services as well as feedback for the Beginning of Life and input for End of Life. The model is generic and may be used in various Asset Lifecycle Management cases. It is developed to facilitate complex physical assets and to work in industrial environment

Conceptual Framework for a Data Model to Support Asset Management Decision-Making Process

Part 4: Product and Asset Life Cycle Management in Smart Factories of Industry 4.0International audienceInformation and data management is nowadays a central issue to support the Asset Management (AM) decision-making process. Manufacturing companies have to take different decisions along the asset lifecycle and at different organisational levels, and, to this end, they require proper information and data management. In the literature, besides the crucial role played by information and data, there is evidence of existing gaps, especially related to information management and integration, and transformation of data into useful information. Thus, a conceptual framework is proposed to guide the definition of a data model to fulfil the previously identified gap. Generally, the framework aims at contributing to the improvement of the integration of information along the AM decision-making process. Specifically, it is intended to be aligned with the AM theory and, in particular, its fundamentals defined in the scientific literature and the ISO 5500x body of standards. Overall, thanks to the improvement of the information management and integration along with the AM decision-making, the expectation is to be capable of achieving more value-oriented decisions for the asset lifecycle

An ontology-based approach for Product Lifecycle Management

Ontologies are rapidly becoming popular in various research fields. There is a tendency both in converting existing models into ontologies and in creating new models. In this work we are focusing on Closed-Loop Product Lifecycle Management (PLM) models. An ontology model of a Product Data and Knowledge Management Semantic Object Model for PLM has been developed, with the aim of implementing ontology advantages and features into the model. An initial effort of developing the model into an ontology using Web Ontology Language-Description Logic (OWL-DL) is described in detail and the background and the motives for converting existing PLM models to ontologies is provided. The new model facilitates several of the OWL-DL capabilities, while maintaining previously achieved characteristics. Furthermore, a case study is presented based on application scenarios on the automotive industry. This case study deals with data integration and interoperability problems, in which a significant number of reasoning capabilities is implemented. (C) 2010 Elsevier B.V. All rights reserved

A mereotopological product relationship description approach for assembly oriented design

This paper describes a novel approach for integrated assembly modelling and planning. The main objective is to make assembly information accessible and exploitable by data management systems and computer-aided X tools in order to support product architects and designers. Product information and knowledge as well as the related assembly sequence require a logical foundation in order to be managed consistently and processed proactively. In this context, product relationships are considered and described in the part-whole theory supported by mereology and its extension, mereotopology. Firstly, past and current research work are presented on concurrent product design and assembly sequence planning approaches; existing assembly relational models; and spatio-temporal mereotopology. A background of previous research work is also included in order to highlight the current research problem. Then, a mathematical description approach of product relationships based on mereotopology and temporal relationships is introduced. Finally, an ontological implementation of the proposed description using OWL DL and SWRL is presented and illustrated in a case study describing a mechanical assembly, enabling hence, reuse and collaborative exploitation of the assembly knowledge in the different product lifecycle phases. (C) 2012 Elsevier Ltd. All rights reserved