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Semantic Organization of Product Lifecycle Information Through a Modular Ontology INTERNATIONAL JOURNAL OF CIRCUITS, SYSTEMS AND SIGNAL PROCESSING Volume 9, 2015 Semantic organization of product lifecycle information through a modular ontology Giulia Bruno exploited by SMEs. Studies estimated that information Abstract—It is known that one of the main reasons of the success retrieval is not efficient and around 50% of the available of manufacturing enterprises is their ability to design and maintain a knowledge is not stored in information systems [5]. coherent structure to represent their knowledge, especially the small In literature, a recent trend about manufacturing knowledge and medium sized enterprises (SMEs), which are not often organized management is the inclusion of semantic models, both to help to manage information efficiently. Several commercial PLM systems have been developed in the last years to help companies in the company in organizing and sharing their data, and to allow organizing their large amount of data, but they are rarely exploited the easy finding of information and its reuse. In fact, mainly due to the high cost and difficult customization. Recent trends ontologies make it possible to integrate information from in literature focused on the development of semantic knowledge different abstraction levels, and they improve knowledge management systems, both to help companies in organizing and capture and reuse [6]. Several ontologies have already been sharing their data and to allow the easy finding of information and its proposed for knowledge management in manufacturing, but reuse. The aim of this paper is to develop a knowledge management system to structure the product lifecycle knowledge of SMEs based they mainly develop semantic models to grant interoperability on a modular ontology. The modular ontology contains a reference among different systems or they are product-centric ontologies ontology to represent the main concepts with their relationships, and containing very detailed information on product features and several domain-specific ontologies to specialize and enrich the few details about actual product management. reference ontology with specific information. Particularly, this paper From the experience derived from the EU-FP7 amePLM is focused on the specification of the reference ontology with a project, it emerged that one of the main problems of SMEs is manufacturing process ontology module. Some examples of the usage of the system to extract information through SPARQL queries are the lack of a semantic structure to link the different kinds of also presented. information generated about a product during its whole lifecycle. This information has to be easily searchable based Keywords—Information retrieval, knowledge modeling, on criteria different from company to company. Thus, the aim manufacturing systems, semantic model. of this work is to design a more simple tool to support the manufacturing knowledge management, based on a modular I. INTRODUCTION sets of ontologies. LTHOUGH knowledge management systems proved A single reference ontology contains the basic concepts A their applicability and benefits in many domains, the together with the relationships among them, and a set of design and the maintenance of the underlying knowledge base domain-specific ontologies are integrated to extend and is still a complex and costly task [1]. Especially in the specialize the basic concepts. The modular structure of manufacturing domain, the product lifecycle knowledge has to ontologies allow an easy customization to include the specific be carefully organized and stored because unreliable knowledge that is needed time by time by a company. This knowledge prevents the reuse of the results achieved utilizing paper is mainly focused on the specification of the reference human excellence [2]. ontology with the manufacturing processes knowledge. However, companies (especially SMEs) usually do not use a The rest of the paper is organized as follows. Section 2 knowledge management system, thus are not able to efficiently presents the recent works addressing the exploitation of reuse previous information [3]. Furthermore, people who ontologies in manufacturing. Section 3 and Section 4 detail the worked in an enterprise may have very valuable knowledge, development process of the modular ontology at the basis of and when they leave their knowledge is taken away [4]. the proposed knowledge management system. Section 5 Several commercial PLM tools were developed in the last describes the whole architecture of the proposed knowledge years, but they are seen as complex software which need a management system and gives details on its implementation. huge effort to be understood and used, thus are rarely Section 6 shows how the ontology is populated with concrete data and how it is queried to retrieve information. Finally, This work was partially supported by the EU-FP7 research project on Section 7 draws conclusions and states future works. Advanced Platform for Manufacturing Engineering and Product Lifecycle Management (amePLM, contract number 285171). G. Bruno is with the Department of Management and Production II. RELATED WORKS Engineering of Politecnico di Torino, Italy (phone: 00390110907280; fax: Several works focused on the development of semantic 00390110907299; e-mail: [email protected]). ISSN: 1998-4464 16 INTERNATIONAL JOURNAL OF CIRCUITS, SYSTEMS AND SIGNAL PROCESSING Volume 9, 2015 models for specific products or specific lifecycle phases in by integrating a specific manufacturing ontology. order to store information and share it among applications. However, previous works are mainly focused in representing III. MODULAR ONTOLOGY very detailed information about specific aspects of product According to [14], the process to define an ontology starts management for interoperability purpose. For example, [7] from the identification of the set of relevant concepts, then addressed the development of an ontological assembly model proceeds with the organization of concepts in a formal model to allow the interoperability between software platforms. [8] representing the ontology structure, and finally performs the focused on semantic integration of PLM objects based on an implementation of the model in OWL. This procedure was ontology, but they consider only concepts derived from the bill followed to define the reference ontology and then again to of material to create the ontology. [9] proposed an ontology to define each domain-specific ontology. eliminate confusion of semantic concepts in the ship-building industry by using a classification trees. A. Reference ontology Under the FP6 project PROMISE, [10] developed a As described in more details in [22], the set of high level semantic object model for product data and knowledge concepts needed to represent the product lifecycle management in UML language, and then translated that model management knowledge of a company are the following. in EXPRESS language to create a new Product Lifecycle Production item: either a product or a product Management Standard as an extension of STEP. [11] component. Each product can be made of several developed a port-based ontology to represent the intended components, and the same component can be used by exchange of signals, energy, and materials. [12] introduced an different products. Each component can be in turn be approach to support interoperability in product data composed by other components. management, while [13] developed a manufacturing core Characteristic: a material, a functional characteristic or a physical characteristic (e.g., height, length, width, weight, ontology model to integrate design and manufacturing etc) which refers to a production item. computer-based systems. [14] showed the benefits of applying Customer: the reference person or company who ordered ontologies to support knowledge sharing in PLM with a focus a product. on assembly processes. Also approaches to develop a Activity: an action executed during the lifecycle of a communication interface for different design support systems product by one or more resources, which has one or more to share platform independent product, process and system files in input and produces one or more files in output. related knowledge were proposed [15]. Under the FP7 project File: an electronic source of information, which is iProd, [16] developed a set of ontologies for integrating involved in an activity and refers to one or more engineering data from heterogeneous IT systems. resources or production items. A recent work addresses the definition of a manufacturing Resource: an entity that is involved in the execution of an process ontology to formalize the semantics of manufacturing activity. It can be of two kinds, Person or Machine. capability knowledge [17]. Also the present work has the aim Role: the role of a person denoting his/her skills in the of constructing a scalable and shared manufacturing process company. knowledge system. However, the model proposed in this paper These concepts were organized in a formal model, shown in covers not only the manufacturing processes but all the Fig.1, according to the UML class diagram formalism [23]. information involved in the product lifecycle. In fact, the The Production item class is linked to the Customer class to manufacturing process is only one of the types of activities store the customer who ordered each product. A production done during the product lifecycle, which starts from the design item is also associated to the Characteristic class to store the and ends
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