Ana Milicic

Towards the Definition of Domain Concepts and Knowledge through the Application of the User Story Mapping Method

The context and problem of identifying and thereafter representing, analyzing and managing information and knowledge about an organization has always been very crucial to achieve business goals in an efficient and flexible way. Particularly in a PLM context, the issue of information overload is growing in importance. An emergent challenge consists in providing a context-driven access to federated information and knowledge and fostering cross-discipline collaborations between actors to improve quality in product development. This paper highlights key issues for knowledge definition and representation. We propose a bottom-up approach based on the User Story Mapping method (USM). This method is user-centric and leads to the definition of current and/or expected scenarios and processes along with a collaboratively agreed vision. Common concepts and viewpoints are therefore derived and generalized through a process of merging defined roles, activities and usages sequences with a focus on the product content. This bottom-up approach provides a federated and common understanding of information throughout the industrial product and process lifecycle; which combined with appropriate tools and methods, such as questionnaires, standards specifications, knowledge based approaches, etc. results in the definition of the knowledge network and domain and therefore improves capabilities for sharing and reusing this knowledge in collaborative product development. The proposed approach is applied in the context of the FP7 European project LinkedDesign (Linked Knowledge in Manufacturing, Engineering and Design for Next-Generation Production) based on three application scenarios.

Specialization of a Fundamental Ontology for Manufacturing Product Lifecycle Applications: A Case Study for Lifecycle Cost Assessment

This paper aims to study the specialization of a fundamental ontology describing manufacturing product lifecycle applications. This specialization is conducted through a case study of an Italian company. On the one hand this specialization is meant to define a specific ontology for LCC applications and on the other hand it aims to validate the mapping with the fundamental ontology implemented for manufacturing product lifecycle applications.

Design of Fundamental Ontology for Manufacturing Product Lifecycle Applications

In today’s world of fast manufacturing, high quality demands and highly competitive markets, it has become vital for companies to be able to extract knowledge from their operating data, to manage and to reuse this knowledge in efficient and automated manner. Ontology has proven to be one of the most successful methods in fulfilling this demand and to this day, it has been applied in number of scenarios within companies of all scales. The most appealing features of the ontology are well-defined structure of the knowledge organization; being machine understandable enables automatic reasoning and inference and finally, well defined semantics enables easy interoperability and design of the plug-in modules. Still, one key downfall of ontology is that it usually has to be manually designed from the beginning for each new use-case. This requires highly specialized knowledge experts working closely with the domain experts for, sometimes, significant period of time. In this paper we propose LinkedDesign solution for described issues, as an example of design of fundamental ontology which can be easily adjusted and adopted for different production systems, thus eliminating the need for repetition of entire design process for every individual company. We also discuss and point to a new and challenging fields of research emerging from application of ontology into manufacturing companies, mainly concerning rapidly growing amounts of knowledge which are beginning to exceed human ability to process it.

PLM Ontology Exploitation through Inference and Statistical Analysis A Case Study for LCC

Abstract In a time of growing complexity and amount of a product related data, ontology has show to be an efficient and convenient method for structuring and modeling the domain of interest. It provides a clear picture of all relevant concepts, their relationships and the rules they follow. It is a structured, centralized data base, that allows fast updates and prevents redundancy. Still, fast, real-time functions of todays companies impose additional requirements on a operational domain model and in this paper, we argue that product life-cycle management (PLM) ontology can meet those requirements. In that sense, tools that we propose for ontology exploitation are mainly inference on ontology rules on one side, and ontology instances extraction for the purpose of visualization and data mining on the other side. We implement these tools for the case of manufacturing company on a real life data provided and analyze benefits from the aspect of non-expert end-user. This research is done as a part of FP7 project LinkedDesign.

Linked Data Exploration in Product Life-Cycle Management

Product Life Cycle Management (PLM) strategies have been proven as recommended approach for handling, planning and decision making regarding all aspects of products different life cycle stages. As this domain includes number of actors, system platforms and technologies, gathering information and handling knowledge often emerges as challenging problem. In this paper we propose a methodology to support a PLM approach taking advantage from the emerging semantic web technologies and the underlying paradigm of Linked Data. The main purpose of this methodology is twofold. First, it aims at providing a semantic model for handling different data sources and data types, structuring thus information from all stages of a product life cycle. Second, it extends reasoning mechanisms offered by semantic technologies, to conduct comparative and in-depth data analysis based on data mining and pattern discovery.

An autonomous system for PLM domain data exploitation

In this article, a system for automated data analysis and data modelling is presented. It is a well-known fact that a fully automated, data independent data mining system cannot be designed. It is proposed here that data from the product lifecycle management (PLM) domain can be successfully modelled mathematically by exploiting the advantages of having a semantic model of data, relaxed time constraints and by allowing sub-optimal accuracy. A data mining procedure is followed through in detail and, for each step, it is argued how the proposed assumptions tackle the challenges of automation. Finally, an industrial use case is presented to demonstrate the value gained from such a system.

From English to RDF - A Meta-Modelling Approach for Predictive Maintenance Knowledge Base Design

Ever growing complexity of the information domains that are relevant for product life cycle management is pushing researchers to invest efforts into creating an abstract modelling techniques in order to structure the available knowledge. Ontology showed to be a convenient method for build such structures and number of domain specific ontologies has been developed in recent years. In this paper, we propose a meta-modelling approach that provides a guided, step-by-step solution for ontology design. Contribution is tested through an example of ontology for predictive maintenance.

Chapter 3 – LEAP Semantics

In this chapter the ontology objectives, benefits, and main methodologies and tools for ontology design are presented. The LEAP semantic model is proposed, which is based on the design of an upper ontology describing the LEAP domain and its specialization to the three industrial use-cases: Volkswagen, COMAU, and Aker Solutions. The specialization process consists of the creation of application ontologies that are specific to each use-case requirements and their mapping with the upper ontology. Finally, we describe how the semantic model interacts with the LEAP services.

LEAP Use Cases

Abstract Within the LinkedDesign project, all of the concepts and components that have been developed are evaluated and proven using three representative use case scenarios. Although all of the use cases address applications in the products’ BOL life phase (namely design and manufacturing), they are at the same time very diverse and require us to focus on different aspects of manufacturing, such as metrology systems, life cycle cost estimation and knowledge management and reuse. This shows the usability of LEAP platform solutions and the generality of its modules. In this chapter, the use cases will be described and we will explain how the LEAP platform is being exploited for given tasks.

User Story Mapping-Based Method for Domain Semantic Modeling

User story mapping (USM) for domain modeling is a method derived from the software functionality definition domain, which puts the end-user and his perspective in focus. The domain of interest is defined through the collection of user activities, which indirectly gathers all actors, resources, processes and overall dynamics of the domain. USM is a manual procedure that is conducted between the semantics expert and the domain expert, and can sometimes require a number of time-consuming iterations. The ADOxx metamodeling platform facilitated the development of a USM digital tool which provides enhanced performance and visual environment.