Multi-aspect Ontology for Semantic Interoperability in PLM: Analysis of Possible Notations

Smirnov, Alexander; Shilov, Nikolay

doi:10.1007/978-3-030-01614-2_29

Cited by 4 publications

(2 citation statements)

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“…Ontologies serve as machine-readable means of representing the context surrounding the knowledge that is represented in specialised systems in product lifecycle management. They help implement connections and represent interdependencies among departments (Smirnov & Shilov, 2018). An ontology aims to represent the perception of concepts and their relationships as per an individual or of a group of people (Gruber, 1993).…”

Section: Tacit Knowledge Capture In the Product Lifecycle Management Contextmentioning

confidence: 99%

Concept Maps Collaborative Creation in Product Lifecycle Management

2021

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One of the greatest challenges of effectively managing knowledge in an organization is promoting seamless connections of operations between departments, the Product Lifecycle Management paradigm. It is also a paradigm that fosters organizational adaptability and quick change in production. Historically, information systems supporting operations have been developed with a specific department's culture in background. Due to this legacy, connecting data, information systems and people across the product lifecycle is an ongoing puzzle for organizations. Theorists and practicians agree on the need to include employees' expertise and vision in this process. However, this involves multiple perspectives and needs that are different but equally valid make. This study explores a tacit knowledge capture tool to be used as a means to voice the interaction and negotiation among employees. Through its influence on ontologies, concept maps collaborative creation can provide a usability tool focused on meaning throughout the product lifecycle. A literature review of the challenges involved and of the proposed tool is presented, followed by a use case and concluded with recommendations drawn from theory and practice.

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Section: Tacit Knowledge Capture In the Product Lifecycle Management Contextmentioning

confidence: 99%

Concept Maps Collaborative Creation in Product Lifecycle Management

2021

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“…Today, product lifecycle management (PLM) automation is devoted a significant attention [1][2][3][4]. In previous publications we considered intelligent IT support for the entire PLM cycle [5] and the PLM stage of marketing [6,7]. One of the possible results of this process is "Digital Customer Journey" [8] standing for complete IT support of the customer at all PLM stages from finding the supplier through product configuration and sales to product usage and disposal (fig.…”

Section: Introductionmentioning

confidence: 99%

Free Text Customer Requests Analysis: Information Extraction Based on Fuzzy String Comparison

Smirnov¹,

Shilov²,

Evers³

et al. 2020

Product Lifecycle Management Enabling Smart X

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Complex systems (such as automation systems), from here on referred as "products" are usually difficult for customers to specify since there are a lot of parameters to be defined and the customer should perfectly know what is really needed and important for the supplier in order to provide for a proper system. As a result, creating forms and templates for the customer request specification entry helps only for relatively simple tasks and the completely digital request acquisition and processing is still a matter of future work. Currently, the original request specification comes from the customer in various ways (texts, images, diagrams, a phone or a direct talk to the company's sales representative) and the results of the analysis of this specification are often forwarded further to the back-office in a form of free or semi-structured text written in natural language. Since this text is the main source of information about the customer request, it is very important to extract as much information from it as possible. The paper reports the research and development work on semantic text analysis for information extraction from customer requests written in natural language. The core of the work is development of methods for finding a pre-defined list of terms (product parameters that are important for the order specification) in a fuzzy (similarity-based) manner with the help of synonym dictionaries. The results are illustrated on a case study from the automation equipment producer Festo SE & Co KG.

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