Engineers distinguish between nominal and actual qualities, a dichotomy that is fundamental to guarantee that physical objects satisfy design requirements. Computational ontologies are broadly exploited across engineering domains, even though they do not attempt at making explicit the intended semantic of the two notions. The purpose of the paper is to present a foundational analysis of nominal and actual qualities to support their robust specification for knowledge representation. Instead of presenting an ontology, we discuss various modeling alternatives on which users can rely to develop their ontologies.

Providing an integrated product-service system (PSS) supported by cyber-physical systems, as a smart solution, is increasingly offered by industrial machinery. In this approach, instead of providing products with after-sale services, the value proposition is mostly based on guaranteeing a trustable operation. As a result, capturing and analyzing information from a machine’s condition during its lifespan becomes an essential part of the smart PSS. Enabling this through lifecycle monitoring, sensing devices are at the core of smart PSS. Thus, the optimal configuration of PSS components is a critical step to ensure the efficiency of the solution. PSS design challenges arise because of the differences between characteristics and specifications of the embedded sensing system and the product. To fulfill this challenge, knowledge extraction and reuse from these domains is crucial during the design process. To do so, a sensor ontology is used as the backbone of the PSS knowledge-based framework. The focus of this paper is on defining the embedded sensing systems tailored to industrial PSS and the use of these systems in providing customized services. As part of the ICP4Life platform, this paper presents a sensing system ontology as a framework to support the smart services in industrial machinery PSS. An industrial use case is conducted to validate the efficiency of the proposed ontology and to show the benefits of the ICP4Life platform to reduce time and cost of PSS development processes.

Abstract:Enterprise production is becoming more and more knowledge oriented nowadays and knowledge management is playing a key role in making commercial profit and maintaining enterprise competence. Knowledge characterization and measurement are the bases of knowledge management, and this paper aims to develop a method for characterizing and measuring knowledge in a comprehensive and practical way. Knowledge in its static state is modelled as a vector, whose values vary with the situation, and changes in state are modelled as a finite state machine.