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In order to reduce time and costs, while maintaining a high level of product quality, effective implementation of systems engineering processes may be beneficial for small and medium-sized enterprises. However, applying a prescriptive generic system engineering standard in the enterprise, without any consideration of the company's organisation, background and context, is inappropriate. Moreover, due to severe resource limitations, the difficulties in following and complying with a standard are even more obvious in SMEs. In this context, this paper explores a framework to help SMEs evaluate the maturity of processes, promote a progressive deployment and standardisation of their engineering processes to manage manufacturing projects, based on the experience and practices underway in SMEs and with reference to international systems engineering standards. Our proposal is to stand by companies to help them evolve their engineering processes by progressively aligning them with systems engineering standards without disrupting the overall organisation and practices of the company. [ABSTRACT FROM AUTHOR]

Within maintenance management activities, engineers need to select maintenance strategies so to carry out the technical maintenance actions. A single equipment is composed of several components with different failure modes. There should be a maintenance strategy for each of them; while some of the components can be run-to-failure applying corrective maintenance, some others cannot afford a failure, and preventive or predictive strategies should be implemented. Selecting and assessing maintenance strategies is a complex task for which information from many sources should be retrieved. Information from a Failure Mode, Effects and Criticality Analysis, a cost–benefit-risk analysis, Computational Maintenance Management Systems, is often used by engineers to select and assess maintenance strategies. A selected strategy is often not evaluated over time to check its effectiveness. The strategy may need adjustments or substituted by a more efficient one, for example, a condition-based strategy substituting a time-based one. To facilitate maintenance strategies selection and assessment, the current study proposes an Ontology model for Maintenance Strategy Selection and Assessment (OMSSA). OMSSA serves as a formal terminology framework in maintenance strategies that can be used to develop smart computational agents that can help in the decision-making process for selecting and assessing maintenance strategies. To facilitate its future reuse and integration with other ontologies in the industrial domain, OMSSA builds following the state-of-the-art in ontology development by using a top-level domain-neutral ontology, the Basic Formal Ontology. [ABSTRACT FROM AUTHOR]

In order to lead successful projects, coordinating the different business units of a company is compulsory. This paper proposes a framework to make companies' practices evolve toward a better alignment of the business units based on their processes, and illustrates it with project management and systems engineering processes. Indeed, all the different organization units intend to serve the common global objective to satisfy the customer needs, and need to closely collaborate during projects. However, work organization in companies often leads to barriers between these stakeholders, with the result of an incoherent decision-making that may compromise project execution. Therefore, the issue of processes alignment from different domains lies at the very heart of ongoing research topics and ranks first among economic and industrial concerns. This paper uses a qualitative approach to show how different business units' processes can be integrated and illustrate this framework by aligning the systems engineering and project management processes within a certain engineering project context. By using the proposed framework, different teams (or even different companies, in a context of distributed enterprise) can align their practices, while also making them evolve toward a better compliance with standards. [ABSTRACT FROM AUTHOR]

One of the main goals of predictive maintenance is to be able to trigger the right maintenance actions at the right moment in time building upon the monitoring of the health status of the concerned systems and their components. As such, it allows identifying incipient faults and forecasting the moment of failure at the earliest stage. Many different data-driven methods are used in such approaches (Naderi and Khorasani in 2017 IEEE 30th Canadian conference on electrical and computer engineering (CCECE), Windsor, ON, IEEE, pp 1–6, 2017. 10.1109/ccece.2017.7946715; Sarkar et al. in J Eng Gas Turbines Power 1338(8):081602, 2011. 10.1115/1.4002877; Svärd et al. in Mech Syst Signal Process 45(1):170–192, 2014. 10.1016/j.ymssp.2013.11.002; Pourbabaee et al. Mech Syst Signal Process 76–77:136–156, 2016. 10.1016/j.ymssp.2016.02.023). This work uses the self-organizing maps (SOMs) or Kohonen map, thanks to its ability to emphasize underlying behavior such as fault modes. An automatic fault mode detection is presented based on a SOM network and the kernel density estimation with as less as possible prior knowledge. The different SOM development steps are presented and the suitable solutions proposed to structure the approach are accompanied by mathematical methods. The generated maps are then used with kernel density analysis to isolate fault modes on them. Finally, a methodology is presented to identify the different fault modes. The work is illustrated with an aircraft jet engines case study. [ABSTRACT FROM AUTHOR]

Obsolescence is the fact that an entity (physical or logical) is becoming outdated or no longer possesses the required level of performance. The objectives of this article are twofold. First, it is intended to contribute to the understanding of obsolescence propagation. Secondly, two supporting approaches for the Identification and Assessment phases are proposed: the House of Obsolescence and the System Obsolescence Criticality Analysis. The former allows the mapping of obsolescence propagation via dependencies, whether imposed changes are desired or imposed, by external actors to the system architecture. Whereas, the objective of the latter is to assign an obsolescence criticality index to the identified risks in order to prioritize them for solution or mitigation determination during the analysis phase. The tools make extensive use of the modeled system knowledge through the application of Systems Engineering. The application of these approaches is presented through an illustrative study. [ABSTRACT FROM AUTHOR]