An interoperable semantic service toolset with domain ontology for automated decision support in the end-of-life domain

Abstract

In product-diverse, end-of-life (EoL) production lines the relevant markets, competitors and customer bases continuously change as new products are processed. The resale market itself changes with the influx of new products, as well as hardware and software discontinuations. Competitive business decision making is often performed by a human operator and may not be timely or fully informed. These are decisions such as whether to perform a high cost repair or recycle a product or whether to use a batch of parts in repair or sell them on can be used to optimise product life-cycle management (PLM) and profit margins. A real-time decision making capability can reduce the risk of performing non-profitable processing. The novel contribution of this work is an interoperable semantic decision support toolset that is necessary to enable a capability for timely EoL decisions based on complete knowledge on profitability, predicted pricing and cost-of-production. Many decision support systems have been proposed for the EoL domain, but a lack of interoperability and use of unstructured knowledge bases has led to decisions based on knowledge that is not up to date. Using formalised, semantic technologies offers sustainable decision making in this volatile and increasingly competitive domain.

Revisão sistemática da literatura sobre ontologias para modelos de negócio e processos na pecuária de corte

“…Ontologias empregadas em níveis estratégicos foram usadas para desenvolver sistemas de apoio a decisão (e.g. (Pease et al, 2020)) e ontologias empregadas em níveis tático e operacional se preocupam com a definição dos processos de negócio da empresa (e.g. (Zou et al, 2019;Afify et al, 2017;Yingbo e Xia, 2019)).…”

“…Não há descrição de aplicação prática da ontologia a nenhum modelo ou aplicação específicos. Pease et al (2020) desenvolve uma ontologia de domínio projetada para um sistema automatizado de apoio à tomada de decisão para produtos end-of-life, que são produtos que atingiram o final de sua vida útil e serão descontinuados. A motivação para o trabalho é o fato de que decisões sobre continuidade de produtos são tomadas por pessoas que podem não ter total ciência das informações necessárias para aquela tomada de decisão, podendo não ser efetivadas corretamente ou em tempo hábil.…”

“…Todos os trabalhos listados na Tabela 3 realizaram verificação de consistência em suas ontologias, com exceção de (Da Silva et al, 2019). Note-se que, em (Pease et al, 2020), duas ferramentas de inferência foram usadas para verificação de consistência e, portanto, esse trabalho aparece em duas linhas da tabela. As inferências realizadas nos trabalhos analisados incluem o processamento de operações bancárias (Yingbo e Xia, 2019), a extração de informações sobre saúde animal (Da Silva et al, 2019) e sobre plantações (Pani e Mishra, 2016;Walisadeera et al, 2015) e, por fim, estimativas de risco e lucro em sistema de apoio a decisão (Pease et al, 2020).…”

A dynamic domain ontology model based on the optimal matching method of network news

“…proposed an ontology-based data recommendation system for social networks, which made use of ontologies to lter and update nodes [22]. Pease et al proposed the EoL Domain Ontology for automated decision support in end-life domains [23]. Georgescu designed the DO as the structure of the natural language processing model and proposed the ML-based NLP model for cybersecurity [24].…”

Decision Support Systems to Promote Health and Well-Being of People During Their Working Age: The Case of the WorkingAge EU Project

“…In [21], a DSS is described for workers with disabilities who are more sensitive for stress at work and for the injuries connected with non-adequate workplaces. Based on ontologies, many DSSes have been developed for business decision making, or for cyber-physical systems [17,18], which are very similar to our application area. In fact, these systems tightly integrate software, human, and physical components with the need to satisfy constraints on performance and safety of the monitored activities, exhibiting a high degree of automation for the management of their functionalities and decision making processes.…”