File(s) under embargo

Reason: Publisher requirement.

1

month(s)

12

day(s)

until file(s) become available

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

journal contribution
posted on 21.01.2021, 16:45 by Sarogini Pease, Richard Sharpe, Kate Van-Lopik, Eleni Tsalapati, Paul Goodall, Robert I.M. Young, Paul Conway, Andrew West
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. These decisions 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 enables 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.

Funding

Adaptive Informatics for Intelligent Manufacturing (AI2M)

Engineering and Physical Sciences Research Council

Find out more...

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Published in

Future Generation Computer Systems

Volume

112

Pages

848 - 858

Publisher

Elsevier

Version

AM (Accepted Manuscript)

Rights holder

© Elsevier

Publisher statement

This paper was accepted for publication in the journal Future Generation Computer Systems and the definitive published version is available at https://doi.org/10.1016/j.future.2020.06.008.

Acceptance date

05/06/2020

Publication date

2020-06-19

Copyright date

2020

ISSN

0167-739X

eISSN

1872-7115

Language

en

Depositor

Dr Sarogini Pease. Deposit date: 19 January 2021

Exports