Improving supply-chain-management based on semantically enriched risk descriptions
No Thumbnail Available
Authors
Author (Corporation)
Publication date
04.10.2012
Typ of student thesis
Course of study
Collections
Type
04B - Conference paper
Editors
Editor (Corporation)
Supervisor
Parent work
Proceedings of 4th Conference on Knowledge Management and Information Sharing (KMIS2012)
Special issue
DOI of the original publication
Link
Series
Series number
Volume
Issue / Number
Pages / Duration
70-80
Patent number
Publisher / Publishing institution
Place of publication / Event location
Barcelona
Edition
Version
Programming language
Assignee
Practice partner / Client
Abstract
To discover risk as early as possible is a major demand of today's supply-chain-risk-management. This includes analysis of internal resources (e.g. ERP and CRM data) but also of external sources (e.g. entries in the Commercial Register and newspaper reports). It is not so much the problem of getting the information as to analyze and evaluate it near-term, cross-linked and forward-looking. In the APPRIS project an Early-Warning-System (EWS) is developed applying semantic technologies, namely an enterprise ontology and an inference engine, for the assessment of procurement risks. The approach allows for integrating data from various information sources, of various information types (structured and unstructured), and information quality (assured facts, news); automatic identification, validation and quantification of risks and aggregation of assessment results on several granularity levels. For representation the graphical user interface of a project partner's commercial supply-management-system is used. Motivating scenario is derived from three business project partners' real requirements for an EWS with special reference to the downstream side of supply chain models, to suppliers' company structures and single sourcing. Research paper: Improving supply-chain-management based on semantically enriched risk descriptions.
Keywords
Subject (DDC)
330 - Wirtschaft
005 - Computer Programmierung, Programme und Daten
005 - Computer Programmierung, Programme und Daten
Event
International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management
Exhibition start date
Exhibition end date
Conference start date
Conference end date
Date of the last check
ISBN
ISSN
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
Peer review of the complete publication
Open access category
License
Citation
EMMENEGGER, Sandro, Emanuele LAURENZINI und Barbara THÖNSSEN, 2012. Improving supply-chain-management based on semantically enriched risk descriptions. In: Proceedings of 4th Conference on Knowledge Management and Information Sharing (KMIS2012). Barcelona. 4 Oktober 2012. S. 70–80. Verfügbar unter: http://hdl.handle.net/11654/9081