Details
| Titel in Übersetzung | Entwicklung eines fallbasierten Expertensystems für das Störungsmanagement in Fahrerlosen Transportsystemen |
|---|---|
| Originalsprache | Englisch |
| Fachzeitschrift | Logistics Journal |
| Jahrgang | 2019 |
| Publikationsstatus | Veröffentlicht - 2019 |
| Extern publiziert | Ja |
Abstract
Automated guided vehicle systems (AGVS) are an essential part of modern intralogistics. So far, the major part of the design cycle (implementation and opera-tion) of an AGVS demands human expertise. Especially, the manually executed management of occurring disturbances leads to high maintenance costs since it often requires the consultation of experts. Therefore, the following paper discusses the development of a Case-Based Reasoning (CBR) expert system for assisting the disturbance management in AGVS. The development is sectioned into three major parts: (1) generation of the case-base, (2) development of the algorithms for case retrieval, case adaptation and retaining new cases and (3) the validation of the expert system. The generation of the case-base and the training data for the expert system is done by simulating the real production layout of a German white good manufacturer using the simulation environment Visual Components. The solutions for the simulated disturbances as well as the adaptation algorithms are based on knowledge extracted from system experts.
Schlagwörter
- Automated guided vehicle systems, Case-Based Reasoning, Disturbance management, Expert systems
ASJC Scopus Sachgebiete
- Betriebswirtschaft, Management und Rechnungswesen (insg.)
- Management-Informationssysteme
- Ingenieurwesen (insg.)
- Steuerungs- und Systemtechnik
- Entscheidungswissenschaften (insg.)
- Managementlehre und Operations Resarch
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in: Logistics Journal, Jahrgang 2019, 2019.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Development of a Case-Based Reasoning expert system for the disturbance management in automated guided vehicle systems
AU - Soltani, Ali
AU - Stonis, Malte
AU - Overmeyer, Ludger
N1 - Funding information: The IGF project 19327 N of the Federal Logistics Association (BVL) are funded via the German Federation of Industrial Research Associations (AiF) in the program of Industrial Collective Research (IGF) by the Federal Ministry for Economic Affairs and Energy (BMWi) based on a decision of the German Bundestag.
PY - 2019
Y1 - 2019
N2 - Automated guided vehicle systems (AGVS) are an essential part of modern intralogistics. So far, the major part of the design cycle (implementation and opera-tion) of an AGVS demands human expertise. Especially, the manually executed management of occurring disturbances leads to high maintenance costs since it often requires the consultation of experts. Therefore, the following paper discusses the development of a Case-Based Reasoning (CBR) expert system for assisting the disturbance management in AGVS. The development is sectioned into three major parts: (1) generation of the case-base, (2) development of the algorithms for case retrieval, case adaptation and retaining new cases and (3) the validation of the expert system. The generation of the case-base and the training data for the expert system is done by simulating the real production layout of a German white good manufacturer using the simulation environment Visual Components. The solutions for the simulated disturbances as well as the adaptation algorithms are based on knowledge extracted from system experts.
AB - Automated guided vehicle systems (AGVS) are an essential part of modern intralogistics. So far, the major part of the design cycle (implementation and opera-tion) of an AGVS demands human expertise. Especially, the manually executed management of occurring disturbances leads to high maintenance costs since it often requires the consultation of experts. Therefore, the following paper discusses the development of a Case-Based Reasoning (CBR) expert system for assisting the disturbance management in AGVS. The development is sectioned into three major parts: (1) generation of the case-base, (2) development of the algorithms for case retrieval, case adaptation and retaining new cases and (3) the validation of the expert system. The generation of the case-base and the training data for the expert system is done by simulating the real production layout of a German white good manufacturer using the simulation environment Visual Components. The solutions for the simulated disturbances as well as the adaptation algorithms are based on knowledge extracted from system experts.
KW - Automated guided vehicle systems
KW - Case-Based Reasoning
KW - Disturbance management
KW - Expert systems
UR - http://www.scopus.com/inward/record.url?scp=85084698774&partnerID=8YFLogxK
U2 - 10.2195/lj_Proc_soltani_en_201912_01
DO - 10.2195/lj_Proc_soltani_en_201912_01
M3 - Article
AN - SCOPUS:85084698774
VL - 2019
JO - Logistics Journal
JF - Logistics Journal
SN - 1860-7977
ER -