Life-Cycle Oriented Risk Assessment Using a Monte Carlo Simulation

State of the art mechatronic systems are complex assemblies of various parts and sub-systems. In such an interconnected system, even relatively cheap parts can have a major impact on the overall performance due to unexpected failure. Hence, lifecycle management has major implications on the successf...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Züst, Simon, Huonder, Michael, West, Shaun, Stoll, Oliver
Format: Artikel
Sprache:ger
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title
container_volume
creator Züst, Simon
Huonder, Michael
West, Shaun
Stoll, Oliver
description State of the art mechatronic systems are complex assemblies of various parts and sub-systems. In such an interconnected system, even relatively cheap parts can have a major impact on the overall performance due to unexpected failure. Hence, lifecycle management has major implications on the successful modification of existing products. Potential savings due to changes in production and procurement must be compared to the implied risk of products failing in the field due to these changes. This work documents a generic approach for risk assessment based on the distribution of the expected savings and incident costs over the whole lifecycle. To do so, a stochastic model is introduced to quantify the expected savings and costs given a non-risk-free product modification. Using a Monte Carlo simulation, the effects of uncertainty are incorporated into the risk management. The model and simulation are deployed within an industrial use case. The application demonstrates both the appropriateness of the tool and its useability.
doi_str_mv 10.5281/zenodo.6343954
format Article
fullrecord <record><control><sourceid>luzern_LYEOE</sourceid><recordid>TN_cdi_luzern_lory_v2_6343954</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>6343954</sourcerecordid><originalsourceid>FETCH-luzern_lory_v2_63439543</originalsourceid><addsrcrecordid>eNpjYBAzNNAzNbIw1K9KzctPydczMzYxtjQ14WRw8slMS9V1rkzOSVXwL8pMzStJTVEIyizOVnAsLk4tLs4FiiiEFmfmpSskKvjmA6UVnBOLcvIVgjNzS3MSSzLz83gYWNMSc4pTeaE0N4Osm2uIs4duTmlValFefE5-UWV8mVE81E5jQvIACus1jA</addsrcrecordid><sourcetype>Institutional Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Life-Cycle Oriented Risk Assessment Using a Monte Carlo Simulation</title><source>LORY (Lucerne Open Repository)</source><creator>Züst, Simon ; Huonder, Michael ; West, Shaun ; Stoll, Oliver</creator><creatorcontrib>Züst, Simon ; Huonder, Michael ; West, Shaun ; Stoll, Oliver</creatorcontrib><description>State of the art mechatronic systems are complex assemblies of various parts and sub-systems. In such an interconnected system, even relatively cheap parts can have a major impact on the overall performance due to unexpected failure. Hence, lifecycle management has major implications on the successful modification of existing products. Potential savings due to changes in production and procurement must be compared to the implied risk of products failing in the field due to these changes. This work documents a generic approach for risk assessment based on the distribution of the expected savings and incident costs over the whole lifecycle. To do so, a stochastic model is introduced to quantify the expected savings and costs given a non-risk-free product modification. Using a Monte Carlo simulation, the effects of uncertainty are incorporated into the risk management. The model and simulation are deployed within an industrial use case. The application demonstrates both the appropriateness of the tool and its useability.</description><identifier>DOI: 10.5281/zenodo.6343954</identifier><language>ger</language><publisher>Zenodo</publisher><subject>lifecycle-management; risk management; Monte Carlo simulation</subject><creationdate>2021-12</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><orcidid>0000-0001-7487-1827 ; 0000-0002-8042-1459 ; 0000-0002-1918-3842</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,780,27859</link.rule.ids><linktorsrc>$$Uhttps://zenodo.org/record/6343954$$EView_record_in_LORY_(Lucerne_Open_Repository)$$FView_record_in_$$GLORY_(Lucerne_Open_Repository)$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Züst, Simon</creatorcontrib><creatorcontrib>Huonder, Michael</creatorcontrib><creatorcontrib>West, Shaun</creatorcontrib><creatorcontrib>Stoll, Oliver</creatorcontrib><title>Life-Cycle Oriented Risk Assessment Using a Monte Carlo Simulation</title><description>State of the art mechatronic systems are complex assemblies of various parts and sub-systems. In such an interconnected system, even relatively cheap parts can have a major impact on the overall performance due to unexpected failure. Hence, lifecycle management has major implications on the successful modification of existing products. Potential savings due to changes in production and procurement must be compared to the implied risk of products failing in the field due to these changes. This work documents a generic approach for risk assessment based on the distribution of the expected savings and incident costs over the whole lifecycle. To do so, a stochastic model is introduced to quantify the expected savings and costs given a non-risk-free product modification. Using a Monte Carlo simulation, the effects of uncertainty are incorporated into the risk management. The model and simulation are deployed within an industrial use case. The application demonstrates both the appropriateness of the tool and its useability.</description><subject>lifecycle-management; risk management; Monte Carlo simulation</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>LYEOE</sourceid><recordid>eNpjYBAzNNAzNbIw1K9KzctPydczMzYxtjQ14WRw8slMS9V1rkzOSVXwL8pMzStJTVEIyizOVnAsLk4tLs4FiiiEFmfmpSskKvjmA6UVnBOLcvIVgjNzS3MSSzLz83gYWNMSc4pTeaE0N4Osm2uIs4duTmlValFefE5-UWV8mVE81E5jQvIACus1jA</recordid><startdate>20211221</startdate><enddate>20211221</enddate><creator>Züst, Simon</creator><creator>Huonder, Michael</creator><creator>West, Shaun</creator><creator>Stoll, Oliver</creator><general>Zenodo</general><scope>LYEOE</scope><orcidid>https://orcid.org/0000-0001-7487-1827</orcidid><orcidid>https://orcid.org/0000-0002-8042-1459</orcidid><orcidid>https://orcid.org/0000-0002-1918-3842</orcidid></search><sort><creationdate>20211221</creationdate><title>Life-Cycle Oriented Risk Assessment Using a Monte Carlo Simulation</title><author>Züst, Simon ; Huonder, Michael ; West, Shaun ; Stoll, Oliver</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-luzern_lory_v2_63439543</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>ger</language><creationdate>2021</creationdate><topic>lifecycle-management; risk management; Monte Carlo simulation</topic><toplevel>online_resources</toplevel><creatorcontrib>Züst, Simon</creatorcontrib><creatorcontrib>Huonder, Michael</creatorcontrib><creatorcontrib>West, Shaun</creatorcontrib><creatorcontrib>Stoll, Oliver</creatorcontrib><collection>LORY (Lucerne Open Repository)</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Züst, Simon</au><au>Huonder, Michael</au><au>West, Shaun</au><au>Stoll, Oliver</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Life-Cycle Oriented Risk Assessment Using a Monte Carlo Simulation</atitle><date>2021-12-21</date><risdate>2021</risdate><abstract>State of the art mechatronic systems are complex assemblies of various parts and sub-systems. In such an interconnected system, even relatively cheap parts can have a major impact on the overall performance due to unexpected failure. Hence, lifecycle management has major implications on the successful modification of existing products. Potential savings due to changes in production and procurement must be compared to the implied risk of products failing in the field due to these changes. This work documents a generic approach for risk assessment based on the distribution of the expected savings and incident costs over the whole lifecycle. To do so, a stochastic model is introduced to quantify the expected savings and costs given a non-risk-free product modification. Using a Monte Carlo simulation, the effects of uncertainty are incorporated into the risk management. The model and simulation are deployed within an industrial use case. The application demonstrates both the appropriateness of the tool and its useability.</abstract><pub>Zenodo</pub><doi>10.5281/zenodo.6343954</doi><orcidid>https://orcid.org/0000-0001-7487-1827</orcidid><orcidid>https://orcid.org/0000-0002-8042-1459</orcidid><orcidid>https://orcid.org/0000-0002-1918-3842</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext_linktorsrc
identifier DOI: 10.5281/zenodo.6343954
ispartof
issn
language ger
recordid cdi_luzern_lory_v2_6343954
source LORY (Lucerne Open Repository)
subjects lifecycle-management
risk management
Monte Carlo simulation
title Life-Cycle Oriented Risk Assessment Using a Monte Carlo Simulation
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-10T14%3A00%3A53IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-luzern_LYEOE&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Life-Cycle%20Oriented%20Risk%20Assessment%20Using%20a%20Monte%20Carlo%20Simulation&rft.au=Z%C3%BCst,%20Simon&rft.date=2021-12-21&rft_id=info:doi/10.5281/zenodo.6343954&rft_dat=%3Cluzern_LYEOE%3E6343954%3C/luzern_LYEOE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true