Tracing the interrelationship between key performance indicators and production cost using bayesian networks

Suraj Panicker, Hari Nagarajan, Hossein Mokhtarian, Azarakhsh Hamedi, Ananda Chakraborti, Eric Coatanea, Karl Haapala, Kari Koskinen

Tutkimustuotos: KonferenssiartikkeliScientificvertaisarvioitu

13 Sitaatiot (Scopus)
114 Lataukset (Pure)

Abstrakti

Key performance indicators (KPIs) are used to monitor and improve production cost, quality, and time. A plethora of manufacturing KPIs are currently in use, with others continually being developed to meet organizational needs. However, obtaining the optimum KPI values at different organizational levels is challenging due to the complex interactions between manufacturing decisions, variables, and the desired targets. A Bayesian network is developed to characterize the interrelationships between manufacturing decisions and variables, selected KPI, and total production cost. For an additive manufacturing case, the approach enables appropriate KPI value estimation for achieving desired production cost targets in a manufacturing enterprise.
AlkuperäiskieliEnglanti
Otsikko52nd CIRP Conference on Manufacturing Systems (CMS)
AlaotsikkoLjubljana, Slovenia, June 12-14, 2019
ToimittajatPeter Butala, Edvard Govekar, Rok Vrabic
KustantajaElsevier
Sivut500-505
Sivumäärä6
Vuosikerta81
DOI - pysyväislinkit
TilaJulkaistu - 2019
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaCIRP Conference on Manufacturing Systems -
Kesto: 1 tammik. 2000 → …

Julkaisusarja

NimiProcedia CIRP
Vuosikerta81
ISSN (elektroninen)2212-8271

Conference

ConferenceCIRP Conference on Manufacturing Systems
Ajanjakso1/01/00 → …

Julkaisufoorumi-taso

  • Jufo-taso 1

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