Analysis of key performance indicators in a manufacturing plant via fuzzy cognitive maps

被引：2

作者：

Baykasoglu, Adil ^{[1
]}

Atalay, Zehra Nur ^{[2
]}

Golcuk, Ilker ^{[3
]}

机构：

[1] Dokuz Eylul Univ, Fac Engn, Dept Ind Engn, Izmir, Turkey

[2] Dokuz Eylul Univ, Grad Sch Nat & Appl Sci, Izmir, Turkey

[3] Izmir Bakircay Univ, Fac Engn & Architecture, Dept Ind Engn, Izmir, Turkey

来源：

2019 INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS CONFERENCE (ASYU) | 2019年

关键词：

Fuzzy cognitive maps; key performance indicators; performance measurement; criteria interaction;

D O I：

10.1109/asyu48272.2019.8946387

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Companies have to follow key performance indicators (KPIs) for their key objectives, such as increasing of productivity and profit, and reducing cost. Performance measurement and management is also important in this context. The interaction between key performance indicators is often ignored and these interactions are expressed by the subjective evaluations of decision makers. In this study, fuzzy cognitive map (FCM) was trained based on historical data in a production system and connection matrix was formed/analyzed based on the data. KPIs and their values are taken from the company where the present application is performed.

引用

页码：526 / 529

页数：4

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