A DECISION-MODEL FOR THE ROBOT SELECTION PROBLEM USING ROBUST REGRESSION

被引：18
|
作者：
KHOUJA, M [1 ]
BOOTH, DE [1 ]
机构：
[1] KENT STATE UNIV,COLL BUSINESS ADM,FAC MANAGEMENT,DEPT ADM SCI,KENT,OH 44242
来源：
DECISION SCIENCES | 1991年 / 22卷 / 03期
关键词：
DECISION ANALYSIS; PRODUCTION OPERATIONS MANAGEMENT; AND STATISTICAL TECHNIQUES;
D O I：
10.1111/j.1540-5915.1991.tb01288.x
中图分类号：
C93 [管理学];
学科分类号：
12 ; 1201 ; 1202 ; 120202 ;
摘要：
Industrial robots are increasingly used by many manufacturing firms. The number of robot manufacturers has also increased with many of these firms now offering a wide range of models. A potential user is thus faced with many options in both performance and cost. This paper proposes a decision model for the robot selection problem. The proposed model uses robust regression to identify, based on manufacturers' specifications, the robots that are the better performers for a given cost. Robust regression is used because it identifies and is resistant to the effects of outlying observations, key components in the proposed model. The robots selected by the model become candidates for testing to verify manufacturers' specifications. The model is tested on a real data set and an example is presented. Copyright © 1991, Wiley Blackwell. All rights reserved
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页码：656 / 662
页数：7
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