Schedule instability, service level and cost in a material requirements planning system

被引:12
作者
Bai, X [1 ]
Davis, JS
Kanet, JJ
Cantrell, S
Patteson, JW
机构
[1] Virginia State Univ, Dept Informat Syst & Decis Sci, Petersburg, VA 23806 USA
[2] Clemson Univ, Dept Management, Clemson, SC 29634 USA
关键词
D O I
10.1080/00207540110119973
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The primary objective of this work was to evaluate how four important system parameters (schedule frozen interval, schedule re-planning interval, safety stock and lot-sizing rules) affect material requirements planning (MRP) system performance in terms of schedule instability, total cost and service level, considering different levels of two operating factors: the lead-times of items in the product structure, and the accuracy of the demand forecast. The research design employed a simulation model in Visual Basic run on a personal computer. This study concluded that all system parameters and operating factors significantly influence the three performance measures. Frozen interval, forecast accuracy, and lead-time have the most significant impact on system instability and total cost. Forecast accuracy, safety stock, and lead-time have the most impact on service level. Due to the interactions among system parameters and operating factors, there are no win-win principles to set parameters in order to achieve better system performance under all operating conditions. However, the results help determine appropriate system parameters under particular operating conditions. For example, when the forecast is more accurate, system instability is relatively insensitive to the size of re-planning interval, but frequent re-planning helps reduce total cost and improve service level.
引用
收藏
页码:1725 / 1758
页数:34
相关论文
共 22 条
[1]  
[Anonymous], PRODUCTION INVENTORY
[2]  
Baker K.R., 1977, DECISION SCI, V8, P19, DOI [DOI 10.1111/J.1540-5915.1977.TB01065.X, 10.1111/j.1540-5915.1977.tb01065.x]
[3]  
Biggs J. R., 1979, Decision Sciences, V10, P96, DOI 10.1111/j.1540-5915.1979.tb00010.x
[4]  
Biggs J. R., 1982, Decision Sciences, V13, P570, DOI 10.1111/j.1540-5915.1982.tb01183.x
[5]   A COMPARISON OF STRATEGIES TO DAMPEN NERVOUSNESS IN MRP SYSTEMS [J].
BLACKBURN, JD ;
KROPP, DH ;
MILLEN, RA .
MANAGEMENT SCIENCE, 1986, 32 (04) :413-429
[6]   MRP SYSTEM NERVOUSNESS - CAUSES AND CURES [J].
BLACKBURN, JD ;
KROPP, DH ;
MILLEN, RA .
ENGINEERING COSTS AND PRODUCTION ECONOMICS, 1985, 9 (1-3) :141-146
[7]  
CHU CH, 1989, OMEGA, V16, P325
[8]  
Kadipasaoglu S. N., 1995, Journal of Operations Management, V13, P193, DOI 10.1016/0272-6963(95)00023-L
[9]  
Krupp J. A. G., 1997, Production and Inventory Management Journal, V38, P11
[10]   OPTIMAL FORECAST BIASING IN THEORETICAL INVENTORY MODELS [J].
LEE, TS ;
SHIH, W .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 1989, 27 (05) :809-830