Delivery Chains, Multivariate Control Charts, Economic Statistical Design and Genetic Algorithms.
Abstract :
[en] The theory of the delivery chain considers the delivery of goods and services to
customers within a specific time interval. Nowadays, organizations are focusing to satisfy
their customers’ demands not only to meet the expectations for products quality but also
in delivery times through managing delivery chains. Obviously it is desirable that a
company has minimum delivery time of goods and services to its customers. Therefore,
establishing economic and reliable control charts for monitoring the key characteristics of
delivery chain is of great importance especially for managers to improve the whole
delivery chains performance. On the other hand, as we shall see in the present paper, the
performance of a delivery chain is multivariate in nature because customers do not
evaluate a delivery performance with a univariate mindset and also there are usually
several production and delivery sites, and variety of different methods of transportation of
goods and services. In this paper, we propose a relatively new application of the
economic statistical design of the multivariate T2 control chart to monitor the delivery
chain performance and it is illustrated through a case study in the TNT express mail in
Iran.
Disciplines :
Quantitative methods in economics & management
Author, co-author :
Faraz, Alireza ; Université de Liège - ULiège > HEC-Ecole de gestion : UER > Statistique appliquée à la gestion et à l'économie
Heuchenne, Cédric ; Université de Liège - ULiège > HEC-Ecole de gestion : UER > Statistique appliquée à la gestion et à l'économie
Saniga, Erwin; Department of Business Administration, University of Delaware, Newark, Delaware
Foster, Earnest; Department of Business Administration, Penn State University, Pennsylvania, USA
Language :
English
Title :
Monitoring delivery chains in a supply chain using multivariate control charts
Publication date :
13 July 2011
Event name :
2th International Symposium on Statistical Process Control