scholarly journals The impact of Advance Demand Information on the Performance of production/inventory systems

2015 ◽  
Vol 48 (3) ◽  
pp. 1744-1749
Author(s):  
B. Rostami-Tabar ◽  
E. Sahin
Keyword(s):  
Inventory Systems ◽  
Advance Demand Information ◽  
Production Inventory ◽  
Demand Information ◽  
The Impact

The Value of Advance Demand Information in Production/Inventory Systems

2004 ◽  
Vol 126 (1-4) ◽  
pp. 135-157 ◽  
Author(s):  
Fikri Karaesmen ◽  
George Liberopoulos ◽  
Yves Dallery
Keyword(s):  
Inventory Systems ◽  
Advance Demand Information ◽  
Production Inventory ◽  
Demand Information

Modeling the Impact of Merging Capacity in Production-Inventory Systems

2004 ◽  
Vol 50 (8) ◽  
pp. 1082-1094 ◽  
Author(s):  
Ananth V. Iyer ◽  
Apurva Jain
Keyword(s):  
Inventory Systems ◽  
Production Inventory ◽  
The Impact

scholarly journals A COMPARISON OF THE PUSH AND PULL PRODUCTION SYSTEMS AT THEIR OPTI MAL DESIGNS UNDER THE ECONOMIC CONSIDERATION

2017 ◽  
Vol 22 (4) ◽  
pp. 313
Author(s):  
N. Chiadamrong ◽  
P. Kohly
Keyword(s):  
Material Flow ◽  
Production Systems ◽  
Inventory Systems ◽  
Operating Costs ◽  
Shop Floor ◽  
Optimized Design ◽  
Production Inventory ◽  
Fair Comparison ◽  
Push And Pull ◽  
The Impact

The term “push” and “pull” have been used to explain a wide variety of production inventory systems. The distinction refers to a specific attribute, which can be identified by observing the mechanisms for controlling material flow on the shop floor and a specific policy for the management of inventories and production schedules. This paper gives an attempt to compare these systems under their optimal settings under a constraint resource. Two optimal-seeking methods (Taguchi method and Response Surface Methodology) are used to suggest the optimized design of the system under an economic term, which is the profit generated from the system. Then, a fair comparison can be made where each system is operating at its optimal design. Results from this study will reveal an in teresting outcome, letting us know the impact of the push and pull mechanisms on the systems’ operating costs as well as their profits. 

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