Title :
An Analytical Performance Modeling Approach for Supply Chain Networks
Author :
Srivathsan, Sandeep ; Kamath, Manjunath
Author_Institution :
Sch. of Ind. Eng. & Manage., Oklahoma State Univ., Stillwater, OK, USA
fDate :
4/1/2012 12:00:00 AM
Abstract :
An analytical performance modeling approach for supply chain networks (SCNs) is developed based on the parametric decomposition method. The upstream flow of demand information and the downstream flow of material are analyzed to derive the arrival process parameters at various inventory points in a SCN. A sequential solution procedure that proceeds from the supplier stage to the retailer stage is then developed. The backorder distribution plays a key role in linking probability calculations between adjacent stages in the SCN model. This sequential procedure can be used to derive the inventory and backorder distributions at various inventory points in the SCN, when specific models are chosen for the SCN components, namely, suppliers, transportation operations, and manufacturers. An example SCN with three suppliers, two manufacturers, and three retailers is used to illustrate the modeling approach. The accuracy of the analytical results is evaluated by comparison with simulation estimates. The approach developed yields computationally efficient and numerically accurate analytical models that are especially useful in addressing SCN design issues.
Keywords :
flow production systems; order processing; probability; supply chain management; SCN model; analytical performance modeling approach; backorder distribution; demand information upstream flow; inventory management; inventory points; material downstream flow; parametric decomposition method; probability calculations; retailer stage; sequential solution procedure; supplier stage; supply chain networks; Analytical models; Approximation methods; Delay; Materials; Supply chains; Transportation; Base-stock policy; parametric decomposition; queueing; supply chain;
Journal_Title :
Automation Science and Engineering, IEEE Transactions on
DOI :
10.1109/TASE.2012.2189564