Selection of a pull production control policy under different demand situations for a manufacturing system by AHP-algorithm

A multistage serial production system is considered in the present paper. A generalized model has been developed with the use of probabilistic demand situations for the end product. The demand situations considered are binomial, exponential, lognormal and Poisson. These demand patterns are used as input parameter for various production control policies. The output values for performance parameters are obtained by simulation. The production policies analyzed are Kanban, CONWIP and Hybrid as alternatives for controlling the engineering manufacture. In the presence of several performance measures, it often becomes difficult for the management to select the most appropriate policy. Analytic hierarchy process (AHP) has been implemented for the purpose of selection. Computational results have been reported along with the sensitivity analysis after designing and conducting various experiments.