Proportional Control Approach Research Articles

Mitigating variance amplification under stochastic lead-time: The proportional control approach

Logistic volatility is a significant contributor to supply chain inefficiency. In this paper we investigate the amplification of order and inventory fluctuations in a state-space supply chain model with stochastic lead-time, general auto-correlated demand and a proportional order-up-to replenishment policy. We identify the exact distribution functions of the orders and the inventory levels. We give conditions for the ability of proportional control mechanism to simultaneously reduce inventory and order variances. For AR(2) and ARMA(1,1) demand, we show that both variances can be lowered together under the proportional order-up-to policy. Simulation with real demand and lead-time data also confirms a cost benefit exists.

Sheet Thickness Optimization for Superplastic Forming of Engineering Structures

This paper explores two optimization strategies; the gradient search and proportional control methods, for determining the initial sheet thickness of superplastic forming to ensure final desired part thickness. A hemispherical dome model was involved in the testing of both optimization methods. Also, a three-dimensional rectangular box model was optimized by the proportional control method. The gradient search technique is shown to be acceptable in terms of the optimized thickness obtained, but displays poor convergence rates. The proportional control approach presented is easy to be implemented, and yields not only more accurate sheet thickness, but much higher convergence speeds that makes such optimization possible on complex geometric models. [S1087-1357(00)01001-7]