STOCHASTIC MODELING FOR AUTOMATED MATERIAL HANDLING-SYSTEM DESIGN ANDCONTROL

Material handling systems (MHSs) are micro-transportation systems that share many of the same challenges in, design and operation. as their larger-scale transportation counterparts. However, because of the auto mation technology employed in material handling, such systems also pre sent many new challenges. Over the past decade, progress in automation technology has led to the replacement of many non-automated MHSs with automated systems. Use of an automated MHS can lead to significantly lower overall material handling cost, and thus overall production cost . However, the installation cost of such a system can be significant, and an MHS that does not function properly can lead to significant los ses in productivity and profits. Analysis of design and control proble ms for such systems must take into account the fact that MHSs typicall y operate in a stochastic environment, with stochastic demands for mat erial handling flexibility in vehicle routing, variable processing tim es and other random elements. This paper reviews research on design an d control of automated MHSs, with emphasis on analytical models that i ncorporate stochastic elements. We focus on models of automated storag e and retrieval systems and automated guided vehicle systems. In addit ion to evaluating the existing literature, we describe areas where fur ther research is needed.