Queueing Models for Assembly-Like Systems.

Abstract

Queueing models for assembly-like systems are formulated and limit theorems are developed for the stochastic processes associated with these models. The basic single-station model, intended to be representative of an assembly operation, is studied in Part I. It consists of several input processes, each of which delivers a different type of 'component part' or 'input item', and a server who assembles these items into finished products, requiring exactly one input item of each type per assembly. Assuming the input processes to be renewal processes and service times (or assembly times) to be i.i.d. random variables, it is shown that such a system is inherently instable, and 'functional' limit theorems are developed for properly normalized versions of the basic queue length and waiting time processes. In Part II a similar model of a more complex assembly network is introduced, and generalizations are obtained for all of the results developed in Part I. In Part III some related models and possible directions for future research, including some natural problems of optimal design and control, are discussed briefly. (Author)

Document Details

Document Type
Technical Report
Publication Date
Nov 30, 1970
Accession Number
AD0721083

Entities

People

  • John M. Harrison

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Assembly
  • Mathematics
  • Random Variables
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Industrial Economics
  • Mathematical Modeling and Probability Theory.
  • Systems Analysis and Design