Algorithms for production flow analysis

Abstract

Production Flow Analysis (PFA) is a manual method that helps a company to identify sources of delay in material flows due to complex operation sequences, size of parts population, variety of machines (or number of departments), poorly designed facility layouts, incorrect choice of machines for operations, etc. This paper describes a set of algorithms which seek to automate the different phases of analysis in this classical design method for Cellular Manufacturing and Facility Layout. The algorithms for PFA use a variety of forms of input data Travel Chart, Operation Sequences or a Machine-Part matrix. In particular, this paper describes an enhanced machine-part matrix clustering (MPMC) algorithm to automate the Group Analysis phase of PFA. The improved clustering effectiveness and computational benefits due to the enhancements in this MPMC algorithm are demonstrated. Extensive experiments using test matrices from the literature and industry have been conducted.