Skip to main navigation Skip to search Skip to main content

Factorial experiments in the analysis of assembly systems

  • K. K. Lai
  • , Kokin Lam
  • , W. K. Leung

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    Abstract

    Assembly systems are a key tool for mass production and are increasingly being implemented in the manufacturing industry. Since the performance of such systems depends on the levels of many design variables, they are not well understood. In this paper the performance of free transfer automatic assembly systems with closed inspection and repair loops is studied via factorial experiments of a simulated system. Five factors were identified that affect the throughput of the system: buffer size, number of pallets in the system, number of repair stations repair time of jammed assembly machines, and subcomponent defect rate. Initially, two levels of each factor were considered, so that a full 2s factorial design of the experiment was used to study the system. Next, to develop a deeper understanding of the linear or non-linear effect of each factor, additional levels were investigated. Finally, a predictive model is proposed. Engineers and system designers can use this predictive model to estimate the performance of the system, given a combination of levels of each of the five factors that we studied. © 1994, Taylor & Francis Group, LLC. All rights reserved.
    Original languageEnglish
    Pages (from-to)383-394
    JournalJournal of Applied Statistics
    Volume21
    Issue number5
    DOIs
    Publication statusPublished - 1 Jan 1994

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 9 - Industry, Innovation, and Infrastructure
      SDG 9 Industry, Innovation, and Infrastructure

    Fingerprint

    Dive into the research topics of 'Factorial experiments in the analysis of assembly systems'. Together they form a unique fingerprint.

    Cite this