A methodology for selecting assembly systems feeding policy

Abstract

Purpose

Assembly systems require uninterrupted components' availability to feed workstations. This paper aims to propose a methodology to help managers in evaluating and selecting the most suitable policy for materials delivery to the shop floor. The analysis focuses on three basic policies, namely kitting, just in time kanban‐based continuous supply and line storage, even including class‐based hybrid policies.

Design/methodology/approach

Descriptive models are developed to design components' delivery systems and to compute their performances. Empirical criteria are utilized to associate specific policies to components classes in order to implement customized hybrid line feeding policies. A case study is then included to exemplify the method application and to show its capabilities as a decision making tool.

Findings

Hybrid feeding policies may be preferable to a single feeding policy common to all components. This is shown in a representative case study. However, in general there is a priori superior method and only a comparison of alternative feeding policies based on objective performance measures can determine the best approach in specific industrial applications.

Research limitations/implications

The methodology is aimed at preliminary sizing and selection of alternative line feeding systems in deterministic environments. It is not intended for detailed performance analysis of assembly systems.

Practical implications

Production managers are given quantitative decision tools to properly select the components' delivery method at an early decision stage. This allows trade‐offs between alternatives to be explored in order to deploy customized feeding policies differentiated on components basis to better fit specific company requirements.

Originality/value

The paper extends previous descriptive models for line feeding systems and includes the possibility of hybrid policies.

Citation

Caputo, A.C. and Pelagagge, P.M. (2011), "A methodology for selecting assembly systems feeding policy", Industrial Management & Data Systems, Vol. 111 No. 1, pp. 84-112. https://doi.org/10.1108/02635571111099749