Benchmark the best factory data collection system (FDC) using AHP-GRA method

Abstract

Purpose

The purpose of this paper is to propose a multi-criteria decision making method to evaluate factory data collection (FDC) system alternatives.

Design/methodology/approach

“Information” in is fundamental resource to the success of any business which is as valuable as capital or people. The factory data (information) collection system (FDC system) consists of the various paper documents, terminals, and automated devices located throughout the plant for collecting data on shop floor operations for compiling and processing the data. In this paper, nine alternatives of FDC methods are evaluated on the basis of eight criteria. The weight of each criterion is determined using Analytic Hierarchy Process, and the same weights are used to evaluate alternatives of FDC system using Grey Relational Analysis – A multi-criterion decision making method.

Findings

The methodology facilitates the selection of the best FDC system that will minimize the data entry time and chances of errors. The methodology suggests Radio-Frequency Identification (RFID) system is the most preferred choice (ideal) among the nine alternatives whereas Operation tear strips is the worst solution.

Originality/value

The proposed methodology will provide a useful tool to the decision maker, which may help to eliminate the associated risks during data entry. The selected best FDC system, i.e. RFID is most suitable tool for ERP system to integrate internal (manufacturing) and external (sales and service) management information system.

Citation

Gangurde, S.R. (2016), "Benchmark the best factory data collection system (FDC) using AHP-GRA method", Benchmarking: An International Journal, Vol. 23 No. 2, pp. 359-370. https://doi.org/10.1108/BIJ-03-2014-0023