An evaluation of input and output of expert systems for selection of material handling equipment

Abstract

Purpose – The purpose of this paper is to evaluate expert systems (ES) for selection of material handling (MH) equipment on their use of information and generation of equipment, and provide guidelines that can enhance developing them in the future. Design/methodology/approach – Data envelopment analysis (DEA) is used to evaluate efficiency of ES on their use of information and generation of equipment. Characteristics of benchmark ES are identified to serve as guidelines in developing future ES. Findings – Results of DEA indicate that most ES use a large amount of information that does not commensurate with the number and variety of equipment they generate. Research limitations/implications – The ideal MH equipment for a situation is not known whether it is selected by ES or other procedures. Therefore, this study focusses on efficiency of ES in using information to generate MH equipment without regard to whether ES produce the right equipment for a situation or not. Practical implications – Developers of future ES should consider the efficiency of an ES in using information and generation of equipment, in addition to considering its functions and methodologies. They should utilize means similar to those employed by benchmark methodologies and other ones that can be thought of to economize information and generate more number and variety of equipment, and thus render ES more useful to facility designers and manufacturing managers. Originality/value – The paper presents the first evaluation of ES for selection of MH equipment. The evaluation performed should enhance development of future ES in this field, and can be extended to ES in other application domains.