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

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 ...

[1]  Reza Farzipoor Saen,et al.  The effect of correlation coefficient among multiple input vectors on the efficiency mean in data envelopment analysis , 2005, Appl. Math. Comput..

[2]  Henry C. W. Lau,et al.  Integration of expert system with analytic hierarchy process for the design of material handling equipment selection system , 2001 .

[3]  J. O. Matson,et al.  EXCITE: Expert consultant for in-plant transportation equipment , 1992 .

[4]  Taho Yang,et al.  A hierarchical AHP/DEA methodology for the facilities layout design problem , 2003, Eur. J. Oper. Res..

[5]  Timothy J. Greene,et al.  A knowledge-based system for conveyor equipment selection , 2004, Expert Syst. Appl..

[6]  Marcello Braglia,et al.  Evaluating and selecting investments in industrial robots , 1999 .

[7]  Joe Zhu,et al.  Quantitative models for performance evaluation and benchmarking , 2003 .

[8]  Michael G. Kay,et al.  Mathes: An expert system for material handling equipment selection , 1988 .

[9]  Pedro T. Isaías,et al.  Expert Systems Evaluation Proposal , 2007, HCI.

[10]  Phil Webb,et al.  A Hybrid Fuzzy Knowledge-Based Expert System and Genetic Algorithm for efficient selection and assignment of Material Handling Equipment , 2009, Expert Syst. Appl..

[11]  Leon F. McGinnis,et al.  Performance measurement in the warehousing industry , 2010 .

[12]  Donald E. Brown,et al.  Knowledge-based computer-aided design of materials handling systems , 1989, IEEE Trans. Syst. Man Cybern..

[13]  Osman Kulak,et al.  A decision support system for fuzzy multi-attribute selection of material handling equipments , 2005, Expert Syst. Appl..

[14]  Pius J. Egbelu,et al.  ADVISOR: A computer-aided material handling equipment selection system , 1995 .

[15]  P. S. Welgama,et al.  A hybrid knowledge based/optimization system for automated selection of materials handling system , 1995 .

[16]  Andrew L. Johnson,et al.  Guidelines for using variable selection techniques in data envelopment analysis , 2011, Eur. J. Oper. Res..

[17]  Sunil Vadera,et al.  A survey of AI in operations management from 2005 to 2009 , 2011 .

[18]  Yaakov Roll,et al.  An application procedure for DEA , 1989 .

[19]  Ramazan Yaman.  A Knowledge-Based Approach for Selection of Material Handling Equipment and Material Handling System Pre-design , 2001 .

[20]  James H. Bookbinder,et al.  Material-Handling Equipment Selection Via an Expert System , 1992 .

[21]  Kyung Sup Kim,et al.  An expert system for selection of material handling and storage systems , 1997 .

[22]  Mohsen,et al.  A framework for selection of material handling equipment in manufacturing and logistics facilities , 2010 .

[23]  Joseph Sarkis,et al.  A decision model for evaluation of flexible manufacturing systems in the presence of both cardinal and ordinal factors , 1999 .

[24]  William W. Cooper,et al.  Introduction to Data Envelopment Analysis and Its Uses: With Dea-Solver Software and References , 2005 .

[25]  Cláudia S. Sarrico,et al.  Pitfalls and protocols in DEA , 2001, Eur. J. Oper. Res..

[26]  Yang-Byung Park.  ICMESE: Intelligent consultant system for material handling equipment selection and evaluation , 1996 .

[27]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[28]  Fotios Pasiouras,et al.  Assessing Bank Efficiency and Performance with Operational Research and Artificial Intelligence Techniques: A Survey , 2009, Eur. J. Oper. Res..

[29]  Shinn Sun,et al.  Assessing computer numerical control machines using data envelopment analysis , 2002 .

[30]  Chiwoon Cho,et al.  Design of a web-based integrated material handling system for manufacturing applications , 2005 .