Selection of Material Handling Equipment Using Fuzzy Axiomatic Design Principles

Abstract

Effective movement of materials plays an important role in successful operation of any organization. Proper methods adopted for material movement are also crucial for the overall safety of the personnel involved in the manufacturing processes. Selection of the appropriate material handling equipment (MHE) is a vital task for improving productivity of an organization. In today's technological era, varieties of MHEs are available to carry out a desired task. Depending on the type of material to be moved, there are many quantitative and qualitative factors influencing the selection decision of a suitable MHE. The problem of selecting the right type of MHE for a given purpose can be solved using multi-criteria decision-making (MCDM) methods which are capable of dealing with the combination of crisp and fuzzy data. In this paper, an MCDM method employing fuzzy axiomatic design principles is applied for selecting the most appropriate MHE for the given task. As a measure of suitability, the total information content is calculated for each MHE and the MHE alternative with the least total information content is regarded as the best choice. Two real time problems from the literature, i.e. selection of an automated guided vehicle, and selection of loading and hauling equipments in surface mines, are solved to validate the applicability, flexibility and potentiality of the adopted approach.

An integrated group FWA-ELECTRE III approach based on interval type-2 fuzzy sets for solving the MCDM problems using limit distance mean

“…Many attempts have been carried out for solving the MHESP during the last 3 decades. In a general classification, these studies can be categorized into the following four classes: (1) decision support systems (expert system for the design of repetitive manual materials handling tasks [68], the material handling expert system [69], the prototype expert system for the selection of industrial truck type, an expert consultant for in-plant transportation equipment [70], and a knowledge-based system for the choice of conveyor equipment [71]); (2) hybrid methods (an intelligent knowledge-based expert system, named intelligent consultant system, for selection and evaluation of material handling equipment, which has been composed of the following four models: equipment and their attributes, a rule-based database for selecting type of equipment, an MCDM technique (AHP) for selection of optimal equipment, and simulators to evaluate the performance of the equipment model [72], a decision support system based on axiomatic design principles [73], and a hybrid fuzzy knowledge-based expert system and genetic algorithm for the selection and assignment of the most appropriate MHE [74]); (3) optimization formulations (an integer programming model for minimizing material handling costs in manufacturing systems or warehousing facilities [75], a hybrid methodology including the integer programming formulation for designing layout and material handling system simultaneously [76], a 0-1 integer programming model to determine operation allocation and selection of material handling system in an flexible manufacturing systems simultaneously [77], a mathematical model to implement problem modeled by radio-frequency identification technology [78], and a multi-objective optimization model for selection of material handling system for large ship [79]); (4) the MCDM problems (fuzzy axiomatic design principles for selecting automated guided vehicles [80], fuzzy AHP (FAHP), and decision-making trial and evaluation laboratory (DEMATEL)-ANP with geographic information system for the selection of the best space for leisure in a blighted urban site [81], FAHP and fuzzy additive ratio assessment for selection of conveyor [82], the fuzzy complex proportional assessment (COPRAS) method for evaluating performance measures of equipment in total productive maintenance [83], the AHP and TOPSIS methods for selecting the most appropriate tomography equipment [84], COPRAS, simple additive weighting, and TOPSIS for analyzing and prioritizing Rotor systems [85], FAHP, fuzzy entropy, fuzzy TOPSIS (FTOPSIS), and multi-objective mixed integer linear programming for the choice of MHE in warehouse [86], FAHP for bu...…”

Determination of a Suitable Renewable Energy Source for Mini-Grid Business: A Risk-Based Multicriteria Approach

“…Its acceptance is further strengthened by its capacity to analyse linguistic information. The linguistic terms are converted into crisp values using fuzzy numbers [41,42]. Triangular and trapezoidal are among the frequently used fuzzy numbers for this conversion operation.…”

“…The information content for a criterion is expressed as (12), while (13) gives the total weighted information contents of an alternative. The decision on the best-ranked alternative is based on the alternative with the highest weighted information content value [41,42].…”

Comparison of Customer Preference for Bulk Material Handling Equipment through Fuzzy-AHP Approach

“…Selection of material handling equipment through fuzzy approach find its' application through axiomatic design principles [36], fuzzy AHP approach in FMS environment [37], in surface mine transport by using a combination of Fuzzy MCDM models [38], through decision support system [39], through fuzzy approach and ANP [40]. The present study has tried to provide a relatively simple approach for the decision makers in industry to obtain accurate decision regarding purchase of capital equipment through comparative study through AHP and Fuzzy AHP.…”