An Integrated Decision-Making Model for Efficiency Analysis of the Forklifts in Warehousing Systems

Abstract

In the logistics world, special attention should be given to warehousing systems, cost rationalization, and improvement of all the factors that affect efficiency and contribute to smooth functioning of logistics subsystems. In real time industrial practice, the issue of evaluating and selecting the most appropriate forklift involves a complex decision-making problem that should be formulated through an efficient analytical model. The forklifts efficiency plays a very important role in the company. The forklifts are being used on a daily basis and no logistical processes could be done without them. Therefore, it has been decided to determine their efficiency, which will contribute to the optimization of the process in this logistics subsystem. This study puts forward an integrated forklift selection model using Data Envelopment Analysis (DEA), Full Consistency Method (FUCOM) and Measurement Alternatives and Ranking According to the Compromise Solution (MARCOS) methods. Five input parameters (regular servicing costs, fuel costs, exceptional servicing costs, total number of all minor accidents and damage caused by forklifts) and one output parameter (number of operating hours) were first identified to assess efficiency of eight forklifts in a warehousing system of the Natron-Hayat company using the DEA model. This step allows sorting of efficient forklifts which are subsequently evaluated and ranked using FUCOM and MARCOS methods. A sensitivity analysis is also performed in order to check reliability and accuracy of the results. The findings of this research clearly show that the proposed decision-making model can significantly contribute to all spheres of business applications.

Development of data normalization methods for multi-criteria decision making: applying for MARCOS method

“…In another application of the MARCOS method in the transport operations, when comparing the effective of the railway system performance in the Sub-Saharan African region, the best solution that was determined by the MARCOS method is similar to that one when using seven other methods (WASPAS, ARAS, COCOSO, EDAS, MABAC, SAW, TOPSIS) [20]. In another study, when using the MARCOS method to select the type of forklift truck for the transportation operations, the best solution that was determined using the MARCOS method is similar to the that one when using other methods (WASPAS, ARAS, COCOSO, EDAS, MABAC, SAW, TOPSIS) [21]. The MARCOS method was also successfully applied in selecting the refractory material suppliers in the iron and steel industry in India, and it was also recommended for multi-criteria decision making in in other areas such as defining the maintenance strategy, workshop layout, inventory control policy, and so on [22].…”

“…There are three types of mean: the arithmetic mean, the geometric mean, and the harmonic mean. Assuming there are m values including n 1 , n 2 , …, n m , the formula for calculating of the mean of these three types is presented in (21), (22), and (23).…”

Healthcare performance management using integrated FUCOM‐MARCOS approach: The case of India

“…MCDM methods are scientific tools that assist decision‐making process involving more than one criterion. Over the years, several MCDM methods have been evolved and successfully employed to resolve decision‐making problems in different knowledge domain 69–71 . For example, Salimi and Rezaei 72 used Best Worst Method (BWM) to enumerate the importance of the research and development (R&D) measures and thereby evaluated the R&D performance of 50 firms.…”

“…This method has been used by various researchers to solve decision‐making problem such as evaluation of airline quality, 69 aircraft selection, 70 efficiency analysis of forklifts, 71 etc. Owing to the popularity and advantages of this method, it has been used in this study.…”

“…Over the years, several MCDM methods have been evolved and successfully employed to resolve decision-making problems in different knowledge domain. [69][70][71] For example, Salimi and Rezaei 72 used Best Worst Method (BWM) to enumerate the importance of the research and development (R&D) measures and thereby evaluated the R&D performance of 50 firms. Jain et al 73 employed an integrated BWM and VIKOR method to identify and evaluate risk level of musculoskeletal disorders among hand held users.…”