Fuzzy Similarity Approach for Ranking and Health Assessment of Towers Based on Visual Inspection. Issue 9 (September 2015) - Verma, Mohit; Rajasankar, J.; Anandavalli, N.; Prakash, Amar; Iyer, Nagesh R.
The most common way for the health assessment of existing telecommunication towers is through visual inspection. However, the results of the visual inspection are highly subjective and are merely based on perception which may differ grossly from one expert to another. One of the best ways to normalize human perception and reasoning in decision making is through fuzzy logic. This paper presents a fuzzy approach towards health assessment and ranking of telecommunication towers based on visual inspection. The health assessment of tower is treated as a group multicriteria decision making (MCDM) problem in which the towers are rated by expert group based on different criteria. The model used in the paper is a modified version of fuzzy technique for order preference by similarity to ideal solution (TOPSIS). The modified version rank the towers based on similarity with fuzzy positive ideal solution (FPIS) rather than the distance from fuzzy positive and negative ideal solutions. The model also provides critical information about the issues which need to be addressed to maintain the health of the towers and thereby enables efficient management and allocation of the limited resources. An illustrative example is included to clearly describe the steps involved in the process. Finally, sensitivity analysis for the model is carried out. The results of the sensitivity analysis demonstrate the tolerance of the model for slight variation in the input parameters, which typically reflect the doubt or confusion in the mind of expert while rating. The method is also compared with the closeness coefficient method and is found to be more appropriate for the ranking of towers. The model attempts to bring some rationality to the vagueness involved in visual inspection. The model is an effective tool for health assessment and ranking of towers based on visual inspection.