Maintenance Priority of Racing Road Bicycle using Multi-Criteria Decision-Making Methods: A Review

Abstract

The study offers an alternative to the conventional failure mode and effect analysis (FMEA) method for prioritizing failure modes: a multi-factor decision-making approach. Road bikes designed for racing are highly tuned vehicles built to perform very well in competitive settings. But careful upkeep is required due to the demanding nature of racing, as well as normal wear and tear from high-speed movements and extended use. Even while road bike racing recognizes the need of maintenance, there is a noticeable lack of information in the literature regarding systematic approaches for maintenance decision-making. Existing procedures frequently lack a thorough framework that incorporates a variety of factors, such as durability, cost-effectiveness, racing performance, and safety issues. Furthermore, because racing situations are dynamic, it is necessary to have maintenance procedures that are flexible enough to quickly adjust to changing conditions and specifications. The major goal of this project is to create a methodical framework for employing MCDM techniques to optimize the maintenance of road bikes used for racing. The goal of this framework is to improve racing performance while minimizing downtime, lowering maintenance costs, and guaranteeing rider safety by incorporating several criteria, including major and small failures. This research aims to offer racing teams and enthusiasts an organized approach to maintenance decision-making catered to the particular needs of high-performance racing scenarios through the application of TOPSIS, SAW, and VIKOR techniques. The project intends to increase road racing bicycle efficiency, durability, and overall performance by methodically analyzing and prioritizing different maintenance procedures. This will help to progress both cycling technology and athletic performance. Nine criteria (Chance of failure, non-detection of failure, Level of skill needs, Economic safety, Days necessary for the maintenance, Spare parts availability, Machine Reliability, Cost per kilometre, Lead Repair Time) are used to establish the priority ranking.