Model for predicting mechanical counter weighing equipment replacement time

Abstract

Weighing equipment is so important in business transactions, as it guides the exchange of goods through measurements. However, the equipment is susceptible to many factors that increase their degradation in service, which tend to reduce their service Accurate weighing is essential for fair trade and consumer protection, particularly in markets where mechanical weighing equipment remains prevalent. In Uganda, these devices often degrade over time due to poor handling, environmental exposure, and limited maintenance, leading to measurement inaccuracies and consumer complaints. This study aimed to develop a Weibull-based predictive model to estimate the optimal replacement time for mechanical counter weighing equipment. The specific objectives were; First to assess the failure patterns and causes of mechanical weighing equipment degradation, Secondly, to identify the key factors influencing equipment performance through perception surveys and inspection data, and thirdly, to develop and validate a predictive model using the Weibull distribution. A cross-sectional research design was employed, with data collected from four major trading centers in Kampala. Binary logistic regression was used to analyze factors affecting degradation, while Maximum Likelihood Estimation (MLE) was applied for Weibull parameter fitting. Model validation was conducted using standard Goodness-of-Fit tests. Out of 310 scales inspected, 76% exhibited degradation, largely due to dust exposure, overloading, vibrations, and humidity. The estimated optimal replacement time was 8.4 years. The resulting model offers a data-driven decision-support tool to guide timely replacement, enhance legal metrology enforcement, and protect consumers in trade environments.