Assessment of Conveyor Telemetry System in a Manufacturing Firm: A Case Study of a Brewery in Eastern Nigeria

Abstract

Unplanned downtimes in conveyor systems present significant operational and financial challenges in manufacturing environments. This study assesses and enhances a telemetry-based predictive maintenance system for the conveyor lines of an international brewery in Eastern Nigeria. The modified system integrates vibration, speed, temperature, and current sensors, supported by Programmable Logic Controllers (PLC), Variable Frequency Drives (VFD), and a Grafana dashboard for real-time visualization. Data collected under real operational conditions revealed early warning signs of faults: electric motor current rose from an optimal 0–1A to a critical 3A before automatic shutdown; bearing vibration levels escalated from 0.5 mm/s to 4.6 mm/s, indicating failure; and conveyor belt speed dropped from 7 cm/s to 2 cm/s, signaling slippage. These anomalies were detected and corrected before resulting in major downtime. The system also enabled condition-based maintenance, avoiding the inefficiencies of reactive and preventive strategies. Benchmarking against ISO 17359, ISO 55000, and IEC 61508 confirmed alignment with industrial best practices. Financial analysis showed a 60% reduction in monthly maintenance costs, from ₦20 million to ₦6.2 million, yielding estimated savings of ₦13.8 million per month. Over a six-month period, cumulative savings totaled ₦82.8 million, affirming the system's economic viability. These results validate the role of integrated telemetry in reducing downtime, extending equipment lifespan, and improving manufacturing efficiency. The study encourages broader industry adoption and recommends future integration with machine learning for automated fault prediction.