Application of Quantitative Models for Enhancing Supply Chain Efficiency and Mitigating Risks in Water Tank Manufacturing Industry Nigeria

Abstract

The study investigates quantitative models for analyzing the supply chain risks associated with a water tank manufacturing company's facility in Aba, Abia State. Aba, renowned for its bustling commercial activities in the southern part of Nigeria, faces challenges in the supply process due to the combined factors of water tank weight and size. This research explores the intricacies of supply chain management, aiming to identify risk assessment models and vulnerabilities, propose optimal scenarios, and recommend improved risk management strategies. Various methods such as risk factor identification, route time estimation, critical path analysis, cost-related risk assessment, comparison of logistic choices, decision tree analysis, and mitigation strategies were employed to determine the most efficient supply path and reduce costs. The analysis reveals that PATH 6 emerges as the most time-efficient route, with a critical path identified at 62 hours. From the result obtained by applying the developed paths to the supply chain mechanism of five major distributors of the company to observe the cost-effectiveness of each path between the budgeted cost, previous cost, and the cost of supplying the goods by following the developed path, which the budgeted cost and paths cost are closely related compared to the previous cost, for Global Chidozie Nzelu (G.C.N) Enterprise, the overall cost reduction from budgeted, actual, and total path costs stood at 7.89% and 9.44%, respectively. Similar trends were observed for St. Chris Global (S.C.G) Limited. (LTD.) (7.04% and 6.34%), Adiliaba Trading Company (A.T.C) LTD (5.76% and 7.31%), Rechard Romeo International (R.R.I) Company (6.07% and 5.46%), and Ndubia Goddy Lines (N.G.L) LTD (5.76% and 7.31%), showing a total reduction of 6.851%. This research empowers the water tank manufacturing company in Aba and Nigeria at large, to optimize its supply chain; furthermore, the implications extend to shaping a more efficient and adaptable landscape for manufacturing industries in the region.