Z-DEA-FMEA: identifying effective strategies for optimizing the HIV drugs supply chain using multi-criteria decision-making approaches

TL;DR

This study improves the HIV drug supply chain by identifying and prioritizing risks using a new multi-criteria decision-making framework to enhance delivery and reduce costs.

Contribution

A novel hybrid framework using Z-numbers and multi-criteria methods to assess and prioritize HIV drug supply chain risks.

Findings

Quantity Errors (F14) are the top risk impacting supply chain efficiency.

Pack Price Discrepancies (F16) have the highest financial impact on freight costs.

Delivery Confirmation (F06) is highlighted as a key factor affecting delivery efficiency.

Abstract

Millions of people living with HIV around the world depend on having access to antiretroviral (ARV) drugs, yet the supply chain continues to confront obstacles like rising freight costs and delivery delays. These inefficiencies put timely access to life-saving medications at risk, especially in resource-limited settings. To find ways to improve the HIV drug supply chain, this study looks into the underlying causes of these disruptions.

This study aims to: (1) assess and prioritize risks in the HIV drug supply chain, focusing on failure modes impacting delivery timelines and freight costs; and (2) enhance supply chain substantivity (fulfillment capacity) and resilience (disruption adaptability) through evidence-based strategies.

Using Z-numbers to handle uncertainty, we developed a hybrid multi-criteria decision-making framework that integrates Z-SWARA, Z-WASPAS, and Z-DEA-FMEA. Along with using FMEA to assess risks and identify failure modes, the method ranks them based on freight costs and delivery timeliness, using hybrid rankings, RPN, Z-SWARA/Z-WASPAS, and Z-DEA-FMEA efficiencies.

Hybrid rankings indicate that the primary contributors to supply chain inefficiencies are Quantity Errors (F14, ranked 1st, 𝑄𝑡𝑜𝑡𝑎𝑙=0.9374), Pack Price Discrepancies (F16, ranked 2nd, 0.8430), and Unit Miscalculation (F13, ranked 3rd, 0.7261). The Z-WASPAS analysis emphasizes the financial implications of F16, placing it at the top for Freight Costs (K = 0.178). Additionally, Z-DEA-FMEA notes efficiency shifts including Delivery Confirmation (F06, 𝜃=0.7303, Delivery). In the case of Weight Failures (F20), the Freight score (𝑄𝑖=0.6991, ranked 3rd) surpasses that of Delivery (0.6753, ranked 4th), while Shipment Mode Selection (F04) holds the 5th position overall (𝑄𝑡𝑜𝑡𝑎𝑙=0.6741).

Aiming to improve the availability of antiretroviral (ARV) medications, our approach integrates risk, uncertainty, and efficiency analysis to formulate evidence-based strategies by utilizing Z-numbers. It redefines concepts of resilience and substantivity, providing decision-makers with a framework to enhance delivery speed and minimize costs. These improvements strengthen global health logistics.

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