MTA model for finished goods inventory management aimed at minimising inventory costs and maximising product availability

This paper presents an original Make-to-Availability (MTA) model for repetitive production, identifying conditions where it outperforms the classical Make-to-Stock (MTS) model. While the MTA concept originated from the Theory of Constraints, it lacked detailed operational definitions. The authors define these parameters and conduct a comparative study using computer simulations based on a real industrial automation enterprise to ensure high-fidelity test parameters. The primary objective is to find an optimal trade-off between conflicting metrics: minimising operational costs and maximising product availability. Unlike cyclical MTS, the dynamic MTA model continuously monitors inventory across three buffer zones. Production triggers and prioritisation depend on buffer penetration, synchronising output with demand while actively managing capacity. The study employs a multi-criteria objective function to evaluate these models under varying demand and capacity loading. Although based on a single case study – a recognised method for testing innovative models – the findings offer analytical generalisations for high-volume consumer goods manufacturing. To enhance credibility, a bootstrap analysis was incorporated for statistical verification, demonstrating result stability. Findings show MTA’s superiority under high demand volatility and capacity constraints, where it significantly improves customer service levels while avoiding excessive inventory costs and capital engagement.