Designing a Baseline Digital Traceability Prototype and FMECA-Based Quality Risk Mapping for Indonesia’s Retail-Oriented Beef Post-Slaughter Cold Chain

Abstract

Indonesia’s beef supply chain continues to experience structural challenges in maintaining post-slaughter quality and transparency. National consumption has increased from 1.44 kg/capita in 2006 to 1.90 kg/capita in 2019, with projections exceeding 2.12 kg/capita by 2025, while domestic production consistently supplies less than half of national demand, creating a deficit of roughly 184,000 tons (40%). Although live cattle imported from Australia are managed under well-established identification systems at the feedlot stage, previous studies indicate that batch-level traceability is lost immediately after slaughter, as carcasses transition into chilling, deboning, packing, storage, distribution, and retail operations that rely heavily on manual, non-integrated documentation. Existing research largely focuses on macro-level supply chain mapping, information flow modeling, or halal assurance frameworks, yet no prior work has provided a quality-oriented, post-slaughter risk assessment or a pragmatic digital traceability prototype tailored for retail-focused beef cold chains in Indonesia.

This exploratory baseline study aims to (1) map the post-slaughter beef cold chain supplying modern retail outlets, (2) identify critical quality and traceability risks using Failure Mode, Effects, and Criticality Analysis (FMECA), and (3) design a lightweight digital traceability prototype capturing batch origin, handling conditions, sanitation compliance, temperature history, and product movement. Field observations reveal three dominant high-risk areas: loss of batch identity after slaughter, temperature instability during storage and transport, and batch mixing during slicing and packing, all of which significantly influence microbial load dynamics, color stability, drip loss, and shelf-life performance.

The proposed prototype establishes a quality-driven digital foundation for improving post-slaughter transparency and supports future integration with IoT-enabled temperature monitoring, RFID-based tagging, or blockchain architectures to strengthen consumer-facing traceability in Indonesia’s modern beef retail sector.