A Robust Quality-Control Framework for Standardizing Potato-Chip Frying Parameters Using Goal Programming and Monte Carlo Simulation - Cicilia Sriliasta Bangun; Andre Wicaksana; Edwar; MD. Amperajaya; Antoniette T. Mollejon (Universitas Islam Negeri Sultan Syarif Kasim Riau, 2026)
Capacity expansion in continuous food processing can destabilize quality when operating settings developed for a lower-throughput line are carried forward without statistical revalidation. This issue is pronounced in potato-chip frying, where moisture removal, oil uptake, immersion condition, and residence time interact during processing. Previous studies have explained frying mechanisms or proposed optimized parameter values, but fewer have shown how those results can be converted into Statistical Process Control (SPC) routines that operators can monitor and act on. This study proposes an integrated quality-control framework to standardize frying parameters after a 22% demand surge increased waste from 1-5% to approximately 20%. Historical shift-level records from March-May 2025 were treated as Phase-I data; after structural cleaning and IQR-based screening, 113 of 132 records were retained. The framework connects CTQ identification, empirical response modelling, lexicographic goal programming, Monte Carlo validation, scenario-tested operating windows, sensitivity ranking, Ppk review, and SPC deployment. Moisture content and oil content were selected as CTQs. Simulation results showed stable moisture performance, whereas oil content remained the limiting CTQ with predictive Ppk of 0.92. The framework offers a practical bridge between optimization results and shop-floor SPC implementation for post-expansion frying stabilization.