Year: 2026
Type: article
Abstract: Proper planning of resource allocation and workload balancing enhances process performance and reduces costs. The objective of this study is to demonstrate the applicability of process mining (PM) techniques in identifying bottlenecks, deviations, and workload imbalances within poultry meat production processes. An event log—constructed from the daily records of a national poultry producer for the period of January 2026 (comprising 100 cases and 285 events)—was analysed using variant analysis and a Directly-Follows Graph (DFG). Following the organization and simplification of the data in Excel 365, a DFG process map was generated via scripts developed using the PM4Py library in the Python programming language. The analysis revealed bottlenecks, delays, and deviations; it was observed that the median length of cases was 3 steps (with a maximum of 10), the rework rate remained low, and delays were primarily concentrated on weekends (share of delayed records: Saturday 65%, Sunday 72%), stemming from issues related to work scheduling and workload imbalances. These findings indicate that process mining can provide decision support based on daily operational records in livestock production, contributing a practical, field-based example to the limited existing literature on process mining in the production sector. It is recommended that task codes be aligned with their respective locations and that the distribution of workloads be reorganized.
Author: Cemal Çelik
Institution: Bandırma Onyedi Eylül University
Language: Turkish
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W7223839593