Ricky Adhika Saputra
Universitas 17 Agustus 1945 Surabaya, Indonesia

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Design of an Ergonomic Dumpling Skin Cutting Tool Using an Anthropometric Approach: A Case Study at Rizky Jaya SMEs Ricky Adhika Saputra; Handy Febri Satoto
JRSI (Jurnal Rekayasa Sistem dan Industri) Vol. 13 No. 01 (2026): Jurnal Rekayasa Sistem & Industri
Publisher : Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jrsi.v13i01.11028

Abstract

The dumpling skin production process at UMKM Rizky Jaya currently faces significant operational challenges, specifically a production bottleneck at the manual cutting station. While noodle production has been automated, dumpling skin cutting relies on manual labor using conventional knives, requiring 7 minutes per 8.5 kg batch. This inefficiency results in physical fatigue for the 26 workers, inconsistent product dimensions, and significant lost sales during peak demand periods where orders reach up to 498 kg/day. This research focuses on the ergonomic design of a dumpling skin cutting tool based on anthropometric measurements to enhance productivity and worker comfort. Data collection involved measuring specific physical dimensions of five operators to ensure the tool’s geometric compatibility with the human body. The primary variables analyzed include shoulder height (average 143.4 cm), standing waist height (average 99.8 cm), and functional forward arm reach (average 77.0 cm). Statistical processing, including data adequacy and uniformity tests, was conducted to establish the 5th percentile as a design limit. The proposed design features a 70 cm high compact frame with a 50x70 cm cutting area, integrating a 5V laser line for visual precision and a neodymium magnet socket system for rapid blade replacement. By aligning the tool dimensions with the 5th percentile reach of 71.18 cm, the design ensures that all operators can function within a normal reach area, thereby minimizing the risk of Low Back Pain and shoulder fatigue. Implementation is projected to reduce cycle times from 7 minutes to under 4 minutes, effectively eliminating the current bottleneck.