INTEGRATING LEAN WASTE ANALYSIS INTO ROBOTIC INDUSTRIES: INSIGHTS FROM THE WASTE ASSESSMENT MODEL - Satriyono, Raden Danang Aryo Putro; Faozi, Ekan; Fahmi, Afiqoh Akmalia; Wibowo, Ari Mukti (Industrial Engineering Department, Faculty of Engineering, Universitas Brawijaya, 2026)
The rapid growth of high‑tech manufacturing demands rigorous waste‑reduction strategies to sustain competitiveness. This research applies the Waste Assessment Model (WAM), a systematic tool for identifying and ranking the seven classic lean wastes, to PT Stechoq Robotika Indonesia, a research and development driven robotics firm. Using the three‑step WAM process (Seven Waste Relationship, Waste Relationship Matrix, and Waste Assessment Questionnaire), data were collected from production‑line operators and analyzed through matrix scoring and questionnaire weighting. Quantitative results reveal that Defect (19.9 %), Overproduction (17.1 %), and Process (17.1 %) are the most influential waste sources, while the WAQ highlights Motion (24.4 %), Transportation (22.4 %), and Process (17.1 %) as the dominant waste types to target. The study demonstrates that waste from defects, overproduction, and process steps significantly propagates secondary wastes, with inventory waste emerging as the most affected (17.8 %). These insights provide a data‑driven roadmap for lean‑focused interventions, aligning with broader industry practices on waste prioritization.