Perancangan Trolley Menggunakan Metode Reverse Engineering pada Produksi Komponen Panel Exterior D-Nose Ifle di PT. XYZ Berdasarkan Hasil Analisis Menggunakan Pendekatan DMAI - Rahmah, Nabila; Lubis, Marina Yustiana; Safrudin, Yunita Nugrahaini (Jurnal Teknik Industri Terintegrasi (JUTIN), 2023)
PT XYZ is an Aerospace company in Asia which operates in the aircraft industry, where the production process is still not running well because defects are still found. Efforts made by the company to prevent defects occur are by giving warnings or warnings to production process operators to increase their caution in working, but these efforts are still unable to prevent defective products from occurring. Based on these problems, the method used at the design proposal stage is the Six Sigma method with the DMAI and Reverse Engineering approaches. Six Sigma is a method of identifying and eliminating variability, Reverse Engineering is a method of product development from existing products. The stages of these two methods are integrated to improve the material handling process for D-Nose Ifle Exterior Panel components which have the highest frequency of defects appearing due to the position of component placement which is carried out in a stacked manner and the use of safeguards on the MHE is not appropriate. The proposed design made is a trolley. The aim of designing the trolley is to overcome the occurrence of scratch & damage defects by changing the dimensions and capacity of the trolley to be suitable for loading a maximum of 4 D-Nose Ifle Exterior Panel components without stacking them and using rubber guards to protect the components, so that the company can carry out material processing effective handling without damaging product quality. With the proposed trolley, it is hoped that it can minimize the number of defects by 46.88% of the previous number of defects and can also increase the process capability from the existing sigma level of 3.896 sigma to a new sigma level value of 4.119 sigma, which means an increase of 0.223 sigma.