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نظام ذكي لتقييم الخشونة السطحية لعملية تشكيل الصفائح التزايدية == Intelligent Surface Roughness Evaluation System of Ismf Process
Author name:
اوس خالد ابراهيم
Supervisor name:
وسام كاظم حمدان
General topic:
Production engineering metallurgy and materials
Specific topic:
Production Engineering
Degree:
Master
University:
University of Technology
Language:
English
University location:
Baghdad
First pages:
50T177 - p.pdf
Abstract:
تعد عملية تشكيل الصفائح التزايدية تقنية حديثة نسبيا لتشكيل الصفائح المعدنية والتي توفر امكانية تصنيع اجزاء معقدة الشكل وذلك باستخدام مكائن التفريز المبرمجة (CNC milling machines) بدون الحاجة الى قوالب خاصة لكل منتج والتي تتطلب وقتا طويلا للتصنيع مقارنة مع | Incremental Sheet Metal Forming (ISMF) is a modern sheet metal forming technology which offers the possibility of manufacturing 3D complex parts of thin sheet metals using the CNC milling machine. The surface quality is a very important aspect in any manufacturing process. Therefore, this study focuses on the surface quality of parts produced by single point incremental forming (SPIF) process. As a consequence, the objective of this study is to control the surface roughness by studying five forming factors, namely; (tool diameter, step size, tool shape, rotational speed and slope angle).In order to evaluate the surface quality, practical experiments for forming pyramid like shapes have been carried out on sheets of aluminum AA1050 with thickness 0.9 mm. As a result, two Adaptive Neuro - Fuzzy Inference systems (ANFISs) are conducted for predicting the surface roughness. The first system depends on the five forming factors as a direct contact estimation method while the second system utilizes contactless parameters (average gray level, standard deviation and mean frequency) that are extracted from the products images using a vision system as a contactless prediction method. A third model is developed using Sugeno Fuzzy Inference System (SFIS) for the evaluation of forming factors by which the surface roughness for a certain slope angle is obtained.Both quantitative and qualitative assessments have been used to explore the effects of the five forming factors on surface quality of parts produced by SPIF process. The ANOVA and MEP results show that the incremental step size and the forming tool shape are the most important factors affecting the surface roughness. These two factors are directly and inversely proportional to the surface roughness respectively. The maximum and minimum surface roughness, which is achieved from all the 24 experiments is (Ra = 4.3 & Ra = 0.18 µm) respectively. As a result, a surface with roughness smaller than the initial roughness of the sheet (0.27 µm) has been obtained. The qualitative assessment reveals that the surface roughness tends to increase towards the part deep.It can be concluded that the image based estimation of roughness using ANFIS is superior in terms of prediction accuracy. This vision system can achieve (97.856%) testing prediction accuracy compared to (85.799%) that is reached by the direct contact estimation of roughness. Conclusions also show that the vision system is capable of predicting the surface roughness of a hyperboloid part as a non - linear shape with prediction deviation (14.411%), thus enabling to evaluate the surface quality of complex parts that cannot be measured by the stylus. It can also be concluded that the SFIS is a successful approach for estimating the forming factors by which the surface roughness for a particular slope angle is obtained.
