OPTIMAL MACHINING PARAMETER SELECTION BASED ON REAL-TIME MACHINE MONITORING USING IEC 61499 FUNCTION BLOCKS FOR USE IN A CLOUD MANUFACTURING ENVIRONMENT: A CASE STUDY FOR FACE MILLING

Optimization of manufacturing processes is one of the key challenges towards a sustainable manufacturing environment. The components manufactured nowadays are usually divided into small batches of highly customized parts. These parts are usually machined using the traditional approach for machining on CNC machines. This approach involves the creation of a static G-code for every component that is manufactured, which is dispatched to the machines either manually or through a LAN network. In this paper a new approach in machine tool programming is presented. The proposed system is based on IEC 61499 function blocks to create last-minute feature based code for machining respecting actual machine status. The proposed system optimizes cutting parameters and delivers optimized code with respect to machining time. The function block approach is ideal for on-controller implementation while also allowing through its web based option the embedding into a cloud manufacturing environment. A cloud platform accommodates the machine availability monitoring module for increasing shop-floor awareness and allowing for the correct decisions at the right time. The machining process of face milling was selected as a case study for demonstrating the functionality of the proposed system. The results of the case study are visualized and verified using simulation software.