Fu Xiuli

Research on Predictive Model Surface Roughness in High Speed Milling for Aluminum Alloy 7050-T7451

Surface roughness is one of important factors in the evaluation of machine tool and machining process. It is greatly influenced by cutting conditions in cutting. In this paper a series of cutting experiments have been carried out to study on the predictive model and control of surface roughness in high speed milling aviation aluminum alloy 7050-T7451. The surface roughness is greatly influenced by cutting parameters (cutting speed, feed rate, depth and width of cut, etc). The surface roughness is particularly sensitive to the feed rate and slightly sensitive to the width of cut. Finally, the optimization of cutting conditions was presented to control desired surface roughness and maximum material removal rate.

Optimization of Job-Shop Scheduling Using Fuzzy Heuristic Algorithm for Discrete Manufacturing Enterprise

The paper presents a fuzzy heuristic algorithm to solve the job shop scheduling problem with the optimization objective of production period and deadline of critical parts. Based on classical heuristic scheduling algorithms, the two important time parameters——“Process Preparation Time” and “Remaining Processing Time” which affecting directly the sequencing of workpiece processing were quantified and applied to the fuzzy heuristic algorithm of scheduling problems. Using the fuzzy operators——α and β, the approach which makes Most Work Remaining (MWR) and Shortest Processing Time (SPT) more efficient are approximately equal, and also considers the conditions of machines and key processes in job shop. The results of example analysis (Roller frame in a certain company) and verification show that the optimization of job shop scheduling is not only to reduce production cycle time and operating cost, but also improve production efficiency. It is optimal and feasible for discrete manufacturing enterprise in engineering applications.