Bulent Onalir

Bio: Bulent Onalir is an academic researcher. The author has contributed to research in topics: Injection moulding. The author has an hindex of 1, co-authored 1 publications receiving 1 citations.

Application of computer–aided injection moulding simulation for thermoplastic materials

Abstract: This paper presents the computer–aided simulation of an injection moulding process for thermoplastic materials. The reasons for using computer simulation for the injection moulding process are discussed together with description of the mould–filling and cooling phenomena. The paper also traces the difficulties in transferring the geometry of the part database from a computer–aided design environment to a computer–aided analysis environment by proposing several solutions for plastic products. Details of simulation steps will be examined by using an example part from a finite element mesh representation of mould cavity, runner and cooling channel configurations to evaluation of results from different types of analysis. Commercially available software is used for part modelling and process simulation applications.

Application of Moldflow and Taguchi technique in improving the productivity of injection moulded energy meter base

Abstract: In injection moulding process, the productivity is largely dependent on the cycle time and its optimisation plays a vital role. Productivity improvement in injection moulding is possible by undertaking scientific moulding using the modern process improvement and statistical techniques. This paper describes the improvement in the productivity of injection moulded polycarbonate energy meter base wherein Moldflow software is used to predict the injection pressure, filling time, clamping force, etc. and the design of experiments is carried out to know the impact of various parameters on sink mark, cycle time and overall quality indexes. The experimentation is done using the predicted values obtained from Moldflow analysis and an orthogonal array is employed for optimising injection time followed by pack time and cooling time. Significant improvements are achieved in reducing the cycle time from 51.5 seconds to 42.0 seconds using the systematic optimised processing parameters and thus increasing productivity.