Abstract
The ability to control quality of a part is gaining increased importance with desires to achieve zero-defect manufacturing. Two significant factors affecting process robustness in production of deep drawn automotive parts are variations in material properties of the blanks and the tribology conditions of the process. It is imperative to understand how these factors influence the forming process in order to control the quality of a formed part. This paper presents a preliminary investigation on the front door inner of a Volvo XC90 using a simulation-based approach. The simulations investigate how variation of material and lubrication properties affect the numerical predictions of part quality. To create a realistic lubrication profile in simulations, data of pre-lube lubrication amount, which is measured from the blanking line, is used. Friction models with localized friction conditions are created using TriboForm and is incorporated into the simulations. Finally, the Autoform-Sigmaplus software module is used to create and vary parameters related to material and lubrication properties within a user defined range. On comparing and analysing the numerical investigation results, it is observed that a correlation between the lubrication profile and the predicted part quality exists. However, variation in material properties seems to have a low influence on the predicted part quality. The paper concludes by discussing the relevance of such investigations for improved part quality and proposing suggestions for future work.
Highlights
Sheet Metal Forming (SMF) is the process of transforming a piece of sheet metal into a desired shape [1]
This paper presents a preliminary investigation on the front door inner of a Volvo XC90 using a simulation-based approach
On comparing and analysing the numerical investigation results, it is observed that a correlation between the lubrication profile and the predicted part quality exists
Summary
Sheet Metal Forming (SMF) is the process of transforming a piece of sheet metal into a desired shape [1]. Present work aims to examine the influence of material and tribology conditions on the prediction of part quality via numerical simulations. Simulation models with reliable and validated prediction accuracy could improve knowledge about the system behaviour as well as support in creating mathematical models representing the system. These mathematical models could guide control algorithms in real-time to decide upon the optimum product properties and tool settings that should be adopted for improved quality of parts
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More From: IOP Conference Series: Materials Science and Engineering
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