Designers are facing the principal problems of effective decision making at the initial design stage of product development, which ultimately contribute to profit loss, low quality and increased time to launch the product onto the market. It requires a lot of knowledge and experience. Tools are required to analyze and ensure that crucial decisions have strong foundation before implementation. Discrete event simulation provides such a tool and has got potential to assist in decision making before final implementation. This research work aims measuring the benefits of transformation to lean product development (LPD) via simulation. Simulink-MATLAB tool was used for this purpose. The whole work is limited to design and cost estimation cells of a manufacturing company and consists of two phases. The first phase deals with the assessment of current working model of design and cost estimation cells. The areas for improvements were recognized at this phase. The proposed model for transformation to LPD was developed in the second phase. Four lean enablers namely product values, knowledge-based engineering, set-based concurrent engineering and poke-yoke were incorporated to further enhance the operation of the proposed model. This research work constitutes a useful case for practitioners. Keywords: decision making, discrete event simulation, lean product development, lean enablers
Literature has vastly advocated for incremental sheet forming as a significant process for formation of sheet metal components, because of its higher formability in comparison with the rest of metal forming processes such as deep drawing and stamping. Due to high formability of incremental sheet forming it becomes important to investigate the main factors, influencing the quality of forming products. However, less attention has been given to investigate the inconsistencies reflected often in determining the effect of multiple forming parameters and parametric interactions comprising of spindle rotational speed and feed rate, tool size and sheet thickness, sheet thickness and step depth. This study investigates the effect of various principal factors including tool type, tool size, sheet thickness, spindle speed, feed rate, step increment including and their respective interaction on surface roughness. Research data was collected by undertaking extensive literature review of previous studies on incremental sheet forming regarding surface quality. A quantitative one way analysis of variance (ANOVA) was employed to analyze the significance and contribution of factors influencing surface quality of sheet forming. The findings highlight the contribution of forming parameters and their combined interactions on surface roughness. Based on the empirical findings, this study derives implications for the optimization of tool type, parametric interactions among principal factors and their respective optimized operational range for incremental sheet forming.
This study aims to investigate the effects of process parameters: feed, depth of cut and flow rate, on the temperature during face milling of the D2 tool steel under two different lubricant conditions, Minimum Quantity Lubrication (MQL) and Nano fluid Minimum Quantity Lubrication (NFMQL). Deionized water with the flow rate range 200–400 ml/h was used in MQL. 2% by weight concentration of Al2O3 nano particles with deionized water as a base fluid used as NFMQL with the same flow rate. Response surface methodology RSM central composite design CCD was used to design experiment run, modeling and analysis. ANOVA was used for the adequacy and validation of the system. The comparison shows that NFMQL condition reduced temperature more efficiently during machining.
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