Purpose: To analyse the strength of materials by means of optimization, find the best value of the strength test of mutually influential materials with a variation of roll-hoop height. Design/methodology/approach: The research began with the design of a threedimensional model by varying the height of the roll-hoop on chassis types: A, B, C, D, E, F, G, H ,and I. The height of the main roll hoop at each chassis is: 502, 504, 506 508, 510, 512, 514, 516 and 518 mm. Then by using the student version of Autodesk Inventor, a simulation is made to test: Deflection, Normal stress, Shear stress (T-x / T-y) and Torsional stress. The results of this test are used to analyse the types of chassis that have been designed so that the best chassis design is obtained. Findings: The results obtained in this study are the value of Normal stress decreases with increasing roll-hoop height, and applies inversely to the torsional stress value. Deflection values tend to be stable with increasing roll-hoop height, while Shear stress T-x and T-y values tend to fluctuate. Research limitations/implications: The chassis material uses carbon steel which has mechanical property values in accordance with 2015 FSAE Standard regulations. Practical implications: The optimization results of the design of the roll hoop height on the chassis show that the chassis type B with the main roll hoop height of 504 mm is the best with the lowest deflection value and the difference in tension according to the FSAE rules. Originality/value: The research that has been done only tests the strength of the ingredients separately. In this study trying to analyse the strength of the material by way of optimization to find the best value from the strength test of material that influence each other with a variation of roll-hoop height.
Purpose: The purpose of this study is to analyse the modelling of exhaust gas flow patterns with variations in pressure, number, and shape of filters on the catalytic converter. Design/methodology/approach: The research method used is a simulation using ANSYS, which starts by creating a converter catalytic model with pressure variations: (0.5-1.5 atm), number of filters: (2-5), and the form of filter-cut/filter-not-cut. Findings: The decrease in velocity is caused by non-uniform velocity in the exhaust gas flow that occurs when passing through a bend in the filter-cut that serves as a directional flow to create turbulence. Filter-cut type tends to have fluctuating pressure, turbulence flow pattern shape so that contact between filter and exhaust gas is more effective. Based on the analysis of flow patterns, the speed and pressure of the 5 filter-not-cut design at a pressure of 0.5 are the best, while at pressure (1-1.5 atm) the type 5 filter-cut is the best. Research limitations/implications: This study is limited to filter-not-cut and filter-cut types with variations in the number of filters: 2, 3, 4, and 5, and the inlet pressure between 0.5-1 atm. Practical implications: The practical implications of this study are to find a catalytic converter design that has advantages in the effectiveness of exhaust gas absorption. Originality/value: The results show that the filter-not-cut and filter-cut types have the best effectiveness in the number of 5 filters. Filter-not-cut at the pressure of 0.5 atm and filter-cut at pressure (1-1.5 atm).
Lean manufacturing is about eliminating waste including the seven traditional, this writing suggested an observation on no value added of seven wastes influencing the process of fresh water production. The relationship value among waste was statistically verified to create an approach for continuous improvement action. Thus, the main goal of this research is to develop a methodology of relationship among wastes and eliminate them. In relationship among wastes, it could be known that the high value indicating how often it happened in the production process gave direct cause in the system of fresh water treatment. A recommendation to reduce the highest value of waste is by doing improvement on parameter setting to obtain an optimum mixing model between water supply, alum and stroke pump with Taguchi method. The interaction of relationship among these seven types of waste can be portrayed using fishbone diagram and a relationship model among wastes using PLS smart (partial least squares). The final relationship model with the highest value of waste was analyzed using off-line quality control to upgrade the quality of fresh water used as the basis to eliminate waste and find out the optimal parameter of mixing process in accordance with the health standard.
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