The rear wall of the header box serves as a tubesheet in heat exchangers of double plate header box. Tube-to-tubesheet welding must be performed using orbital Gas Tungsten Arc Welding (GTAW) with a head extension, which is passed through the corresponding hole in the front wall (plugsheet) of the header box, where the welding machine is supported. In this project, the effect of parallelism deviations between the plugsheet and the tubesheet of carbon steel header box is analyzed to evaluate its influence on the quality of the tube-to-tubesheet welding. Welded tube (SA-210 Gr. A1) to tubesheet (SA-516 Gr. 70) coupons are manufactured simulating the parallelism deviations previously analyzed in two double plate header boxes of air-cooled heat exchangers using two different preheating temperatures. Macrographic analysis is performed in order to evaluate the weld penetration (minimum leak path) and length of the weld leg in tube-to-tubesheet joints. The results obtained show important variations in those parameters when the parallelism deviations are equal to or greater than −1 mm over the theoretical distance as well as when the distance approaches +1 mm or more. Finally, the incorporation of dimensional controls prior to the welding process is discussed and the implementation of improvements in orbital GTAW equipment is recommended as an optimal solution for this kind of heat exchangers.

The air entrapment mechanisms in die-casting injection chambers that may produce porosity in manufactured parts are analyzed in this work using visualization techniques of the flow in a transparent injection chamber model, using water as working fluid. In particular, results for the free-surface profile evolution and for the volume of air remaining in the chamber at the instant at which the water begins to flow through the runner are analyzed for different maximum plunger speeds and initial filling fractions. A comparison between these visualizations and the numerical results of Zamora (2007, “Experimental Verification of Numerical Predictions for the Optimum Plunger Speed in the Slow-Phase of a High-Pressure Die Casting Machine ,” Int. J. Adv. Manuf. Technol., 33, pp. 266–276) which were obtained using a three-dimensional numerical model, shows a good degree of agreement. After discussing the air entrapment mechanisms that may produce porosity in manufactured parts, different experiments, which were carried out under real operating conditions using an aluminum alloy in a high-pressure die-casting machine with horizontal cold chamber, will be presented. The die-cavity geometry used in the experiments was appropriately modified to isolate the slow shot phase from the rest of the injection process, and the porosity levels in the manufactured parts were measured using a gravimetric technique. The optimum values of the maximum plunger speed that minimizes porosity in the manufactured parts have been determined. These values are very close to the previous numerical predictions of López (2003, “On the Critical Plunger Speed and Three-Dimensional Effects in High-Pressure Die Casting Injection Chambers ,” ASME J. Manuf. Sci. Eng., 125, pp. 529–537)

A large number of material and process parameters affect both the part quality and the process performance in pressure die-casting (PDC) processes. The complex relations between most of these variables make PDC process optimisation a difficult issue which has been widely studied for many years. Although there are several analytical and numerical models to optimise certain process parameters, it is difficult to establish a specific operational configuration for PDC machines that ensures the joint optimisation of these variables. Therefore, in this study, some of these optimisation models have been implemented in a Decision Support System (DSS) that allows us to define an operational region that establishes a setup of machine parameters that ensures the manufacture of quality parts. By using this DSS, the user can set the values of the input variables related to the casting material, the die, or the casting machine. Then the corresponding calculations are made by the system and the results are expressed in terms of certain output variables such as the maximum filling time, maximum filling fraction, or the plunger velocity profile among others. The DSS allows the user to estimate the influence between input and output variables and find proper values for the input variables to achieve an optimum operational range. Consequently, improved process performance can be achieved taking into account productivity, part quality, and economic aspects.