Abstract Response surface methodology (RSM) is a technique to determine and represent the cause and effect relationship between true mean responses and input control variables influencing the responses as a two or three dimensional hyper surface. Submerged arc welding (SAW) is used extensively in industry to join metals in the manufacture of pipes of different diameters and lengths. The main problem faced in the manufacture of pipes by the SAW process is the selection of the optimum combination of input variables for achieving the required qualities of weld. This problem can be solved by the development of mathematical models through effective and strategic planning and the execution of experiments by RSM. This paper highlights the use of RSM by designing a four-factor five-level central composite rotatable design matrix with full replication for planning, conduction, execution and development of mathematical models. These are useful not only for predicting the weld bead quality but also for selecting optimum process parameters for achieving the desired quality and process optimization.
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