Large quantities of data are accumulated in process planning for body in white (BIW). To acquire the potential and valuable process knowledge from these data, the rough set theory and association rule technique are integrated to discover the useful correlations between the welding type and process requirements. The correlations can guide us to select the welding type according to the given process requirements. During data mining, every process requirement is regarded as an attribute. First, the decision table for the welding type is constructed. Second, rough set theory is employed to remove redundant attributes. A simplified decision table is constructed. Third, association rule is used to extract the useful rules. Finally, an illustrative example indicates this methodology can extract useful rules for the selection of welding type.