Mixed-type　data　consisting　of　both　continuous　observations　and　categorical　observations　are　becoming　prevalent　in　manufacturing　processes　and　service　management.　The　majority　of　existing　statistical　process　control　tools　are　designed　to　monitor　either　continuous　data　or　categorical　data　but　seldom　both.　In　this　article,　we　propose　a　directional　exponentially　weighted　moving　average　control　scheme　composed　of　monitoring　and　diagnosis　for　mixed-type　data.　We　assume　that　there　is　a　latent　unknown　continuous　distribution　that　determines　the　attribute　levels　of　a　categorical　variable,　and　represent　both　continuous　data　and　categorical　data　by　standardised　ranks.　The　proposed　control　chart　also　incorporates　directional　information　to　facilitate　diagnosing　the　shift　direction.　Monte　Carlo　simulations　demonstrate　the　efficiency　of　the　proposed　control　scheme.