When　making　decisions　to　acquire　used　products　or　components　(cores),　a　remanufacturer　faces　limited　information　on　the　quality　or　proportional　yield　of　cores　during　the　recovery　process.　In　this　paper,　we　propose　and　analyse　a　robust　optimisation　model　for　studying　the　remanufacturing　decision　problem　with　partial　random　yield　information,　that　is,　when　the　quality　information　of　cores　is　partly　unknown　in　a　remanufacturing　system.　Regarding　the　impacts　of　unknown　yield　information,　we　only　require　the　support　and　mean　of　the　proportional　yield　rather　than　the　true　distributions.　The　closed-form　solutions　of　acquisition　quantities　are　derived　based　on　the　minimax　regret　approach.　In　addition,　to　validate　the　effectiveness　of　the　analytical　results,　particularly　the　acquisition　of　yield　information,　numerical　experiments　are　designed　and　implemented　using　(1)　the　support　and　mean　of　the　proportional　yield　based　on　the　manufacturer＇s　knowledge　and　(2)　a　sampling　inspection　to　evaluate　the　performance　of　the　robust　optimisation　approach,　the　benchmark,　and　the　naive　approach.　We　observe　that　the　minimax　regret　approach　slightly　underperforms　compared　to　the　benchmark　but　performs　much　better　than　the　naive　approach.　As　an　acceptable　choice,　this　approach　is　less　complicated　and　extremely　easy　to　implement　to　meet　the　needs　of　practical　situations　based　on　its　robust　closed-form　solutions.