A　chilling　process　simulation　approach　is　presented　to　analyze　a　few　pig　chilling　experimental　records　from　a　meatpacking　house.　Two　classes　of　chilling　process　vectors　(CPVs):　temperature　slope　based　cooling　process　vector　and　loss　based　losing　process　vector　were　defined.　They　were　utilized　to　demonstrate　the　transfer　of　heat　and　mass　from　carcass.　As　both　wind　and　no-wind　working　conditions　were　included　in　each　experimental　record,　a　constrained　expectation　maximization　algorithm　was　proposed　to　simulate　different　working　conditions　simultaneously,　i.e.:　E　step　to　construct　the　Wind　CPV　(WCPV)　and　M　step　to　construct　the　No_Wind　CPV　(NWCPV);　in　both　E　step　and　M　step,　partial　order　constraints　were　considered,　and　a　cloud　model　based　on　evolutionary　algorithm　CBEA　was　utilized　as　the　optimization　algorithm.　Based　upon　37　experimental　records,　the　CPVs　were　constructed　and　applied　to　simulate　the　chilling　process　of　pig　carcasses,　the　mean　error　was　0.93°C　for　cooling　process,　1.51‰　for　loss　process.　Meatpacking　companies　can　apply　this　approach　to　analyze　the　practical　pig　chilling　process　data.