Warehouse Activity Profiling and Data Mining

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rc au nb ge e- ms . oIvf et hmeepnrt e -dsips terciibf iuetdi orna nwg ei lsl ceosrsreens tpi ao lnl yd tsoo sl vt oe r at hg ee ms toodr ae gael t emr no adtei vae ss s, it ghne mn tehnet pmroonbtl he .mT. hFoosreeixt ae mm sp lme , ai yn bt heegfoi goudr cea, n1 d5 i%d aot fe tshfeo ri t setmo rsasghei pd rl easws et rhsa on r0b. 1i nc us hb ei cl vf ienegt . pAe rt tchueb ioct hf eeer te(nnde oa rf ltyh e2 0d i ps tarlilbe tust)i opnewr me foi nndt h1. 2 T%h oo sf et hiet ei mt e smms tahya bt em coavnedmi doartee st hfaonr 1b,l0o0c 0k stacking, double-deep rack, push-back rack, and/or pallet flow lanes. The principle is to assign items to storage modes based on their cube-movement.

25%

20%

20%

15%

15%

12%

15%

10%

10%

8%

10%

5%

% Items

3%

2%

5%

0%

<0.1 0.5 2

5 10 50 100 250 1,000 1,000+

Cube (FT 3 ) Picked/Shipped per Month

Figure 21. Cube-movement distribution.

4.3 Popularity-Cube-Movement Distribution Dt hoen ceupbreo- pmeor vl ye, ms leont tt i nd gi s tt ar ikbeust ii on nt o. aTchc eosuen td ibsot rt hi b tuht ei oint es mc apno bp eu l caor mi t yb idni es tdr iibnut ot i oanj oa inndt pdiicstkriinbguitsiopnr.esAennteedxabmelpolwe .popularity-cube-movement distribution for broken case

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