Mechanical Engineering 101

Transcription

1 Mechanical Engineering 101 University of California, Berkeley Lecture #18 1

2 Today s lecture pull systems: kanban Example Parameters Reliability Scheduling, Assumptions, Variations 2

3 Kanban: a method for controlling pull system Japanese roughly translated as card used for production authorization each kanban includes info on part type number of units authorized possible additional info often used together with transport container possibly color-coded to match empty container pulls parts / triggers production kanban card is work order transfer lot size = container size 3

4 Kanban Step N supplier Step N manufacturer Z Z kanban card (and empty container) = request to supplier to make a container of Z and deliver ASAP send request when remaining WIP/material just covers lead time for replenishment 4

5 Kanban example [Mahoney] one-card kanban low mix/high volume environment products X and Z each has 3 steps performed at same 3 stations A,B,C one worker per station (aka Point Of Use, POU) storage after each station Process A Process A+B Process A+B+C 5

6 Kanban card for example X 1 card located with product throughout the system X Model number Replenishment quantity 1 X product: Z product: 6

7 LMHV Location after process A Product X after process A Product specific one-card kanban system product X kanban card Finished product X Product Z after process A Finished product Z Process A Process B Process C Process A Process A+B Process A+B+C 7

8 Signals from parts and cards Authorizes another product Z to be started Product Z Kanban card put up at C Z 1 Product Z removed from FGI 8

9 More details process B & C Z 1 Z 1 C removes partially completed Z from input buffer Z kanban put up at B to schedule production of another Z product Completed Z after process C goes with card to FGI Z 1 9

10 Moving further upstream. Z 1 Z 1 B removes partially completed Z from input buffer Z kanban put up at A to schedule production of another Z product Completed Z after process B goes with card to output buffer 10

11 Last step... process step A creates product Z Z and kanban card placed in step A output buffer 11

12 Idle state no kanban cards at any process stage no production occurs removing an X or Z from FGI would restart process 12

13 Today s lecture pull systems: kanban Intro Parameters Reliability Scheduling, Assumptions, Variations 13

14 Kanban parameters container size each kanban authorizes number of units that fit in container number of kanbans for each part type 14

15 Container size cost to move container based on handling technology ideal container size n for part i, transfer technology j: derived from minimizing total transfer & holding costs (fixed costs = c 1ij ) n ij 2c 2ij h i D i cost/move container of part i with technology j demand for product i holding cost for i 15

16 Number of kanbans Inventory position supply of parts must be coordinated with demand during lead time Q lead time, r reorder point safety stock SS time process step i has demand D, lead time how many parts will be removed during lead time? 1. D D + 16

17 .Number of kanbans for process step i, lead time demand = i D i if we have k i containers (= k i kanbans), each holding n i parts, we ll be ok if number of kanbans: n i * k i >= i D i k i >= i D i / n i 19

18 .Number of kanbans real world: variability! measure variability of lead time demand i D i use to set a safety factor l : i D i <= i D i (1 + l ) with some known probability if lead time demand i D i has mean 100, standard deviation 6, and we want to avoid shortages with ~97 1/2 % probability, what safety factor (l ) should we use? 23

19 .Number of kanbans total kanbans for step i: 27

20 Announcements HW 6 return Midterm Thursday HW 1-6, movies, lecture material through this week Try the posted samples!!! Bring: One 3x5 inch card of notes, handwritten, one side only An approved calculator: Hewlett Packard: The HP 33s and HP 35s models. Texas Instruments: All TI-30X and TI-36X models. Casio: All fx-115 models. 29

21 Today s lecture pull systems: kanban Intro Parameters Reliability Scheduling, Assumptions, Variations 30

22 Process availability example 2 stage process stage 1: 80 parts/hr but fails every 18 hrs w/ 2hrs downtime stage 2: 80 parts/hr reliable constant demand 75 parts/hr buffer 1 2 Demand 75/hour 80/hr 18hrs up/2 hrs down 80/hr 31

23 .Process availability example buffer 1 2 Demand 75/hour 80/hr 18 hrs up/2 hrs down 80/hr Do we have capacity to meet demand? 32

24 .Process availability example buffer 1 2 Demand 75/hour 125/hr 8 hrs up/2 hrs down 80/hr run stage 1 in fast mode 125 parts/hr fails every 8 hrs w/ 2 hrs downtime Average capacity? 35

25 Process availability example buffer 1 2 Demand 75/hour 125/hr 8 hrs up/2 hrs down 80/hr Stage1 production 150 have capacity to meet demand if enough buffer inventory kept since stage 1 faster, buffer will fill up time, hrs 37

26 .Process availability example buffer 1 2 Demand 75/hour 125/hr 8 hrs up/2 hrs down 80/hr kanban size is 5 parts/container for stage 1 output how many kanbans (k) for stage 1? what is max (worst case) lead time to refill container? what is max lead time demand? 38

27 Process availability example buffer 1 2 Demand 75/hour 125/hr 8 hrs up/2 hrs down 80/hr 150 Stage1 production 150 Buffer inventory 150 Stage 2 production 150 FGI time, hrs

28 Capacity, previous example buffer 1 2 Demand 75/hour 125/hr 8 hrs up/2 hrs down 80/hr Average capacity 80% of 125 = 100 parts/hr 48

29 .Preventive maintenance option slow machine to 110 parts/hr 1/2 hr preventive maintenance every 2 hrs Adequate capacity? 49

30 .Preventive maintenance option number kanbans? max lead time =.5 hrs + 5/110 =.55 hrs.55*75 = 41.3, so 9 kanbans slow machine to 110 parts/hr 1/2 hr preventive maintenance every 2 hrs Adequate capacity? 50

31 Time check 53

32 Today s lecture pull systems: kanban Intro Parameters Reliability Scheduling, Assumptions, Variations 55

33 Kanban scheduling rules several choices FCFS first come first served SPT shortest processing time families often FCFS between families EMQ wait until EMQ orders accumulated 56

34 Kanban scheduling rules yet more choices cyclical production fixed, repeating sequence (most efficient sequence) continuous time production quantity set to total number outstanding authorizations» but often have a min and a max periodic review do one full sequence per production period» based on outstanding orders at start of period variation: signal kanbans send signal kanban at reorder point with earlier material kanban signals 57

35 Signal kanbans signal authorizes production of entire EMQ signal kanban signal kanban signal kanban Part A Part B Part C 58

36 Signal kanbans signal authorizes production of entire EMQ possibly preceded by material order authorization material kanban signal kanban material kanban material kanban signal kanban signal kanban Part A Part B Part C 59

37 Oatmeal kanban 60

38 Oatmeal kanban 61

39 Oatmeal kanban 62

40 Kanban systems one card system supplier makes parts in response to arrival of kanban card inventory stored in buffers between stages at user kanban squares empty spot triggers production signal kanbans 63

41 Kanban systems two card system both input (user) and output (producer) buffers maintained Useful with multiple work centers using same part parts already waiting in output buffer when withdrawal kanban arrives from user producer makes parts in response to production kanban posted when a previous order was filled could have been triggered by any work center using part 64

42 2 card kanban example withdrawal kanban (aka transport) kanban production kanban products M,V,W,X,Y,Z PM 2 WM M 2 M PV 1 WV 1 V PW 1 WW 1 W PX 1 WX 1 X PY 1 WY 1 Y PZ 1 WZ 1 Z Inter-process inventory 65

43 Steady state i input buffer WM 2 M WV 1 V WW 1 W WX PM 2 WM 2 M M M M 1 X M X WY 1 Y WZ 1 Z process i i output buffer PV 1 V PW 1 W PX 1 PY 1 Y PZ 1 Z transit i+1 input buffer WV 1 V WW 1 W WX 1 X WY 1 Y WZ 1 Z 66

44 Assumptions needed for efficient use of kanbans demand and demand mix approximately constant otherwise need to adjust # kanbans short setup times allows rapid response to actual demand or you ll need large buffers (lots of inventory) disciplined workforce proper transfer of kanbans produce only if kanban available, flexible capacity cross-trained workers maintenance 67