Chapter 7. Production, Capacity and Material Planning



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Transcription:

Chapter 7 Production, Capacity and Material Planning

Production, Capacity and Material Planning Production plan quantities of final product, subassemblies, parts needed at distinct points in time To generate the Production plan we need: end-product demand forecasts Master production schedule Master production schedule (MPS) delivery plan for the manufacturing organization exact amounts and delivery timings for each end product accounts for manufacturing constraints and final goods inventory Production Management 0

Production, Capacity and Material Planning Based on the MPS: rough-cut capacity planning Material requirements planning determines material requirements and timings for each phase of production detailed capacity planning Production Management 02

Production, Capacity and Material Planning Updates Rough-Cut Capacity Detailed Capacity Planning End-Item Demand Estimate Master Production Schedule (MPS) Material Requirements Planning (MRP) Material Plan Shop Orders Purchasing Plan Shop Floor Control Updates Production Management 03

Master Production Scheduling Aggregate plan demand estimates for individual end-items demand estimates vs. MPS inventory capacity constraints availability of material production lead time... Market environments make-to-stock (MTS) make-to-order (MTO) assemble-to-order (ATO) Production Management 04

Master Production Scheduling MTS produces in batches minimizes customer delivery times at the expense of holding finishedgoods inventory MPS is performed at the end-item level production starts before demand is known precisely small number of end-items, large number of raw-material items MTO no finished-goods inventory customer orders are backlogged MPS is order driven, consisits of firm delivery dates Production Management 05

Master Production Scheduling ATO large number of end-items are assembled from a relatively small set of standard subassemblies, or modules automobile industry MPS governs production of modules (forecast driven) Final Assembly Schedule (FAS) at the end-item level (order driven) 2 lead times, for consumer orders only FAS lead time relevant Production Management 06

Master Production Scheduling MPS- SIBUL manufactures phones three desktop models A, B, C one wall telephone D MPS is equal to the demand forecast for each model WEEKLY MPS Jan Feb (= FORECAST) Product Week 2 3 4 5 Week 6 7 8 Model A 000 000 000 000 2000 2000 2000 2000 Model B 500 500 350 350 Model C 500 500 500 500 000 000 000 Model D 600 600 300 200 weekly total 300 3000 3600 2500 3350 2300 3200 3350 monthly total 2200 2200 Production Management 07

Master Production Scheduling MPS Planning - Example MPS plan for model A of the previous example: Make-to-stock environment No safety-stock for end-items I t = I t- + Q t max{f t,o t } I t = end-item inventory at the end of week t Q t = manufactured quantity to be completed in week t F t = forecast for week t O t = customer orders to be delivered in week t INITIAL DATA Model A Jan Feb Current Inventory = Week Week 600 2 3 4 5 6 7 8 forecast Ft 000 000 000 000 2000 2000 2000 2000 orders Ot 200 800 300 200 00 Production Management 08

Master Production Scheduling Batch production: batch size = 2500 I t = max{0, I t- } max{f t, O t } Q t 0, if It > 0 = 2500, otherwise I = max{0, 600} max{000, 200} = 400 >0 I 2 = max{0, 400} max{000, 800} = -600 <0 => Q2 = 2500 I 2 = 2500 + 400 max{000, 800} = 900, etc. MPS Jan Feb Current Inventory = 600 Week 2 3 4 5 Week 6 7 8 forecast Ft 000 000 000 000 2000 2000 2000 2000 orders Ot 200 800 300 200 00 Inventory It 600 400 900 900 2400 400 900 400 900 MPS Qt 2500 2500 2500 2500 2500 ATP 400 400 2200 2500 2500 2500 Production Management 09

Master Production Scheduling Available to Promise (ATP) ATP = 600 + 0 200 = 400 ATP 2 = 2500 (800 + 300) = 400, etc. Whenever a new order comes in, ATP must be updated Lot-for-Lot production MPS Jan Feb Current Inventory = 600 Week 2 3 4 5 Week 6 7 8 forecast Ft 000 000 000 000 2000 2000 2000 2000 orders Ot 200 800 300 200 00 Inventory It 600 400 0 0 0 0 0 0 0 MPS Qt 0 600 000 000 2000 2000 2000 2000 ATP 400 0 700 800 900 2000 2000 2000 Production Management 0

Master Production Scheduling MPS Modeling differs between MTS-ATO and MTO find final assembly lot sizes additional complexity because of joint capacity constraints cannot be solved for each product independently Production Management

Master Production Scheduling Make-To-Stock-Modeling Q it = production quantity of product i in period t I it = Inventory of product i at end of period t Dit = demand (requirements) for product i in time period t ai = production hours per unit of product i hi = inventory holding cost per unit of product i per time period Ai = set-up cost for product i G = production hours available in period t t y =,if set-up for product i occurs in period t (Q > 0) it it Production Management 2

Master Production Scheduling Make-To-Stock-Modeling min i= t= ( Ay + hi ) i,- t it it it n i= Q it it i n T i it i it I + Q I = D for all (i,t) a Q G for all t y it T it k = t Q 0; I 0; y {0,} it D ik 0 for all (i,t) it Production Management 3

Master Production Scheduling Assemble-To-Order Modeling two master schedules MPS: forecast-driven FAS: order driven overage costs holding costs for modules and assembled products shortage costs final product assemply based on available modules no explicit but implicit shortage costs for modules final products: lost sales, backorders Production Management 4

Master Production Scheduling m module types and n product types Q kt = quantity of module k produced in period t g kj = number of modules of type k required to assemble order j Decision Variables: I kt = inventory of module k at the end of period t y jt =, if order j is assembled and delivered in period t; 0, otherwise h k = holding cost π jt = penalty costs, if order j is satisfied in period t and order j is due in period t (t <t); holding costs if t > t Production Management 5

Master Production Scheduling Assemble-To-Order Modeling min subject to I j= t= I kt n L kt = a y k kt k = t= j= t= j jt m I k, t y jt L = for all j 0; y h + Q G jt t I kt + n n j= g L kj π y jt jt y jt for all (k, t) for all t { 0,} for all (j,k, t) Production Management 6

Master Production Scheduling Capacity Planning Bottleneck in production facilities Rough-Cut Capacity Planning (RCCP) at MPS level feasibility detailed capacity planning (CRP) at MRP level both RCCP and CRP are only providing information Production Management 7

Master Production Scheduling MPS: January Week Product 2 3 4 A 000 000 000 000 B - 500 500 - C 500 500 500 500 D 600-600 - Bill of capacity (min) Assembly Inspection A 20 2 B 24 2.5 C 22 2 D 25 2.4 Capacity requires (hr) Week weekly capacity requirements? Assembly: 000*20 + 500*22 + 600*25 = 68000 min = 33,33 hr Inspection: 000*2 + 500*2 + 600*2,4 = 6440 min = 07,33 hr etc. available capacity per week is 200 hr for the assembly work center and 0 hours for the inspection station; Available capacity 2 3 4 per week Assembly 33 083 333!! 883 200 Inspection 07 04 28!! 83 0 Production Management 8

Master Production Scheduling Infinite capacity planning (information providing) finding a feasible cost optimal solution is a NP-hard problem if no detailed bill of capacity is available: capacity planning using overall factors (globale Belastungsfaktoren) required input: MPS standard hours of machines or direct labor required historical data on individual shop workloads (%) Example from Günther/Tempelmeier C33.3: overall factors Production Management 9

Master Production Scheduling capacity planning using overall factors week product 2 3 4 5 6 A 00 80 20 00 20 60 B 40-60 - 40 - work on work on Total product critical machine non-critical machine A 2 3 B 4 2 6 historic capacity requirements on critical machines: 40% on machine a 60% on machine b Production Management 20

Master Production Scheduling in total 500 working units are available per week, 80 on machine a and 20 on machine b; Solution: overall factor = time per unit x historic capacity needs product A: machine a: x 0,4 = 0,4 machine b: x 0,6 = 0,6 product B: machine a: 4 x 0,4 =,6 machine b: 4 x 0,6 = 2,4 Production Management 2

Master Production Scheduling capacity requirements: product A machine week 2 3 4 5 6 a 40 32 48 40 48 24 b 60 48 72 60 72 36 other 200 60 240 200 240 20 capacity requirements: product B machine week 2 3 4 5 6 a 64-96 - 64 - b 96-44 - 96 - other 80-20 - 80 - Production Management 22

Master Production Scheduling total capacity requirements machine week 2 3 4 5 6 a 04 32 44 40 2 24 b 56 48 26 60 68 36 other 280 60 360 200 320 20 Production Management 23

Master Production Scheduling capacity requirements 400 300 200 00 0 2 3 4 5 6 week a (max 80) b (max 20) other (max 300) Production Management 24

Master Production Scheduling Capacity Modeling heuristic approach for finite-capacity-planning based on input/output analysis relationship between capacity and lead time G= work center capacity R t = work released to the center in period t Q t = production (output) from the work center in period t W t = work in process in period t U t = queue at the work center measured at the beginning of period t, prior to the release of work L t = lead time at the work center in period t Production Management 25

Production Management 26 Master Production Scheduling Lead time is not constant assumptions: constant production rate any order released in this period is completed in this period G W L Q U R U W Q R U U R G U Q t t t t t t t t t t t t t t = + = + = + = + = }, min{

Master Production Scheduling Example Period 0 2 3 4 5 6 G (hr/week) 36 36 36 36 36 36 R t (hours) 20 30 60 20 40 40 Q t (hours) 30 30 36 36 36 36 U t (hours) 0 0 0 24 8 2 6 W t (hours) 30 30 60 44 48 52 L t (weeks) 0,83 0,83,67,22,33,44 Production Management 27

Material Requirements Planning Inputs master production schedule inventory status record bill of material (BOM) Outputs planned order releases purchase orders(supply lead time) workorders(manufacturing lead time) Production Management 28

Material Requirements Planning Level 0 End-Item Level S/A 2 Legend: S/A = subassembly PP = purchased part Level 2 PP 5 4 S/A 6 2 MP = manufactured part RM = raw material Level 3 MP 9 2 PP 0 part # quantity Level 4 RM 2 RM 3 4 2 Production Management 29

Material Requirements Planning MRP Process goal is to find net requirements (trigger purchase and work orders) explosion Example: MPS, 00 end items yields gross requirements netting Net requirements = Gross requirements - on hand inventory - quantity on order done at each level prior to further explosion offsetting the timing of order release is determined lotsizing batch size is determined Production Management 30

Material Requirements Planning Example 7-6 Telephone Microphone S/A Receiver S/A 2 Upper Cover 3 Hand Set Assembly Lower Cover Tapping Screw 2 4 Housing S/A 5 2 Base Assembly Key Key Pad Pad Cord Production Management 3 Board Pack S/A 2 2 22 Rubber Pad 23 3 Hand Set Cord 4 Tapping Screw 4 22 24

Material Requirements Planning PART (gross requirements given) net requirements? Planned order release? Net requ.(week 2) = 600 (600 + 700) = -700 =>Net requ.(week2) = 0 Net requ.(week 3) = 000 (700 + 200) = -900 =>Net requ.(week3) = 0 Net requ.(week 4) = 000 900 = 00 etc. week current 2 3 4 5 6 7 8 gross requirements 600 000 000 2000 2000 2000 2000 scheduled receipts 400 700 200 projected inventory balance 200 600 700 900 0 0 0 0 0 net requirements 00 2000 2000 2000 2000 planned receipts planned order release Production Management 32

Material Requirements Planning Assumptions: lot size: 3000 lead time: 2 weeks week current 2 3 4 5 6 7 8 gross requirements 600 000 000 2000 2000 2000 2000 scheduled receipts 400 700 200 projected inventory balance 200 600 700 900 2900 900 900 2900 900 net requirements 00 2000 2000 2000 2000 planned receipts 3000 3000 3000 planned order release 3000 3000 3000 Production Management 33

Material Requirements Planning Multilevel explosion part number description Qty 2 base assembly 2 housing S/A 23 rubber pad 4 2 key pad lead time is one week lot for lot for parts 2, 23, 2 part 2: fixed lot size of 3000 Production Management 34

Part 2 current 2 3 4 5 6 7 8 gross requirements 600 000 000 2000 2000 2000 2000 scheduled receipts 400 400 400 projected inventory balance 800 200 000 400 2400 400 400 2400 400 net requirements 0 0 0 0 0 0 0 0 planned receipts 0 0 0 3000 0 3000 3000 0 planned order release 0 0 0 3000 0 3000 3000 0 0 x x x Part 2 current 2 3 4 5 6 7 8 gross requirements 0 0 0 3000 0 3000 3000 0 0 scheduled receipts x4 x4 x4 projected inventory balance 500 500 500 0 0 0 0 0 0 net requirements 0 0 0 0 0 0 0 0 planned receipts 0 0 2500 0 3000 3000 0 0 planned order release 0 2500 0 3000 3000 0 0 0 Part 23 current 2 3 4 5 6 7 8 gross requirements 0 0 0 2000 0 2000 2000 0 0 scheduled receipts 0000 projected inventory balance 5000 5000 25000 3000 3000 000 0 0 0 net requirements 0 0 0 0 0 0 0 0 planned receipts 0 0 0 0 0 000 0 0 planned order release 0 0 0 0 000 0 0 0 Part 2 current 2 3 4 5 6 7 8 gross requirements 0 0 2500 0 3000 3000 0 0 0 scheduled receipts 500 projected inventory balance 200 2700 200 200 0 0 0 0 0 net requirements 0 0 0 0 0 0 0 0 planned receipts 0 0 0 2800 3000 0 0 0 planned order release 0 0 2800 3000 0 0 0 0 x x Production Management 35 x

Material Requirements Planning MRP Updating Methods MRP systems operate in a dynamic environment regeneration method: the entire plan is recalculated net change method: recalculates requirements only for those items affected by change February Updated MPS for February Week Week Product 5 6 7 8 5 6 7 8 A 2000 2000 2000 2000 2000 2000 2300 900 B 350 - - 350 500-200 50 C 000-000 000 000-800 000 D - 300 200 - - 300 200 - Net Change for February Week Product 5 6 7 8 A 300-00 B 50 200-200 C -200 D Production Management 36

Material Requirements Planning Additional Netting procedures implosion: opposite of explosion finds common item combining requirements: process of obtaining the gross requirements of a common item pegging: identify the item s end product useful when item shortages occur Production Management 37

Material Requirements Planning Lot Sizing in MRP minimize set-up and holding costs can be formulated as MIP a variety of heuristic approaches are available simplest approach: use independent demand procedures (e.g. EOQ) at every level Production Management 38

Material Requirements Planning MIP Formulation Indices: i =...P t =...T m =...M Parameters: Γ(i) Γ -( i) s i c ij h i a mi b mi L mt oc m G D it label of each item in BOM (assumed that all labels are sorted with respect to the production level starting from the end-items) period t resource m set of immediate successors of item i set of immediate predeccessors of item i setup cost for item i quantity of itme i required to produce item j holding cost for one unit of item i capacity needed on resource m for one unit of item i capacity needed on resource m for the setup process of item i available capacity of resource m in period t overtime cost of resource m large number, but as small as possible (e.g. sum of demands) external demand of item i in period t Production Management 39

Material Requirements Planning I P i= i, t Decision variables: x it I it O mt Equations: = I i, t + xi, t cij j Γ ( i) mi it mi deliverd quantity of item i in period t inventory level of item i at the end of period t overtime hours required for machine m in period t y it binary variable indicating if item i is produced in period t (=) or not (=0) it P T min ( s y + h ( a x + b y ) L + O mt i it i it i= t= t= m= x jt D mt it i,t m,t I T M ) + oc m O x it Gy x it it mt 0 i,t, I, O 0, y {0,} it mt it i, m, t Production Management 40

Material Requirements Planning Multi-Echelon Systems Multi-echelon inventory each level is referred as an echelon total inventory in the system varies with the number of stocking points Modell (Freeland 985): demand is insensitive to the number of stocking points demand is normally distributed and divided evenly among the stocking points, demands at the stocking points are independent of one another a (Q,R) inventory policy is used β-service level (fill rate) is applied Q is determined from the EOQ formula Production Management 4

Material Requirements Planning Reorder point in (Q,R) policies: i: total annual inventory costs (%) c: unit costs A: ordering costs τ σ τ :lead time : variance of demand in lead time β z(β ) given a fill rate choose such that: L( z) φ = z ( y z) φ( y) dy : density of N(0,) distribution; L(z): standard loss function = ( β ) Q σ τ Production Management 42

Unit Normal Linear Loss Integral L(Z) Z.00.02.04.06.08 0.00.3989.3890.3793.3697.3602 0.0.3509.348.3329.3240.354 0.20.3069.2986.2904.2824.2745 0.30.2668.2592.258.2445.2374 0.40.2304.2236.270.204.2040 0.50.978.97.857.799.742 0.60.687.633.580.528.478 0.70.429.38.335.289.245 0.80.202.60.20.080.042 0.90.004.0968.0933.0899.0866.00.0833.0802.0772.0742.074.0.0686.0660.0634.0609.0585.20.056.0539.057.0496.0475.30.0456.0437.048.040.0383.40.0367.035.0336.032.0307.50.0293.0280.0268.0256.0244.60.0233.0222.022.0202.092.70.083.074.066.058.050.80.043 0..036.029.022.06.90.00.004.0099.0094.0089 2.00.0084.0080.0075.007.0067 2.0.0063.0060.0056.0053.0050 2.20.0047.0044.0042.0039.0037 2.30.0036.0034.0032.0030.0028 2.40.0027.0026.0024.0023.0022 2.50.002.008 Production Management.007.006.006 43

Material Requirements Planning Safety stock: s = z σ τ Reorder point: R = D + z τ σ τ Order quantity: Q Average inventory: = EOQ = Q I () = + s 2 I ( n ) = average 2 A ic inventory D for n stocking points I () = 2 2A D ic + zσ τ Production Management 44

Material Requirements Planning for two stocking points : demand at each point : D/2 variance of 2 lead - time demand : σ standard deviation is : σ τ / 2 τ / 2 average inventory at each stocking point is : 2 2AD/2 ic zσ + τ 2 = 2 ( Q / 2 + s) Production Management 45

Material Requirements Planning the average inventory for two stocking point is : I (2) = I ( n) 2 = n I () ( Q / 2 + s) = 2 2 ( Q / 2 + s) = 2 I () for each level the safety stock is :s/ the total safety stock is n s n Production Management 46

Material Requirements Planning Example: At the packaging department of a sugar refinery: A very-high-grade powdered sugar: Level 0 Boxed Sugar Level Sugar Cartons Sugar-refining lead time is five days; Production lead time (filling time) is negligible; Annual demand: D = 800 tons and σ= 2,5 Lead-time demand is normally distributed with Dτ = 6 tons and στ = 3,54 tons Fill rate = 95% A = $50, c = $4000, i = 20% Production Management 47

Material Requirements Planning Inventory at level 0 and? Safety stock? 2 AD 2 x 50 x800 Q = = = 0 tons ic 800 ß = 0,95 => z = 0,7 s = zστ = 0,7x3,54 = 2,5 tons Suppose we keep inventory in level 0 only, i.e., n = : Q 0 I ( ) = + s = + 2,5 = 7, 5tons 2 2 Suppose inventory is maintained at both level 0 and level, i.e., n = 2: I ( 2) = 2I () = 0, 62 tons The safety stock in each level is going to be: s 2 2,5 = 2 =,77tons Production Management 48

Material Requirements Planning MRP as Multi-Echelon Inventory Control continuous-review type policy (Q,R) hierarchy of stocking points (installation) installation stock policy echelon stock (policy): installation inventory position plus all downstream stock MRP: rolling horizon level by level approach bases ordering decisions on projected future installation inventory level Production Management 49

Material Requirements Planning All demands and orders occur at the beginning of the time period orders are initiated immediately after the demands, first for the final items and then successively for the components all demands and orders are for an integer number of units T= planning horizon τ i = lead time for item i s i = safety stock for item I R i = reorder point for item I Q i =Fixed order quantity of item i D it = external requirements of item i in period t Production Management 50

Material Requirements Planning Installation stock policies (Q,R i ) for MRP: a production order is triggered if the installation stock minus safety stock is insufficient to cover the requirements over the next τ i periods an order may consist of more than one order quantity Q if lead time τ i = 0, the MRP is equal to an installation stock policy. safety stock = reorder point Production Management 5

Material Requirements Planning Echelon stock policies (Q,R e ) for MRP: Consider a serial assembly system Installation is the downstream installation (final product) the output of installation i is the input when producing one unit of item i- at the immediate downstream installation w i = installation inventory position at installation i I i = echelon inventory position at installation i (at the same moment) I i = w i + w i- +... w a multi-echelon (Q,R) policy is denoted by (Q i,r ie ) R i e gives the reorder point for echelon inventory at i Production Management 52

Material Requirements Planning R e = s +Dτ R ie = s i +Dτ i +R i- e +Q i- Example: Two-level system, 6 periods 0 0 e e I = 8, I 2 = 38, R = 20, R 2 = 34, Q = 0, Q 2 = D = 2 (Item ), τ =, τ 2 = 2 30 Production Management 53

Material Requirements Planning Item Item 2 Period 2 3 4 5 6 Demand 2 2 2 2 2 2 Level w 8 26 24 22 20 28 Production 0 0 0 0 0 0 Level w2 0 0 0 0 30 0 Production 0 0 30 0 0 0 Suppose now that five units were demanded in period 2: Period 2 3 4 5 6 7 Demand 5 2 2 2 2 2 Item Item 2 Level w Level w2 23 0 2 0 9 30 27 30 25 30 23 30 Production Production 0 30 0 0 0 0 0 0 0 0 0 0 Production Management 54

Material Requirements Planning Lot Size and Lead Time lead time is affected by capacity constraints lot size affects lead time batching effect an increase in lot size should increase lead time saturation effect when lot size decreases, and set-up is not reduced, lead time will increase expected lead time can be calculated using models from queueing theory (M/G/) Production Management 55

Material Requirements Planning L = lead time L = 2 2 ( λ / μ) + λ σ 2λ( λ / μ) 2 + μ λ = mean arrival rate μ = mean service rate σ 2 = service time variance Production Management 56

Production Management 57 Material Requirements Planning 2 2 2 n j j j j j ) ( ) ( : variance time - service : time service mean : batches of rate arrival mean j product for lotsize Q j product for time up - set S j product for time production - unit t j product for period per demand + = + = = = = = = = = = = = = = μ λ λ σ μ λ λ λ λ n j j n j j j j j j j j n j j n j n j j j j j Q t S Q t S Q D D

Material Requirements Planning Production Management 58

Material Planning Work to do: 7.7ab, 7.8, 7.0, 7., 7.4 (additional information: available hours: 225 (Paint), 30 (Mast), 00 (Rope)), 7.5, 7.6, 7.7, 7.3-7.34 Production Management 59