Push-Pull Production and Supply Chain Sy...

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Presentation Transcript

Push-Pull: Strategic Thinking for Operational Excellence : 

Push-Pull: Strategic Thinking for Operational Excellence Yang Sun [email protected] GWC 521 Department of Industrial Engineering Arizona State University

Teaching Philosophy : 

[email protected] 2 Teaching Philosophy Basics Intuition Synthesis Know How Know Why Major Source: Wally Hopp and Mark Spearman, Factory Physics, 2nd Ed., 2000

Basics : 

Basics

Essential Context : 

[email protected] 4 Essential Context The IDIB Portfolio Information Decision Implementation Buffer Sources: Lee Schwarz, Lecture Notes, 2003 Lee Schwarz, "A New Teaching Paradigm: The Information/Control/Buffer Portfolio", Production and Operations Management 7:2, pp. 125-131, 1998 Dan Shunk, “Knowledge Management”, Lecturer Notes.

Variability Basics : 

[email protected] 5 Variability Basics Variability is a fact of life. Increasing variability (always) degrades system performance. Demand Variability The Bullwhip Effect (Volatility Amplification Law) Forecasting Laws Process Variability Think about Little’s Law! Technology/Organization Variability Fruit Flies (Clockspeed Amplification Law) Variability will be buffered by some combination of inventory, capacity, and time. Additional Sources: Hau Lee et al., Information distortion in a Supply Chain: The Bullwhip Effect, Management Science, 43(4), 1997; or The Bullwhip Effect in Supply Chains, Sloan Management Review 38(3), Spring1997 Charley Fine, CLOCKSPEED: Winning Industry Control in the Age of Temporary Advantage, 1998

Buffer Basics : 

[email protected] 6 Buffer Basics Inventory Capacity Time Buffer Strategy Buffer Flexibility/Pooling Buffer Location Definition: Lean = Minimal Buffer Cost TOYOTA Lean Phases: [Eliminate Direct Waste] ? (Value-Add) [Substitute Capacity for Inventory Buffers] (Push -> Pull) ? [Reduce Variability] ? [Reduce Capacity Buffers] (Cont. Improv.) Sources: Wally Hopp, Supply Chain Sciences, 2005

Lessons from History : 

[email protected] 7 Lessons from History A history of buzzwords EOQ; MRP; MPR-II; ERP; BPR; MES; APS; Kanban; JIT; TQM; CIM; FMS; …… What went wrong?

Lessons from History (cont’d) : 

[email protected] 8 Lessons from History (cont’d) Problems with traditional approaches: Scientific Management has stressed math over realism MRP is fundamentally flawed, in the basics, not the details JIT is a collection of methods and slogans, not systems Bottom lines: Supply Chain/Manufacturing systems are large scale, complex, and varied. No “technological silver bullet” can save us. Continuous improvement is essential.

Definition: Supply Network : 

[email protected] 9 Definition: Supply Network A value-oriented network of processes and stockpoints that deliveries goods and services to customers. Sources: Wally Hopp, Supply Chain Sciences, 2005

Definition: Push/Pull Production System : 

[email protected] 10 Definition: Push/Pull Production System Push Systems: schedule work releases based on demand. Pull Systems: authorize work releases based on system status.

So, pull is not… : 

[email protected] 11 So, pull is not… Kanban Kanban is a special case of pull ConWIP is a generalized pull concept Make-to-Order: MRP with firm orders on MPS is make-to-order. But it does not limit WIP and is therefore a push system. Make-to-Stock: Pull systems do replenish inventory voids. But jobs can be associated with customer orders. Forecast Free: Toyota’s classic system made cars to forecasts. Use of tact times or production smoothing often involves production without firm orders (and hence forecasts).

The magic of pull… : 

[email protected] 12 The magic of pull… Cycle Time (?t) ? Variability ? Cost ? Service ? Quality ? Flexibility ? You don’t never make nothin’ and send it no place. Somebody has to come get it. – Hall 1983 I dislike this definition. The key is the WIP cap. Why control the WIP? ConWIP Observability, Efficiency, and Robustness Overcoming rigidity of pull WIP

Exercise : 

[email protected] 13 Exercise Are the following systems push or pull? Kinko’s copy shop Soda vending machine “Pure” MRP system Doctor’s office Supermarket (goods on shelves) Tandem line with finite interstation buffers Runway at O’Hare during peak periods Order entry server at Amazon.com

Definition: Push/Pull Supply Chain : 

[email protected] 14 Definition: Push/Pull Supply Chain A push supply chain makes production and distribution decisions based on forecasts (Build-to-stock) A pull supply chain drives production and distribution by customer orders (Build/Assembly-to-Order) Key concept: Location of the push/pull boundary (PPB) (strategic inventory point, inventory/order (I/O) interface) Source: Simchi-Levi et al., Designing and Managing the Supply Chain, 2003

Push/pull Boundary Location : 

[email protected] 15 Push/pull Boundary Location Real World Examples: IBM PCB Case GM Case (WSJ Oct. 21, 96, A1) HP DeskJet Case (See Lee, Billington, and Carter, HP gains control of inventory and service through design for localization, Interfaces 23(4), 1993; Feitzinger and Lee, Mass Customization at HP: The Power of Postponement, HBR Jan-Feb, 1997) Goal: eliminate entire portion of cycle time seen by customers by building to stock. (Need for responsiveness) Basic Tradeoff: Responsiveness vs. Inventory (Time vs. Cost) Levels: Product design (postponement) and process design (quick response mfg)

Basic Takeaways : 

[email protected] 16 Basic Takeaways Most systems are hybrid Push/pull supply chain is a strategic design Key: where the push/pull boundary is located Lead time is the primary driving factor. (?t) Push/pull production is a control policy Push keywords: Ctrl Release ? Utilization Pull keywords: Ctrl WIP ? Cycle Time (?t) A pull thinking is always desired

Intuition : 

Intuition

The problem is choice : 

[email protected] 18 The problem is choice Yes, but not only…

Fisher’s Matrix : 

[email protected] 19 Fisher’s Matrix Source: Marshall Fisher, “What is the right supply chain for your product”, Harvard Business Review, March-April 1997

Hau Lee’s Matrix : 

[email protected] 20 Hau Lee’s Matrix Demand Uncertainty Low (Functional Product) High (Innovative Product) Low (Stable Process) Low (Functional Product) High (Evolving Process) Supply Uncertainty Demand Uncertainty Low (Functional Product) High (Innovative Product) Low (Stable Process) Low (Functional Product) High (Evolving Process) Supply Uncertainty Source: Hau Lee, “Aligning supply chain strategies with product uncertainties”, California Management Review, 44(3), 2002

Simchi-Levi’s Matrix : 

[email protected] 21 Simchi-Levi’s Matrix Source: David Simchi-Levi et al., Designing and Managing the Supply Chain, 2003

Where to locate the PPB? : 

[email protected] 22 Where to locate the PPB? Auto Semiconductor/Electronics Grocery … Everything Material Assembly Parts Inventory Finished Goods Process Deliver CUSTOMERs Push Push Pull Pull Push Pull Push Pull

Semiconductor Case Study : 

[email protected] 23 Semiconductor Case Study Source: Yang Sun, Comparing Semiconductor Supply Chain Strategies under Demand Uncertainty and Process Variability, Master’s Thesis, ASU

Forecasting and Demand Uncertainty : 

[email protected] 24 Forecasting and Demand Uncertainty There is a confusion between two kinds of forecasting: ‘what can be sold (WCBS)’ and ‘what will be sold (WWBS)’ (Montgomery et al. Forecasting and Time Series Analysis, 1990). The former represents the possible market trends. The latter always represents the company’s capacity and budget constraint. Since capacity utilization is extremely important in semiconductor manufacturing, it is always the WWBS forecasts that triggers the production plan (push). The semiconductor industry is always under stress: either ‘lack-for-sales’ (LFS) (WCBS < WWBS) or ‘lack-for-capacity’ (LFC) (WCBS > WWBS) (Shunk et al. Electronics Industry Drives of Intermediation and Disintermediation, submitted, 2005) Note that huge demand uncertainty EXISTS in the semiconductor industry. WWBS WCBS WCBS (LFC) (LFS)

Process Variability : 

[email protected] 25 Process Variability Integrated into a cycle time distribution Issues that can affect the variance of mfg cycle times: variable capacity, shortage of material, variable priorities in lot release, scheduling and dispatching, frequent machine breakdowns, operator error, etc. Issues that can affect the variance of delivery time: globally distributed destination, regional traffic condition, variable 3PL/4PL, holding in custom Fab Probe Assembly Test Die Bank Final Goods Delivery Material CUSTOMER Front-end Back-end Delivery

Performance Metrics: Cost and Service : 

[email protected] 26 Performance Metrics: Cost and Service On-time delivery service is of critical importance in today’s semiconductor business, but companies are not doing very well today (case: Gateway penalized Intel by shifting business to AMD to blame Intel’s bad delivery service.) Cost (per product sold) performance = front-end mfg costs + back-end mfg costs + inventory (holding) costs + penalty costs based on tardiness Delivery cost ignored (Quality is a given in SC analysis.) Penalty L.T. Due

The Simulation Model : 

[email protected] 27 The Simulation Model Fab Probe Assembly Test Die Bank Final Goods Delivery Material CUSTOMER Front-end Back-end Delivery WWBS Order Generator based on WCBS Forecasts Push Pull (Pull Strategy) Pull (Push-Pull Strategy) Pull (Push Strategy) Performance

DOE Factors : 

[email protected] 28 DOE Factors fractional factorial design Assume: two products, same family, assembled from common generic parent die

A General Case Instance : 

[email protected] 29 A General Case Instance And other assumptions Duarte, 2001 IC Knowledge, 2003

The ‘Global’ Experiment: Effects : 

[email protected] 30 The ‘Global’ Experiment: Effects Since in simulation experiments almost all factors have none-zero effects, Sequential Bifurcation Analysis is suggested by Wan et al. 2003 (QSR Winner paper INFORMS Atlanta ‘03) Group Screening: Factors are grouped as ‘Important’ and ‘Unimportant’ Step-Down: In each step, a group of factors are tested for importance Strategy

Screened Factorial Effects : 

[email protected] 31 Screened Factorial Effects Primary Factors: Due-date Lead Time and Penalty Weight (?t is the game) Secondary Factors: Demand Pattern and Mfg Cycle Time Variability Unimportant Factor: Final Product Logistics Time Variability (Of course “costs” have significant effects, but do we need to analyze them?)

Due-dates vs. Penalty Weights : 

[email protected] 32 Due-dates vs. Penalty Weights Light Penalty Heavy Penalty

Demand Pattern vs. Mfg C.T. Variability : 

[email protected] 33 Demand Pattern vs. Mfg C.T. Variability $ Total Cost per wafer sold – Product A Low Variability High Variability Low Variability High Variability Low Variability High Variability Low Demand Mid Demand High Demand Low Demand Mid Demand High Demand $ Total Cost per wafer sold – Product A High Variability Low Variability High Variability Low Variability Low Variability High Variability High Variability medium due-date and light penalty loose due-date and heavy penalty

The analytical results lead to a conceptual decision framework : 

[email protected]ASU 34 The analytical results lead to a conceptual decision framework Due-Date Lead Time Tight Medium Loose Importance of on-time delivery service Less Important Far More Important Push Pull Step-down to Layer Two Comparison This is Layer One

Layer Two: Push-Pull Can be Appropriate : 

[email protected] 35 Layer Two: Push-Pull Can be Appropriate * Manufacturing variability contains both front-end and back-end variability medium due-date + light penalty or loose due-date + heavy penalty Aggregate Demand Process Variability

What else can be done? : 

[email protected] 36 What else can be done? Pooling/Postponement Hybrid Source: Alex Brown et al., Xilinx improves its semiconductor supply chain using product and process postponement, Interfaces, 30(4), 2000

Technology Involvement : 

[email protected] 37 Technology Involvement Source: Joong-In Kim and Dan Shunk, working paper

Intuition Takeaways : 

[email protected] 38 Intuition Takeaways ?t is the name of the game. From the semiconductor case, lead time customers require and the perceived importance of on-time delivery are the driving factors. We also need to understand not only the nature of the demands but that of the processes. Supply Chain Visibility (both Demand Stream and Supply Stream) is important. Implementation issues should be addressed. Transition from push to pull needs tremendous cultural change and technological support.

Synthesis -- Push-Pull It All Together : 

Synthesis -- Push-Pull It All Together

A Customer-Driven Supply Chain Framework : 

[email protected] 40 A Customer-Driven Supply Chain Framework Semiconductor SC example Source: Yang Sun, Dan Shunk, John Fowler, Proceedings of INFORMS Annual Meeting, San Francisco, Nov. 2005 Info Flow Material Flow

The Semiconductor Flow : 

[email protected] 41 CUSTOMERS Die Bank Wafer Fabrication (W/F) Assembly & Test (A/T) Configuration & Shipment (C/S) The Semiconductor Flow Raw Material

Critical Decisions in the Semiconductor Supply Chain : 

[email protected] 42 Critical Decisions in the Semiconductor Supply Chain Wafer Fabrication (W/F) Assembly & Test (A/T) Configuration & Shipment (C/S) Source: Shunk et al., ASU DBR Survey, 2004

How are they made? : 

[email protected] 43 How are they made? Wafer Fabrication (W/F) Assembly & Test (A/T) Configuration & Shipment (C/S) Decision Technique Current Ideal? W/F A/T C/S 2004 Survey Result Logistic Estimation of Probabilities

Inventory Management : 

[email protected] 44 Inventory Management Key to Supply Chain Management Deterministic model – adjust solution - EOQ to compute order quantity, then add safety stock EOQ Assumptions (not realistic) Key Insight: There is a tradeoff between lot size and inventory Stochastic models - news vendor model - base stock and (Q,r) models - (s,S) models - Multi-echelon and network models

Prioritizing and Releasing : 

[email protected] 45 Prioritizing and Releasing There is sometimes confusion between the production planning domain and the shop floor control domain. We need to connect planning and execution. The releasing function is key to Push-Pull. It connects supply chain planning and factory operation. Supply Chain: Release by forecast vs. by order Factory: MRP Push vs. Kanban/ConWIP Pull Allocation is important for determining “who gets what”.

Logistics : 

[email protected] 46 Logistics Key to Supply Chain Management Often performed by a 3PL or 4PL Begin to contribute large portion to the GDP

Within The Four Walls : 

[email protected] 47 Within The Four Walls Capacity Release Scheduling Dispatching $$$$ $$$ $$ $ Recommended reading: John Fowler et al., Workload Control in the Semiconductor Industry, Production Planning & Control, 13(7), 2002 Shop floor ctrl Workforce planning Quality ctrl …

Synthesis and Implementation : 

[email protected] 48 Synthesis and Implementation The Strategic Importance of Details The Practice Matter of Implementation System view Means-ends analysis Creative alternative generation Modeling and optimization Iteration Communication and Teamwork

Coordination and Collaboration : 

[email protected] 49 Coordination and Collaboration Value of Info Sharing/SC Visibility Coordinated Decision Making Knowledge Sharing and Communities of Common Interests Risk Sharing Contract Management VMI and CPFR Remodeling the Supply Chains to pursue Supply Network Collaboration Recommended Reading: Gérard Cochan, Matching Supply with Demand, 2005

Slide 50: 

[email protected] 50 We think in generalities, we live in detail. –Alfred North Whitehead

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