Presentation on theme: "ENGM 663 Paula Jensen Chapter 6: A Science of Manufacturing"— Presentation transcript:
1ENGM 663 Paula Jensen Chapter 6: A Science of Manufacturing Chapter 7: Basic Factory Dynamics
2Agenda Factory Physics Chapter 6: A Science of Manufacturing (From 2nd Ed)Chapter 7: Basic Factory Dynamics(New Assignment Chapter 6: Problem 1Chapter 7: Problems 5, 8, 10)Test 1 Study Guide
3Objectives, Measures, and Controls I often say that when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind; it may be the beginning of knowledge, but have scarcely, in your thoughts, advanced to the stage of Science, whatever the matter may be.– Lord Kelvin
4Why a Science of Manufacturing? Confusion in Industry:too many “revolutions”management by buzzwordsales glitz over substanceConfusion in Academia:high-powered methodology applied to non-problemshuge variation in what is taughtExample of Other Fields:Civil Engineering–statics, dynamicsElectrical Engineering – electricity and magnetismMany others
5Automobile Design F = ma 200 Nt (1000 kg) (2.7 m/s2) = 2,700 Nt. Requirements:Mass of car of 1000 kgAcceleration of 2.7 meters per second squared (zero to 60 in seconds)Engine with no more than 200 Newtons of forceCan we do it?Answer:No way!F = ma200 Nt (1000 kg) (2.7 m/s2) = 2,700 Nt.
6? Factory Design Requirements: Can we do it? Answer: Who knows? 3000 units per day,with a lead time of not greater than 10 days,and with a service level (percent of jobs that finish on time) of at least 90%.Can we do it?Answer:?Who knows?
8Goals of a Science of Manufacturing Tools:descriptive modelsprescriptive modelssolution techniquesTerminology:rationalize buzzwordsrecognize commonalities across environmentsPerspective:basicsintuitionsynthesis
9The Nature of Science Purpose: Steps: The grand aim of all science is to cover the greatest number of empirical facts by logical deduction from the smallest number of hypothesis or axioms.--- Albert EinsteinSteps:1. Observation.2. Classification.3. Theoretical Conjecture.4. Experimental verification/refutation.5. Repeat.
10Systems AnalysisDefinition: Systems analysis is a structured approach to problem-solving that involves1. Identification of objectives (what you want to accomplish), measures (for comparing alternatives), and controls (what you can change).2. Generation of specific alternatives.3. Modeling (some form of abstraction from reality to facilitate comparison of alternatives).4. Optimization (at least to the extent of ranking alternatives and choosing “best” one).5. Iteration (going back through the process as new facets arise).
11System Analysis Paradigm REAL WORLDOPERATIONSANALYSISANALOG WORLDConjecture ObjectivesVerify constraintsIdentify AlternativesChoose Measures of EffectivenessSpecify Parameters and ControlsModel InteractionsVerify & Validate ModelSYSTEMSDESIGNCompare AlternativesChoose PoliciesAsk “What If” QuestionsCompare ControlsOptimize Control LevelsSensitivity AnalysisImplement PoliciesTrain UsersFine Tune SystemIMPLEMENTATIONEVALUATIONEvaluate System PerformanceLook For OversightsIdentify Future OpportunitiesValidate Model PredictionsQuestion AssumptionsIdentify Other Controls
12General Measures and Objectives Fundamental Objective:elementary starting pointsource of agreementexample - make money over the long-termHierarchy of Objectives:more basic objectives that support fundamental objectivecloser to improvement policiesTradeoffs:objectives conflictwe need models
14Corporate Measures and Objectives Fundamental Objective: Maximize the wealth and well-being of the stakeholders over the long term.Financial Performance Measures:1. Net-profit.2. Return on investment.Components:1. Revenue.2. Expenses.3. Assets.
15Plant Measures and Objectives Throughput: product that is high quality and is sold.Costs: Operating budget of plant.Assets: Capital equipment and WIP.Objectives:Maximize profit.Minimize unit costs.Tradeoffs: we would like (but can’t always have)ThroughputCostAssets
16Systems Analysis Tools Process Mapping:identify main sequence of activitieshighlight bottlenecksclarify critical connections across business systemsWorkshops:structured interaction between various partiesmany methods: Nominal Group Technique, Delphi, etc.roles of moderator and provocateur are critical
17Systems Analysis Tools (cont.) Conjecture and Refutation:promotes group ownership of ideasplaces critical thinking in a constructive modeeveryday use of the scientific methodModeling:always done with specific purposevalue of model is its usefulnessmodeling is an iterative process
18The Need for Process Mapping Example: North American Switch Manufacturer week leadtimes in spite of dramatically reduced factory cycle times:10% Sales15% Order Entry15% Order Coding20% Engineering10% Order Coding15% Scheduling5% Premanufacturing and Manufacturing10% Delivery and PrepConclusion: Lead time reduction must address entire value delivery system.
19Process Mapping Activities Purpose: understand current system byidentifying main sequence of activitieshighlighting bottlenecksclarifying critical connections across business systemTypes of Maps:Assembly Flowchart: diagram of activities to assembly product.Process Flowchart: diagram of how pieces of system interrelate in an organization.Relationship Map: diagram of specific steps to accomplish a task, without indication of functions or subsystems.Cross-Functional Process Map: diagram of specific steps to accomplish a task organized by function or subsystem responsible for the step.
24Conclusions Science of Manufacturing: Systems Approach: Modeling: important for practiceprovides a structure for OM educationSystems Approach:one of the most powerful engineering toolsa key management skill as well (e.g., re-engineering)Modeling:part, but not all, of systems analysiskey to a science of manufacturingmore descriptive models are needed
25Basic Factory Dynamics Physics should be explained as simply as possible, but no simpler.– Albert Einstein
26HAL Case Is HAL lean? What data do we need to decide? Large Panel Line: produces unpopulated printed circuit boardsLine runs 24 hr/day (but 19.5 hrs of productive time)Recent Performance:throughput = 1,400 panels per day (71.8 panels/hr)WIP = 47,600 panelsCT = 34 days (663 hr at 19.5 hr/day)customer service = 75% on-time deliveryIs HAL lean?What data do we need to decide?
27HAL - Large Panel Line Processes Lamination (Cores): press copper and prepreg into core blanksMachining: trim cores to sizeInternal Circuitize: etch circuitry into copper of coresOptical Test and Repair (Internal): scan panels optically for defectsLamination (Composites): press cores into multiple layer boardsExternal Circuitize: etch circuitry into copper on outside of compositesOptical Test and Repair (External): scan composites optically for defectsDrilling: holes to provide connections between layersCopper Plate: deposits copper in holes to establish connectionsProcoat: apply plastic coating to protect boardsSizing: cut panels into boardsEnd of Line Test: final electrical test
28HAL Case - Science? Need relationships between WIP, TH, CT, service! External Benchmarkingbut other plants may not be comparableInternal Benchmarkingcapacity data: what is utilization?but this ignores WIP effectsNeed relationships between WIP, TH, CT, service!
29DefinitionsWorkstations: a collection of one or more identical machines.Parts: a component, sub-assembly, or an assembly that moves through the workstations.End Items: parts sold directly to customers; relationship to constituent parts defined in bill of material.Consumables: bits, chemicals, gasses, etc., used in process but do not become part of the product that is sold.Routing: sequence of workstations needed to make a part.Order: request from customer.Job: transfer quantity on the line.
30Definitions (cont.)Throughput (TH): for a line, throughput is the average quantity of good (non-defective) parts produced per unit time.Work in Process (WIP): inventory between the start and endpoints of a product routing.Raw Material Inventory (RMI): material stocked at beginning of routing.Crib and Finished Goods Inventory (FGI): crib inventory is material held in a stockpoint at the end of a routing; FGI is material held in inventory prior to shipping to the customer.Cycle Time (CT): time between release of the job at the beginning of the routing until it reaches an inventory point at the end of the routing.
31Factory Physics®Definition: A manufacturing system is a goal-oriented network of processes through which parts flow.Structure: Plant is made up of routings (lines), which in turn are made up of processes.Focus: Factory Physics® is concerned with the network and flows at the routing (line) level.
32Parameters Descriptors of a Line: 1) Bottleneck Rate (rb): Rate (parts/unit time or jobs/unit time) of the process center having the highest long-term utilization.2) Raw Process Time (T0): Sum of the long-term average process times of each station in the line.3) Congestion Coefficient (): A unitless measure of congestion.Zero variability case, a = 0.“Practical worst case,” a = 1.“Worst possible case,” a = W0.Note: we won’t use quantitatively,but point it out to recognize that lineswith same rb and T0 can behave verydifferently.
33Parameters (cont.) Relationship: Critical WIP (W0): WIP level in which a line having no congestion would achieve maximum throughput (i.e., rb) with minimum cycle time (i.e., T0).W0 = rb T0
34The Penny Fab Characteristics: Parameters: Four identical tools in series.Each takes 2 hours per piece (penny).No variability.CONWIP job releases.Parameters:rb =T0 =W0 =a =0.5 pennies/hour8 hours0.5 8 = 4 pennies0 (no variability, best case conditions)
76Best Case PerformanceBest Case Law: The minimum cycle time (CTbest) for a given WIP level, w, is given byThe maximum throughput (THbest) for a given WIP level, w is given by,
77Best Case Performance (cont.) Example: For Penny Fab, rb = 0.5 and T0 = 8, so W0 = 0.5 8 = 4,which are exactly the curves we plotted.
78A Manufacturing Law Insights: Little's Law: The fundamental relation between WIP, CT, and TH over the long-term is:Insights:Fundamental relationshipSimple units transformationDefinition of cycle time (CT = WIP/TH)
81Penny Fab Two Simulation (Time=0) 22 hr5 hr3 hr10 hr
82Penny Fab Two Simulation (Time=2) 742 hr5 hr3 hr10 hr
83Penny Fab Two Simulation (Time=4) 7692 hr5 hr3 hr10 hr
84Penny Fab Two Simulation (Time=6) 7892 hr5 hr3 hr10 hr
85Penny Fab Two Simulation (Time=7) 1712892 hr5 hr3 hr10 hr
86Penny Fab Two Simulation (Time=8) 17121092 hr5 hr3 hr10 hr
87Penny Fab Two Simulation (Time=9) 17191210142 hr5 hr3 hr10 hr
88Penny Fab Two Simulation (Time=10) 17191212142 hr5 hr3 hr10 hr
89Penny Fab Two Simulation (Time=12) 1719172214142 hr5 hr3 hr10 hr
90Penny Fab Two Simulation (Time=14) 171917221619242 hr5 hr3 hr10 hr
91Penny Fab Two Simulation (Time=16) 1719172219242 hr5 hr3 hr10 hr
92Penny Fab Two Simulation (Time=17) 271922222019242 hr5 hr3 hr10 hr
93Penny Fab Two Simulation (Time=19) 27292222202424222 hr5 hr3 hr10 hr
94Penny Fab Two Simulation (Time=20) 27Note: job will arrive atbottleneck just in timeto prevent starvation.292222222424222 hr5 hr3 hr10 hr
95Penny Fab Two Simulation (Time=22) 27292732252424242 hr5 hr3 hrNote: job will arrive atbottleneck just in timeto prevent starvation.10 hr
96Penny Fab Two Simulation (Time=24) 27292732252934272 hr5 hr3 hrAnd so on….Bottleneck will juststay busy; all otherswill starve periodically10 hr
97Worst CaseObservation: The Best Case yields the minimum cycle time and maximum throughput for each WIP level.Question: What conditions would cause the maximum cycle time and minimum throughput?Experiment:set average process times same as Best Case (so rb and T0 unchanged)follow a marked job through systemimagine marked job experiences maximum queueing
105Worst Case Performance Worst Case Law: The worst case cycle time for a given WIP level, w, is given by,CTworst = w T0The worst case throughput for a given WIP level, w, is given by,THworst = 1 / T0Randomness?None - perfectly predictable, but bad!
106Practical Worst CaseObservation: There is a BIG GAP between the Best Case and Worst Case performance.Question: Can we find an intermediate case that:divides “good” and “bad” lines, andis computable?Experiment: consider a line with a given rb and T0 and:single machine stationsbalanced linesvariability such that all WIP configurations (states) are equally likely
107PWC Example – 3 jobs, 4 stations clumpedup statesspreadout states
108Practical Worst CaseLet w = jobs in system, N = no. stations in line, and t = process time at all stations:CT(single) = (1 + (w-1)/N) tCT(line) = N [1 + (w-1)/N] t= Nt + (w-1)t= T0 + (w-1)/rbTH = WIP/CT= [w/(w+W0-1)]rbFrom Little’s Law
109Practical Worst Case Performance Practical Worst Case Definition: The practical worst case (PWC) cycle time for a given WIP level, w, is given by,The PWC throughput for a given WIP level, w, is given by,where W0 is the critical WIP.
110TH vs. WIP: Practical Worst Case Best CaserbPWCGood (lean)Bad (fat)Worst Case1/T0W0
111CT vs. WIP: Practical Worst Case PWCBad (fat)Best CaseGood(lean)T0W0
112Penny Fab Two Performance Note: processtimes in PF2have var equalto PWC.But… unlikePWC, it hasunbalancedline and multimachinestations.Best CaserbPenny Fab 2Practical Worst Case1/T0Worst CaseW0
113Penny Fab Two Performance (cont.) Worst CasePractical Worst CasePenny Fab 21/rbT0Best CaseW0
115HAL Case - Situation Critical WIP: rbT0 = 114 33.9 = 3,869 Actual Values:CT = 34 days = 663 hours (at 19.5 hr/day)WIP = 47,600 panelsTH = 71.8 panels/hourConclusions:Throughput is 63% of capacityWIP is 12.3 times critical WIPCT is 24.1 times raw process time
116HAL Case - Analysis Conclusion: actual system is much worse than PWC! TH Resulting from PWC with WIP = 47,600?Much higherthan actual TH!WIP Required for PWC to Achieve TH = 0.63rb?Much lower thanactual WIP!Conclusion: actual system is much worse than PWC!
117HAL Internal Benchmarking Outcome “Lean" Region“Fat" Region
118Labor Constrained Systems Motivation: performance of some systems are limited by labor or a combination of labor and equipment.Full Flexibility with Workers Tied to Jobs:WIP limited by number of workers (n)capacity of line is n/T0Best case achieves capacity and has workers in “zones”ample capacity case also achieves full capacity with “pick and run” policy
119Labor Constrained Systems (cont.) Full Flexibility with Workers Not Tied to Jobs:TH depends on WIP levelsTHCW(n) TH(w) THCW(w)need policy to direct workers to jobs (focus on downstream is effective)Agile Workforce Systemsbucket brigadeskanban with shared tasksworksharing with overlapping zonesmany others
120Factory Dynamics Takeaways Performance Measures:throughputWIPcycle timeserviceRange of Cases:best casepractical worst caseworst caseDiagnostics:simple assessment based on rb, T0, actual WIP,actual THevaluate relative to practical worst case