advanced manufacturing systems design © 2000 john w. nazemetz lecture 9 topic : manufacturing...

Advanced Manufacturing Advanced Manufacturing Systems DesignSystems Design

© 2000 © 2000 John W. NazemetzJohn W. Nazemetz

Lecture 9 Topic :Lecture 9 Topic : Manufacturing Manufacturing Planning and ControlPlanning and Control

Segment A Topic:Segment A Topic: Planning Concepts Planning Concepts

Computer Integrated Manufacturing Systems © 2000 John W. NazemetzSlide 2

ADVANCED ADVANCED MANUFACTURING MANUFACTURING SYSTEMS DESIGNSYSTEMS DESIGN

Manufacturing Manufacturing Planning and Control Planning and Control

Planning ConceptsPlanning Concepts


OverviewOverview

• Manufacturing PlanningManufacturing Planning– Fundamental Concepts– Variation –”The Enemy”– Dealing With Variation

• Product Design• Demand Patterns• Aggregation• In Production and Distribution


Fundamental Concepts Fundamental Concepts (1)(1)

Appropriate Manufacturing PhilosophyAppropriate Manufacturing Philosophy– Job, Batch, Mass Production– Where Product is in Product Life Cycle– Dealing With Variations

• Product Design• Process Design• Production/Demand

– Inventory of Goods– Excess Capacity/Change capacity

– Degree of Automation/Technology• Repetition


Fundamental Concepts Fundamental Concepts (2)(2)

Appropriate Manufacturing PhilosophyAppropriate Manufacturing Philosophy– Concept of Quality– Likely Competitor Actions– Management Philosophy/Style

• Centralized/Decentralized

– Infrastructure• Core Competencies• Information Systems• Worker Skills, Unionization

– Capital Recovery Requirements– Risk/Reward Tradeoff


Basic Framework for Basic Framework for Manufacturing Planning Manufacturing Planning

and Control Systemsand Control Systems• ObjectivesObjectives

– Right Products, at the– Right Time, in the– Right Quantities, at the– Right Quality, at the– Right (Minimum) Cost

• Achieved in an Integrated, Achieved in an Integrated, Rationalized SystemRationalized System


Sources of Variation in Sources of Variation in Manufacturing Systems Manufacturing Systems

--• Timing of Demand ReceiptTiming of Demand Receipt

– Make to Order– Make to Stock

• QuantityQuantity– Reductions/Additions

• Available Production ResourcesAvailable Production Resources– Breakdowns– Supplier Deliveries– Errors in Estimates


Strategies for Dealing Strategies for Dealing with Variationwith Variation

• IdentifyIdentify

• EliminateEliminate

• ReduceReduce

• Acknowledge/React/ModifyAcknowledge/React/Modify


Basic Activities in Basic Activities in Planning and Control Planning and Control

SystemsSystems• Determination of Product Design(s)Determination of Product Design(s)• Determination of Amount to ProduceDetermination of Amount to Produce• Balancing Demand for Resources (Time)Balancing Demand for Resources (Time)• Determination of Operation ParametersDetermination of Operation Parameters• Detailed Planning/SequencingDetailed Planning/Sequencing• Dealing with Variation During Lead Dealing with Variation During Lead

TimeTime• Production and Delivery of ProductProduction and Delivery of Product


Variation and Basic Variation and Basic Mfg. And Control Mfg. And Control

ActivitiesActivities• Product Design VariationProduct Design Variation

– Pre-release– Post Release

• Demand VariationDemand Variation• Resource Availability Resource Availability

– Breakdown– Diversion

• Model vs. Reality Model vs. Reality – Actual vs. Estimated


Product Design Product Design Variation Variation (1)(1)• Sources of VariationSources of Variation

– Overly Diversified Product Line• Main Products• Options within Main Products

– Different Solutions for Same Functionality, Components• Different Designs• Different Suppliers

– Different Processes for Same Part Features• Different Production Processes• Different Routing (Same Processes)


Product Design Product Design Variation Variation (2)(2)

• Strategies to Eliminate/Reduce Strategies to Eliminate/Reduce VariationVariation– Overly Diversified Line

• Determine “Core” Products• Determine “Core”/”Standard” Features• Divestiture

– Differing Solutions for Same Function, Component• Group Technology• Concurrent Engineering• Long Term Relations with Suppliers• Bring Production In-House


Product Design Product Design Variation Variation (3)(3)

• Strategies to React to VariationStrategies to React to Variation– Overly Diversified Line

• Reevaluate Product Line• Focused Factories Concept

– Differing Solutions for Same Function, Component• Agile Manufacturing• Group Technology• Concurrent Engineering• Long Term Relations with Suppliers• Bring Production In-House


Demand VariationDemand Variation• SourcesSources

– Inherent Variation in Demand Pattern• Randomness in Customer Behavior• Incomplete Forecasting Model

– Historical Data Missing or Unavailable

• Inability to Monitor/Predict Underlying Factors– E.g., Weather, Government Action, …

– Changes in Factors Affecting Demand • Individual Customers• Market Conditions (General Economy)• Competitive Environment (Competitor Actions)


Forecasting of Demand Forecasting of Demand Pattern and LevelPattern and Level

• Methods of ForecastingMethods of Forecasting– Historical Data

• Averaging Methods• Exponential Smoothing• Time Series

– Causal Factors• Correlated Products

– Leading Indicators– Source Products– Changes in Competing Products

» Predict and Monitor Competitors, Total Market


Existing/New Product Existing/New Product ForecastingForecasting

• Forecasting - Historical DataForecasting - Historical Data– Best Fit (Curve Fitting, Least Squares)– Regression (Factors)– Reaction and Damping

• Forecasting - New ProductsForecasting - New Products– Market Surveys

• Size of Market• Degree of Penetration

– “Best Guess”


Eliminating/Reducing Eliminating/Reducing Demand VariationDemand Variation

• In Demand Pattern and LevelIn Demand Pattern and Level– Add Complementary Products To Line

• Seasonality• Economic Conditions

– Aggregate Planning– Coordinate Marketing and Manufacturing

• Concurrent Efforts (Manufacture and Marketing)

• In Forecast of DemandIn Forecast of Demand– Use Multiple Models to Reduce Risk

• Historical• Correlated Products


Reacting to Demand Reacting to Demand Variation (1)Variation (1)

• Frequent Recalculation/Reevaluation Frequent Recalculation/Reevaluation • Reduce Risk/UncertaintyReduce Risk/Uncertainty

– Convert Basis of Planning from Prediction to Actual• Customer Relationships (information Sharing)• Incentives for Orders (Pricing)

– Reevaluate Closer to Delivery Date• Shorten Administrative Lead Time• Shorten Production Lead Time

• Shift Problem to SuppliersShift Problem to Suppliers– Add/Reduce Sub-Contracting as Needed



• Eliminate/Reduce Forecast ErrorEliminate/Reduce Forecast Error– Use Strategies for Demand Pattern

Variance Reduction– Improve Forecasting

Models/Methodology

• Forecasting Errors are InevitableForecasting Errors are Inevitable– Accept It– Plan Using Range Rather than Point

Estimates



• Aggregate PlanningAggregate Planning– Earlier, Distributed Production– Varying Delivery Schedules– Varying Pricing/Marketing Strategies

• Varying Capacity Varying Capacity – Labor (Hire/Fire/Subcontract)– Capital Equipment (Sub-Contract,

Make/Buy)

• Maintain InventoriesMaintain Inventories• Maintain Surge CapacityMaintain Surge Capacity



Lecture 9 Topic:Lecture 9 Topic: Manufacturing Manufacturing Planning and ControlPlanning and Control

Segment A Topic:Segment A Topic: Planning Concepts Planning Concepts

END OF SEGMENTEND OF SEGMENT




Segment B Topic:Segment B Topic: Aggregate Aggregate Planning and Progress ControlPlanning and Progress Control


ADVANCED ADVANCED MANUFACTURING MANUFACTURING SYSTEMS DESIGNSYSTEMS DESIGN

Manufacturing Manufacturing Planning and Control Planning and Control

Aggregate Planning and Aggregate Planning and Progress ControlProgress Control


OverviewOverview

• Aggregate PlanningAggregate Planning– Definition and Philosophy– Quantitative Analysis

• Progress ControlProgress Control– Concept– Methods

• MRP• JIT


Aggregate Planning (1)Aggregate Planning (1)

• Definition - Production Planning Definition - Production Planning using Aggregated Informationusing Aggregated Information– Define General Approach – Feasibility Sought

• PhilosophyPhilosophy– Aggregated Data Displays Less

Variation than Individual Data Patterns– Reduce Size/Complexity of Problem

• Decide to React Rather than Predict/Dictate


Aggregate Planning (2)Aggregate Planning (2)

Aggregation ProceduresAggregation Procedures– Determine Common Unit of Measure

• Usually Labor and/or Machine Hours• Assumes Complete Substitutability of

Resources• Balance Capacity (of Unit of Measure vs.

Need)• “First Cut” Procedure to Determine

Production Strategy• May or May Not Include Flow Time Analysis


Aggregate Planning: Aggregate Planning: An LP ApproachAn LP Approach

• Linear Programming ApproachLinear Programming Approach– Determine Aggregation Attribute– Estimate Constraints, Resources

• Estimate Product Requirements/Timing• Estimate Each Product’s Resource

Requirements• Define Availability of Resources

– In-House, SubContract, Breakdowns

• Set Operating Philosophy– Backorders Allowed (0 – X %)– Overtime/Contracting Allowed


Examples of Examples of ParametersParameters• CapacityCapacity

– Available Hours on Production Centers less Non-Working, less Set-Up, less Scrap Production, Less Breakdowns @ Productivity Level

– Available Hours Determined by Management (2nd, 3rd Shifts, OT, etc.)

– Subcontracting Available

• Resource RequirementsResource Requirements– Labor/Machine Hours per Unit of

Output via BOM, Lead Times– % Scrap, % Set-up Time (Batch Sizing)


LP FormulationLP Formulation• Objective EquationObjective Equation

– Minimize Cost• Production (Hire/Fire/Overtime/Subcontract)• Inventory/Backorder Costs (Timing)

– Subject To (Constraints)• Not Exceed Available Capacity

– Machine Routings Often Ignored/Lost in the Aggregation (Labor Hours Used)

– Can Do by Machine/Process Type (Assumes Detailed Sequence will be Manageable

• All Demand Met (Feasible Solution Exists)


Dynamic Programming Dynamic Programming FormulationFormulation

• Wagner-Whitin Algorithm (1960)Wagner-Whitin Algorithm (1960)– Used for Batch Production

• High Set-up Costs• Demand NOT Uniform over Year

– Each Period Evaluated • Should Product be Made this Period (I.e.,

Should a set-up cost be Incurred?)• Balances Inventory Carrying Cost and Set-up

Cost• Once Optimal Sequence Established It is

Independent of Later Demand

– Basis of MRP Concept


Aggregate Planning Aggregate Planning ProcessProcess

• DrawbacksDrawbacks– Often only One Scenario Considered– All Products Have Same

Backorder/Warehousing Costs, Opportunities

– Little Sensitivity Analysis Performed• Range of Demand

• AdvantagesAdvantages– Simple– Errors Often Offset


Aggregate Planning - Aggregate Planning - DrawbacksDrawbacks

Problems with LP ApproachProblems with LP Approach– Illusion of Precision

• Precision Function of Estimates/Aggregation

– Definition of Period (Length)– Flow Times/Batch Transition– Resource Constraints

• Assumed May Not be Actual Constraint

– Abstraction of Reality


Detailed Manufacturing Detailed Manufacturing Release/Progress Release/Progress

ControlControl• Disaggregation of Aggregate Plan Disaggregation of Aggregate Plan

– Controls What Made and When– Provides Guidance to Operating

Personel

• OptionsOptions– Individual Products, Families (GT)– Pre-Planned (Push) – MRP– Dynamic, Real Time (Pull)

• Job Sequencing (Johnson’s Rule, Heuristics)• JIT


Manufacturing Release/ Manufacturing Release/ Progress Control Progress Control

ProblemsProblems• Aggregate Plan is Never AchievableAggregate Plan is Never Achievable

– Actual Demand Differing from Prediction– Missed Delivery Dates (External)

• Suppliers• Wrong Parts, Poor Quality

– Missed Delivery Dates (Internal)• Breakdowns (Labor or Equipment)• Scrap• Priority Order Disruption• Bad Estimates of Production Time• Lack of Sufficient Skills


Detailed Manufacturing Detailed Manufacturing PlanningPlanning

• Strategies to Deal with/ Strategies to Deal with/ Eliminate/Reduce VariationEliminate/Reduce Variation– Reduce Inherent Demand, Forecasting

Variation– More Accurate Resource Requirements– Accept Reasonable Variation (Range)– Ignore in Planning, Empower Floor


Variation During Variation During ProductionProduction• Strategies to Eliminate/Reduce Strategies to Eliminate/Reduce

VariationVariation– Decoupling Line Using Buffer

Inventories– Preventive Maintenance– Improved Supplier Relationships– Penalty Clauses for Missed Delivery– Minimize Priority Interrupts

• Strategies for “Handling” VariationStrategies for “Handling” Variation– Excess or Expand Capacity (OT)– Material, Component Inventories– Shop Floor Control Systems


Variation in Delivery of Variation in Delivery of ProductProduct

• Sources of VariationSources of Variation– Delivery Mechanism/Reliability– Errors in Routing/Addressing– Wait to Aggregate into Unit

Load/Shipment

• Strategies to Eliminate/Reduce Strategies to Eliminate/Reduce VariationVariation– Quote FOB at Your Site– Bring Delivery In-House– Use More Reliable Transporter/Deliverer




Segment B Topic:Segment B Topic: Aggregate Aggregate Planning and ControlPlanning and Control

END OF SEGMENTEND OF SEGMENT




Segment C Topic:Segment C Topic: Release and Release and Progress ControlProgress Control


OverviewOverview

• Releasing and Progress ControlReleasing and Progress Control

• Manufacturing Requirements Manufacturing Requirements PlanningPlanning

• Just in TimeJust in Time

• Toyota Production SystemToyota Production System


Releasing MethodsReleasing Methods

• Machine/Cell Scheduling Rules vs. Machine/Cell Scheduling Rules vs. MRP vs. JIT vs. Varying Production MRP vs. JIT vs. Varying Production HoursHours– Function of Type of Production

System/Products• Job Shop => Machine/Cell (Job) Scheduling• Batch => MRP or JIT

– Function of Demand Variation

• Mass Production => Few scheduling Decisions– Vary Hours Facility Works– Rebalance Facility, Output Rate


Release/Progress Release/Progress ControlControl• MRPMRP

– Centralized– Automated (Computerized)– Adjusted at Fixed Points in Time

(Recalculated)– Key = Time Phased Plan

• JITJIT– Decentralized– Manual (Kanbans)– No Pre-calculation of Release

Times/Dates– Key = Constant Demand, Kanban

Size/Number


Material Requirements Material Requirements Planning (1)Planning (1)

• Determine Planning PeriodDetermine Planning Period• Determine/Estimate Demand Per PeriodDetermine/Estimate Demand Per Period• Establish Bill of Materials (Gozinto)Establish Bill of Materials (Gozinto)• Determine “Critical Path”Determine “Critical Path”

1 2 3 4 5 6 7 8 9 10

LEAD TIME


Material Requirements Material Requirements Planning (2) Planning (2)

1 2 3 4 5 6 7 8 9 10

1

2

3

5

4 6

7

8

9 10

11


Material Requirements Material Requirements Planning (3)Planning (3)

1 2 3 4 5 6 7 8 9 10

PRODUCT TO BE MADEAND DELIVERED AFTERPERIOD 10

PRODUCT MADEBEFORE WEEK 10


Just In Time (1)Just In Time (1)

• Use Parts as NeededUse Parts as Needed• When Kanban Empty, Send UpstreamWhen Kanban Empty, Send Upstream• When Empty Kanban Received, FillWhen Empty Kanban Received, Fill


Just In Time (2)Just In Time (2)

• Key CalculationsKey Calculations– Number of Kanbans– Size of Kanbans

• Key ParametersKey Parameters– Set Up Time (Short or Use Signal Kanbans)– Receipt Time (Short or Use Signal Kanban)

• Determine Using Linear ProgrammingDetermine Using Linear Programming


Analysis of Releasing Analysis of Releasing and Progress Controland Progress Control

• Push/Pull -- MRP vs. JITPush/Pull -- MRP vs. JIT– Determining Factors

• Mixed Model Production System• Period to Period Stability of Demand

– Low => JIT– Higher => MRP

• Set-Up/Changeover Requirements, Lot Sizing– Low => JIT– Higher => MRP w.Wagner-Whitin

– Determine Sequencing• Sequence Dependant Time/Cost


AcknowledgementAcknowledgement

• The illustrations on the following The illustrations on the following seven (7) slides are taken from seven (7) slides are taken from Singh, Singh, Systems Approach to Systems Approach to Computer Integrated Design and Computer Integrated Design and ManufacturingManufacturing, John Wiley and , John Wiley and Sons, New York, New York, c1996. Sons, New York, New York, c1996. Pages 507, 511-4.Pages 507, 511-4.


An Integrated GT and An Integrated GT and MRP FrameworkMRP Framework

• Ham, et alHam, et al


GT - MRP Example (1)GT - MRP Example (1)Minimize CostMinimize Cost

Minimize Production TimeMinimize Production Time

Balance WorkloadsBalance Workloads


GT - MRP Example (2)GT - MRP Example (2)


Toyota Production Toyota Production SystemSystem

• PhilosophyPhilosophy– Eliminate

• MUDA (Waste)– Defects, Overproduction, Unneeded

Processing, Unneeded Conveyance, Excess Inventory, Unneeded Motions, Delays

• MURA (Uneveness)– Unbalanced Lines (Bottlenecks), Variation

• MURI (Overburdening of Resources)– Provide Surge/Excess Capacity



Lecture 6 Topic:Lecture 6 Topic: Manufacturing Manufacturing Planning and ControlPlanning and Control

Discussion Topic C:Discussion Topic C: Release and Release and Progress ControlProgress Control

END OF SEGMENT END OF SEGMENT

advanced manufacturing systems design © 2000 john w. nazemetz lecture 9 topic : manufacturing...

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