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Supply Chain Model


Supply Chain Model An Overview Supply Chain Fundamentals Material flows Supply of raw material: Lead Times, storage.. Production: scheduling, batch and continuous ... – PowerPoint PPT presentation

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Title: Supply Chain Model

Supply Chain Model
  • An Overview

Supply Chain Fundamentals
Typically a Supply Chain consists of
  • Material flows
  • Supply of raw material Lead Times, storage..
  • Production scheduling, batch and continuous
    processes, changeover time, batch
  • Warehousing dispatch, replenishment, stock
  • Market customer service level and expectations,
    storage, On Time In Full (OTIF)
  • Transportation simple or complex?, travel times,
    variability, small, big orders
  • Third Parties Outsourcing or Third Party Supply
    may be a factor at any stage
  • Information flows
  • Forecasts customer demand, Supply Chain
    forecasting, manual, automatic
  • Actual orders Order size and frequency profiles,
  • Processing Automated or manual, ERP?,
    Information sharing, emergency orders

Supply Chain Fundamentals
Result Customer Service Level Agreements (SLAs)
are necessary
Service Levels and metrics
Supply Chain Fundamentals
Why the difference between perfect and real
Supply Chain? Uncertainty
  • Market Demand
  • Consumer or customer demand may be variable
  • More importantly demand patterns may be difficult
    to predict
  • Demand is often forecasted poorly. Automated
    systems with manual interference are typical
  • Market demand forecasts, Supply Chain forecasts
    and factory forecasts are calculated in isolation
    from each other, leading to duplication of effort
    and to the amplification of errors
  • Production
  • Often production efficiency is at the expense of
    overall Supply Chain goals
  • Production batch sizes may be larger than
  • Long forecasting horizon may allow production
    scheduling to be optimised but lengthens lead
  • Various unknowns combine so that production
    schedule adherence is not 100
  • Warehousing
  • Information about existing stock is not shared
    adequately through the system
  • Safety stock calculation is likely to be less
    than optimal
  • A replenishment policy which works is likely to
    be in operation rather than one that is best
  • Other
  • Steady predictable demand is handled similarly to
    volatile demand in the Supply Chain
  • Transportation may be unreliable or unpredictable
  • Raw material supply may be unreliable or
  • Arrangements with Third Parties may reduce
    visibility and information sharing

Supply Chain Fundamentals
Why the difference between perfect and real
Supply Chain? Uncertainty
Uncertainty, Variability
What can Simulation do?
Discrete Event Simulation is an approach aimed
precisely at accounting for uncertainty
  • Mocsims Supply Chain Model was built using using
    Extend simulation software with an interface
    created in Microsoft Excel
  • Note Similar logic could be coded into any
    other DE package. The choice of simulation
    software is not key. The advantages of Extend
    are that it
  • has Runkit and Player versions and so models can
    easily be ported and share amongst users
  • is fast
  • is object oriented which allows for easy
    configuration of different Supply Chain networks
    once the core modules have been designed
  • has adequate animation
  • Links easily with spreadsheets

Supply Chain Model output
Results can be formatted to suit client
conventions or for easy translation into value
  • For each Product Type, SKU the following output
    information is available instantaneously and
    against time
  • Stock quantities at each location
  • Service level measures such as OTIF for each
    stage of the Supply Chain or overall
  • Lead Times and Lead Time variance for each stage
    of the Supply Chain or overall
  • Production metrics
  • Orders in transit
  • All output can be converted to units of Orders,
    Quantity or Value
  • Output can be viewed dynamically for training or
    demonstration purposes or analysed when runs are

Supply Chain Model dynamic interface
Case Study
Client applied Supply Chain Simulator to
  • Prototype and design an alternative Supply Chain
  • Train the Supply Chain organisation
  • Demonstrate and sell advantages of the proposed
    Supply Chain structure across the business

Project Stages were
  • Configuration of the model to match existing
    Supply Chain conditions and proposed alternative
  • Collection, analysis and processing of historical
  • Tuning the model to match As-Is conditions
  • Design of simulation scenarios
  • Completion of simulation runs and compilation of
  • Run training courses based on the scenarios tested

Case Study detail
Sample of scenarios tested
  • All variability/uncertainty parameters switched
    off to demonstrate the perfect-world Supply
  • Lead Times are a minimal (equal to production or
    transport times only)
  • Service levels (On Time In Full - OTIF) are 100
    at each Supply/Demand stage
  • Introduce demand variability (order frequency,
    order size, then both)
  • Then adjust safety stock levels to increase OTIF
  • Repeat runs until OTIF is at acceptable levels
  • Repeat the previous experiment for different
    types of uncertainty and variability
  • Forecast accuracy
  • Production schedule adherence
  • Supply Chain accuracy
  • Carry out runs to show the effect of increasing
    agreed Lead Times relative to the average
    possible throughput times
  • In this case a build-up of stock occurs because
    orders often arrive earlier than expected. This
    stock would have to be either acceptable to the
    and customer or held until a suitable delivery
    point by the supplier.
  • Show impact of changes to Supply Chain production
    batch size
  • Bigger batch size improves production efficiency
    but means increased stock must be held downstream
    in the Supply Chain
  • In this case it was possible to reduce the
    negative impact of small batch sizes on factories
    be designing an optimum production sequence which
    minimised changeover times.

Case Study detail
Planned scenarios include
  • Carry out runs to show the impact of changing the
    length of
  • Review period (for each warehouse a review period
    can be set. This makes warehouse management
    simpler but effectively increases Lead Time)
  • Scheduling horizon (Increasing this makes
    production scheduling easier but increases Lead
  • Customer types split into segments with different
    Customer Service Levels
  • Model would help to quantify the benefits of
    splitting customers in different ways for example
    it might be rational to separate stable
    predictable demand from more unpredictable.
  • Show the benefits of increased visibility and
    information sharing
  • The model was configured to account for three
    strategies Make to Stock, Make to Order and
    Vendor Managed Inventory