Support Chain Optimisation

Course

Inhouse

Price on request

Description

  • Type

    Course

  • Methodology

    Inhouse

  • Duration

    4 Days

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Course programme

Day 1

Session 1. Nature of consumables.

  • The nature of consumables (as distinct from repairables).

Session 2. EOQs and Lot Sizes.

  • Optimum Stock levels, Re-order Points & Quantities.

Session 3. Demand forecasting

  • Moving Averages and Exponential Smoothing.

Session 4. Demand forecasting (Continued)

  • Compound Exponential Smoothing.
  • Triple Exponential Smoothing / Seasonal Forecasting

Day 2

Session 5. Identification of the System-based demand drivers

  • The aim of lecture one is to identify and define the specific system parameters (drivers) of demand which are relevant to inventory management planners and forecasters, to explain why (and how) they are relevant in stock control and to examine the relationships between these elements and their significance.

Session 6. Inventory Management Operational and Maintenance Factors

  • Having defined the characteristics of a system, placed these data in context and understood which parameters drive significant changes to support policies and organizations (and why), system operators (who have little influence on a system's hardware design) must understand the effect and nature of Operational and Maintenance Factors on Inventory Management and the support chain (which Operators do have influence over).

Session 7. Key Stock Control Measures of Effectiveness (MOE)

  • Having identified all the key drivers, Inventory management planners must measure the effectiveness of their supply chain in order to optimize stock control. Frequently used MOEs include:
    • Service Levels, Demand Satisfaction/Fill Rate/OSSR.
    • Dispatch reliability Availability (achieved, operational, inherent).
    • Sustainability.
    • Waiting Times.
    • AOGs/No Gos/NORS/"D" States/Expected Back Orders.
    • Cost of Shortage.

Day 3

Session 8. Introduction to Statistics and Probability Theory

  • The concept of fluctuation in demand is discussed showing the limitation of many techniques to accommodate variability in supply, demand and repair rates. Planners must accommodate this variability if they are to forecast accurately (and thus optimize) Supply Chains and Repair Processes. Probability theory and statistical processes relevant to planners are introduced and developed sufficiently to provide Support Chain Analysts with an understanding of both the power and limitation of applying probability to variability.

Note: Although this Session is the longest single phase of the seminar it is broken into straightforward manageable steps. It includes enough material for attendees with even basic numeracy to become sufficiently familiar with the terms and techniques to enable them to use, with confidence, statistical techniques and probability theory

Session 9. Mathematical Techniques and Solutions

  • This Session describes and explains the most commonly applied mathematical techniques for Demand analysis and forecasting, Optimal stock control and Inventory management. Examples of each technique and its application are provided and the positive and negative attributes of each approach are discussed. It is usually during this session that attendees understand for the first time the strengths and weaknesses the processes currently in use at their organization and the benefits or risks that could be realized by adopting a different (or supplementary) technique.

Day 4

Session 10. Practical Application of Techniques

  • Having achieved an understanding of statistical and probability processes, their application and how and why software tools are developed, current applications are discussed and practical examples and demonstrations of various COTS products are given.

Session 11. Other Computer-based Support Chain Analysis Processes

  • An examination of other models and methods available to Supply Chain planners is undertaken. A description of techniques, with examples and applications, is provided including the relative merits and demerits of each. Parametric Analysis, Expert systems, Artificial Intelligence
  • Guided Search paradigms (Genetic Algorithms, Simulated annealing and random mutation hill climbing) are all explained.

Session 12. Data Sources and Issues

  • Having examined the above aspects relevant to planners, the importance of data will now be apparent. To conclude, this stock control training course, an examination is conducted of the various data sources (and issues to be resolved) if Support Chain Analysis is to be successfully undertaken.

Support Chain Optimisation

Price on request