Presentation on theme: "Inventory, Distribution and Value-Added Activities Analysis Dr. Gerald Evans Dr. Gail DePuy Dr. John Usher Maria Chiodi University of Louisville."— Presentation transcript:
Inventory, Distribution and Value-Added Activities Analysis Dr. Gerald Evans Dr. Gail DePuy Dr. John Usher Maria Chiodi University of Louisville
System Under Study The N. Glantz and Sons Distribution System for signage supplies, consisting of Vendors, one Distribution Center (located in Louisville), and 19 Branch Offices (located throughout the US). Approximately 5000 SKUs. (s,S) inventory policy in use at each branch and at the DC. Regular shipping schedule for shipments from the DC to the branches.
Primary Questions Being Addressed Should the DC be enlarged? Should the Branch Offices order stock through the DC, or directly from the vendor (for specific SKUs)? Are value-added operations at the DC economically viable?
Secondary Questions Being Addressed Should another DC be constructed (e.g., on the West Coast)? What should the reorder points and reorder quantities be (at each branch and at the DC) for each SKU? Is there a better shipping schedule?; if so, what would it be? How would changes in demand patterns at the branches affect the optimal values for the control variables?
Research Methodologies Because of the complex relationships (nonlinear, not of a closed-form) between the control variables and the performance measures of the system, and because of the “time-dynamic” behavior of the system, simulation model(s) are being constructed to represent the system operation. In addition, an Excel spreadsheet model, is being developed to allow a static analysis addressing one of the major questions: should the branches order directly from the DC or from the vendors? The spreadsheet model will also aid in the verification of the simulation model.
Arena Simulation Model(s) The Arena (Version 8) simulation software package is being used to construct a prototypical simulation model; this model will represent the movement of one SKU from one vendor through the system. Following verification and validation of the prototypical model, additional data (for additional part types and vendors) will be utilized to construct a full-scale simulation model of the Glantz Distribution System.
Prototypical Simulation Model: Submodels Submodels incorporated within the prototypical model are used to represent the following processes as parts of the overall system operation: – Customer orders at Branches. – Branch orders to the DC. – Branch orders to Vendor. – DC orders to Vendor. – Vendor shipments to DC. – Vendor shipments to Branches. – DC shipments to Branches. – Time advancement (keeping track of Day of Week and Day of Simulation).
Prototypical Simulation Model: Input Parameters (which stay constant through the simulation run) Number of Branches. Customer demands at Branches. Shipping costs (Vendor to DC, Vendor to Branches, DC to Branches). Transit times (Vendor to Branches, Vendor to DC). Shipping Schedule (DC to Branches). Inventory Carrying Charges (at DC and at Branches). SKU characteristics (purchase price (nonlinear relationship allowed), selling price, volume (used to determine capacity requirements)). Lost sales cost per unit. Fixed ordering cost.
Prototypical Simulation Model: Input Control Variables (which stay constant through the simulation run) Reorder points and reorder levels at each Branch and at the DC. Fraction of orders made by the Branch to the DC (as opposed to the vendor) for each Branch. Shipping Schedule (from DC to Branches).
Prototypical Simulation Model: Outputs (which require initial values, but which vary through the simulation run) Day of Week and Day of Simulation. Indicator variables for Branches and DC to represent whether or not there is an outstanding order for the respective Branch or DC. Inventory Levels, Inventory Volumes (capacity used), and Value of Inventory at each Branch, at the DC, and in-transit from the DC to any of the Branches. Number of times that an order requested by a Branch cannot be supplied by the DC because of insufficient inventory level. Accumulated Sales Dollars at each Branch. Accumulated Lost Sales Cost at each Branch. Accumulated Transportation Costs for shipments to each Branch categorized by shipments from the DC to that Branch and by shipments from the Vendor to that Branch. Accumulated Transportation Costs for shipments from the Vendor to the DC. Accumulated Fixed Ordering Costs for each Branch and for the DC. Accumulated Purchased Parts Cost for each Branch and for the DC. Inventory Carrying Charges for each Branch, for the DC, and in transit from the DC to one of the Branches.
Prototypical Simulation Model: Main Performance Measures Output Net System Profit = Sales Dollars for All Branches - Total Lost Sales Cost over All Branches – Total Ordering Cost - Total Shipping Cost - Total Purchased Parts Cost - System Inventory Carrying Charges. Maximum Capacity required for inventory storage at each Branch and at the DC.
Work Item JASONDJFMAMJJ Part A: DC sizing analysis Project kick off X Initial data gathering (Target vendors/skus) XXX Literature Review XXX Develop simulation model XX Load with single SKU XXX Debug - Verify output XX Upgrade model - Load target vendors/skus XXX Run initial analysis XX Parallel spreadsheet analysis XXX Preliminary conclusions - DC XX Review preliminary results with client X
Revise/upgrade model as required XXX Continue data gathering XXXXX Load selected additional vendor/sku data XX Process additional data - XXX Draw conclusions - DC XX Review findings with client X Part B. Analyze Value Added opportunities XXXX Preliminary conclusions – VA X Review findings with client XX Wrap - Up Recycle/ re-run as required XX Final Report Preparation XX Final Report-Out to Client X