Fluent Essays

This week were going to work individually on a simulator/software for designing supply chains and managing them with a digital twin. It integrates supply chain design, optimization, and simulation with operations data enabling network analysis and improvement.There are 4 videos to watch as you go through the assignment document.Be sure to submit your work on the Student Submission file. The book, ivanov-supply chain simulation has been included but is not needed for this assignment. Its really there for reference should you choose to peruse it. anylogistics_student_submission_file.docx anylogistix_assignment_rev1.pdf anylogistix_data.xlsx ivanov_supply_chain_simulation_and_optimization_with_alx.pdf Unformatted Attachment Preview Part 1: Greenfield Analysis Screen Capture 1: DC’s and Customers To receive credit, the scenario and results MUST include your name and initials. The file must also include the map inclusive of your customers and DCs. Part 2: Network Optimization Screen Capture 2: Customer Groups To receive credit, the scenario and results MUST follow the naming convention outlined in the assignment guidelines. Screen Capture 3: Product Flows Take a screen capture of the sources included in the Flow table. To receive credit, the naming convention of the supplier must be followed. Screen Capture 4: Profitability (Operating Loss) Take a screen capture of the profit (Operating Loss). The screen capture MUST include the scenario name inclusive of “YOUR NAME” Screen Capture 5: Profitability Take 2 Take a screen capture of the profit. The screen capture MUST include the scenario name inclusive of “YOUR NAME” Screen Capture 6: Profitability Take 3 Take a screen capture of the profit. The screen capture MUST include the scenario name inclusive of “YOUR NAME” Part 3: Simulation Screen Capture 7: Dashboard; Annual Performance • After running the simulation for a complete year, take a screen capture of the dashboard. The screen capture MUST include the scenario name inclusive of “YOUR NAME” Screen Capture 8: Dashboard; Annual Performance (Take 2) • After altering parameters and rerunning the simulation for a complete year, take a screen capture of the dashboard. The screen capture MUST include the scenario name inclusive of “YOUR NAME” Part 4: Independent Simulation and Summary Screen Capture 9: Dashboard; Annual Performance (Independent Simulation) • After altering parameters and rerunning the simulation for a complete year, take a screen capture of the dashboard and place the results here. The screen capture MUST include the scenario name inclusive of “YOUR NAME”. Additionally, your reflection (a few paragraphs) should be included. AnyLogistix Assignment(s) AnyLogistix™ (ALX™) is software for designing supply chains and managing them with a digital twin. It integrates supply chain design, optimization, and simulation with operations data enabling network analysis and improvement. Prior to completing the four assignments outlined below, you must download a free version of the Personal Learning Edition of the software using the link below: https://www.anylogistix.com/personal-learning-edition/ NOTE: ALX is Java based and has been tested on the following platforms: Microsoft Windows 10 x64, Microsoft Windows 8 x64, Microsoft Windows 7 SP1 x64. Full System Requirements are accessible via the link included above. Part 1: Greenfield Analysis (GFA) A Greenfield Analysis is used to find optimal number of distribution centers as well as for defining the approximate locations for the supply chain sites taking into account the following data: Locations of the customers/sites, list of products, aggregated demand for each customer and product, and direct distance between customers and DCs/Warehouses or number of facilities we need to find. (Source: https://www.anylogistix.com/help/index.jsp?topic=\%2Fcom.anylogic.anyLogistix.help\%2Fhtml\%2Fexperiments\%2FGFA.html) Part 1 is associated with Video 1 through the 12 minute mark (accessible via Canvas). Once ALX is downloaded on your machine, launch the application to perform the following functions: • Create New Scenario o Click New Scenario o Select Scenario Type: GFA o Rename the Scenario NOTE: Your name must be included in the scenario (see below) o Click OK 1 • Add customers o Add customer via GIS map ▪ Click the Create Customer icon (blue icon) o o ▪ Double-click on Washington, DC on the map (re-center and zoom in on the map) ▪ In the Customer table, rename the customer “Washington, DC” Download the AnyLogistix Data.xlsx file to your machine to facilitate the import below Add customers via the Import function ▪ Click Import Scenario ▪ ▪ Select: • Select the AnyLogistix Data.xlsx file from your machine • Open Advanced options • Sheets to import: Customers, Demand, Locations • Create new scenario: off • Scenario name: Choose your scenario • Import experiments: no Click OK NOTE: If you receive a warning message, simply click “OK” 2 • Modify product – a product is in the scenario by default. You will customize accordingly. o Navigate to the Products table o Double-click the Name of the existing product and change it to “PS4” o Double-click the Unit and select “pcs” • Add demand o Demand was automatically populated via the import. To confirm, perform the following steps: ▪ Navigate to the Demand table ▪ Double-click the Parameters for Washington, DC o ▪ View the current settings and click OK Define the Product ▪ Press Ctrl and click the Product column title ▪ ▪ Press the spacebar OR (Note: this may vary on your PC) Select PS4 from the drop down menu ▪ Click OK 3 • Configure and run the GFA experiment o Click on the name of your experiment under GFA, then click on GFA experiment o Enter: ▪ Number of sites: 4 ▪ Product measurement unit: pcs o Click the Run icon (red triangle) o Click the Filter icon (funnel) and then click Show Connections (four connected squares) to see which distribution center is serving which customers. o Repeat the previous steps with 3 sites, and rerun the experiment. o To hold on to settings, rename the results. ▪ Right-click the word Results and change the name of the experiment to “Your Initials_4DCs” ▪ Right-click the word Results 2 and change the name of the experiment to “Your Initials_3DCs” Right-click the name 3DCs and click Convert to GFA scenario. Repeat this step for the 4DCs experiment Screen Capture 1: Take a screen capture of your results and place in the separate results file. Rename AnyLogistics_Name. Note: To receive credit, the scenario and results MUST include your name and initials. The file must also include the map inclusive of your customers and DCs. o o 4 i.e. SamJones_GreenfieldAnalysis i.e. SJ_4DCs and SJ_3DCs 5 Part 2: Network Optimization (NO) Network optimization experiment is used to provide the most optimal locations for distribution or production facilities, product flows, and sourcing options. The optimal solution is the best set of flows and facilities considering a profit maximizing objective and adherence to all constraints (i.e. Production). The experiment considers the following data: Demand; Location of suppliers, customers, existing and potential facilities, and paths between the supply chain elements; Product flows; Product storages; DC fixed/variable costs, and transportation costs; and Time periods. (Source: https://www.anylogistix.com/help/index.jsp?topic=\%2Fcom.anylogic.anyLogistix.help\%2Fhtml\%2Fexperiments\%2FGFA.html ) Part 2 is associated with Video 1 (12 through end) and Video 2 (accessible via Canvas). Part 2 is dependent on Part 1. To complete Part 2 perform the following steps: • • Right-click the 3DCs scenario name and select Create Copy as NO Investigate the GFA DC locations o Click on GFA DC and zoom in o Select a more appropriate DC location (based on roads, expected costs, etc.) and move the DC location. Refer to the end of Video 1 and beginning of Video 2. Rename the DC based on the location. Ensure your Initials are included (see below): o Repeat this step for GFA DC 2 & 3 • Rename Groups o Navigate to the Groups table o Rename each of the groups as follows: ▪ GFA_Your Initials_DC#_City Name_ Customers (e.g. GFA_SJ_ DC1_ Bayonne_Customers) o Screen Capture 2: Take a screen capture of your results and place in the separate results file. Note: To receive credit, the naming convention above must be followed. 6 • Add a supplier o In the map, navigate to the Port of Los Angeles o Click the create a supplier icon (green circle) o Double-click the port to add a supplier o Navigate to the Suppliers table and rename the supplier Your Initials_Port of LA o o Navigate to the Product Flows table Click Add, o o o In the Source column, select YourInitials_Port of LA In the Destination column, select All sites In the product column, select PS4 Screen Capture 3: Take a screen capture of the sources included in the Product Flows table and place in the separate results file. Note: To receive credit, the naming convention of the supplier must be followed. 7 • Modify the cost calculation o Navigate to the Paths table o Double-Click the first cell in the “From” column and change it to “All locations”. The “To” cell should also be “All locations” o • Double-click the Cost Calculation Parameters cell. Change the Amount unit to pcs and change the Cost per unit to 0.002 Test run the experiment o Click NO experiment o Change the Product statistics unit to pcs o Click the run icon (red triangle) o The profit result will be a loss Screen Capture 4: Take a screen capture of the profit and place in the separate results file. The screen capture MUST include the scenario name inclusive of “YOUR NAME” 8 • Specify the product cost and price o Navigate to the Products table and specify 399 for Revenue and 381 for Cost • Re-run the experiment Screen Capture 5: Profitability Take 2 Take a screen capture of the profit and place the results in the separate results file. The screen capture MUST include the scenario name inclusive of “YOUR NAME” • • Specify cost of processing outgoing shipments o Navigate to the Processing cost table and create a table records for each DC o Specify the product and the cost of processing shipments. Enter: ▪ Product: PS4 ▪ Unit: pcs ▪ Cost: enter $0.58 for GFA DC’s 1 & 3, and $0.52 for GFA DC 2 Re-run the experiment Screen Capture 6: Profitability Take 3 Take a screen capture of the profit and place the results in the separate results file. The screen capture MUST include the scenario name inclusive of “YOUR NAME” 9 Part 3: Simulation Simulation experiment is used to model the actual products delivery on the GIS map with detailed statistics generated real-time. It is used as well for what-if scenarios to see how the changes you make affect the outcome. Simulation experiment works with the same set of data that is used for GFA and Network optimization experiments alongside the additional data provided for this type of experiment: Suppliers, Sourcing of products, Inventory policies, and Expenses incurred. Source: https://ww.anylogistix.com/help/index.jsp?topic=\%2Fcom.anylogic.anyLogistix.help\%2Fhtml\%2Fexperiments\%2FGFA.html Part 3 is associated with Video 3 ((accessible via Canvas). Part 3 is dependent on Parts 1 and 2. To complete Part 3 perform the following steps: • • Right-click the scenario name (within NO) and select Create Copy as SIM Prior to creating an inventory policy (below), add a group for DCs only. It should be the same as GFA group but will be named Your Initials_DCs and have the 3 distribution centers selected as sites. • Create inventory policy o Navigate to the Inventory table o Set all policies to Exclude o o o o Change the Product to PS4 Press Ctrl and click the word Policy Parameters to highlight the column. Press spacebar Set the values to Min: 300; Max: 3000 Highlight the Initial Stock column and set the values to 1000 10 • Create simulation experiment o Click Simulation experiment o Change the Product statistics unit to pcs o Right-click the empty space next to the word Dashboard and select Add item o In the selection menu, choose Revenue, Total Cost, and Profit and then click OK o o o Repeat the Add item step. Select Products and then Available Inventory. Click OK Repeat the Add item step. Select Demand Received Dropped Orders metric. Click the Run icon Screen Capture 7: Dashboard; Annual Performance • After running the simulation for a complete year, take a screen capture of the dashboard and place the results in the separate results file. The screen capture MUST include the scenario name inclusive of “YOUR NAME” • Run what-if scenarios o Navigate to the Inventory table o Adjust the Policy parameters cell in the GFA group row: Min: 2000; Max: 5000 o Set the Initial Stock, units to 2000. o Navigate back to the Simulation experiment and run it. o Compare the results of the two experiments Screen Capture 8: Dashboard; Annual Performance (Take 2) • After altering parameters and rerunning the simulation for a complete year, take a screen capture of the dashboard and place the results in the separate results file. The screen capture MUST include the scenario name inclusive of “YOUR NAME” 11 Part 4: Independent Simulation Video 4 is associated with Part 4 of this assignment. While not required (to watch), much of the information contained within will aide in the completion of the assignment. 1. Adjust the number and locations of the DC’s to only 2 • • • Return to the NO scenario and create a copy (use the initial scenario as a backup) Rename (right click and select properties) as follows: YourInitials_Independent Simulation Move, create, or delete warehouses o Make sure that you adjust the customer lists in the Product Flows table so each customer is served by the one closest DC o Adjust the Processing Costs as follows: ▪ Large metropolitan areas: $0.60 per piece ▪ Small metropolitan or outskirts of large metropolitan areas: $0.55 per piece ▪ Rural areas: $0.50 per piece 3. Create a new SIM and attempt to maximize your profitability by adjusting the inventory settings 4. Select the appropriate metrics (including profitability) and display on your dashboard 5. Summarize your results in a few paragraphs Screen Capture 9: Dashboard; Annual Performance (Independent Simulation) • After altering parameters and rerunning the simulation for a complete year, take a screen capture of the dashboard and place the results in the separate results file. The screen capture MUST include the scenario name inclusive of “YOUR NAME”. Additionally, your reflection (a few paragraphs) should be included. 12 startDate endDate description type GFA name My Supply Chain creationDate 2017-05-31 Name Type Phoenix Customer Dallas Customer Boston Customer Nashville Customer Orlando Customer San AntonioCustomer Denver Customer Seattle Customer PhiladelphiaCustomer Los AngelesCustomer Chicago Customer Detroit Customer JacksonvilleCustomer San Jose Customer Kansas City Customer Atlanta Customer New York Customer Salt Lake City Customer San Diego Customer Location Inclusion Type Icon Phoenix location Include Dallas location Include Boston location Include Nashville location Include Orlando location Include San AntonioInclude location Denver location Include Seattle location Include PhiladelphiaInclude location Los AngelesInclude location Chicago location Include Detroit location Include JacksonvilleInclude location San Jose location Include Kansas City Include location Atlanta location Include New York location Include Salt Lake City Include location San Diego location Include 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 Name Type Location Inclusion Type Icon Customer Product Phoenix Dallas Boston Nashville Orlando San Antonio Denver Seattle Philadelphia Los Angeles Chicago Detroit Jacksonville San Jose Kansas City Atlanta New York Salt Lake City San Diego Demand Type PeriodicDemand[period::2.0;quantity::108.0] PeriodicDemand[period::5.0;quantity::225.0] PeriodicDemand[period::5.0;quantity::10.0] PeriodicDemand[period::3.0;quantity::68.0] PeriodicDemand[period::2.0;quantity::18.0] PeriodicDemand[period::3.0;quantity::152.0] PeriodicDemand[period::3.0;quantity::70.0] PeriodicDemand[period::5.0;quantity::10.0] PeriodicDemand[period::3.0;quantity::165.0] PeriodicDemand[period::1.0;quantity::138.0] PeriodicDemand[period::3.0;quantity::287.0] PeriodicDemand[period::2.0;quantity::48.0] PeriodicDemand[period::1.0;quantity::30.0] PeriodicDemand[period::5.0;quantity::179.0] PeriodicDemand[period::5.0;quantity::83.0] PeriodicDemand[period::3.0;quantity::48.0] PeriodicDemand[period::1.0;quantity::300.0] PeriodicDemand[period::5.0;quantity::34.0] PeriodicDemand[period::1.0;quantity::50.0] Time Period (All periods) (All periods) (All periods) (All periods) (All periods) (All periods) (All periods) (All periods) (All periods) (All periods) (All periods) (All periods) (All periods) (All periods) (All periods) (All periods) (All periods) (All periods) (All periods) id date quantity Name DescriptionCustomers Sites Suppliers Groups Name Locations Code Name Region Denver location Salt Lake City location Chicago location Boston location Dallas location San Antonio location Kansas City location Jacksonville location San Diego location Seattle location San Jose location Detroit location Los Angeles location Atlanta location Nashville location Phoenix location Orlando location New York location Philadelphia location Country USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA USA Latitude Longitude Autofill Coordinates 39.73915 -104.985 FALSE 40.76701 -111.89 FALSE 41.87555 -87.6244 FALSE 42.36048 -71.0596 FALSE 32.77627 -96.7969 FALSE 29.4246 -98.4951 FALSE 39.08447 -94.563 FALSE 30.33218 -81.6557 FALSE 32.71742 -117.163 FALSE 47.60383 -122.33 FALSE 37.33619 -121.891 FALSE 42.34866 -83.0567 FALSE 34.05439 -118.244 FALSE 33.7491 -84.3902 FALSE 36.16223 -86.7744 FALSE 33.44859 -112.077 FALSE 28.54212 -81.379 FALSE 40.7306 -73.9866 FALSE 39.9524 -75.1636 FALSE Name Product Amount from Amount to Unit to Name Periods Name Start End Demand Coefficient Basic period2017-01-012017-12-31 1 Name Products Name Product Unit m³ Delivery Destination Product Source Time PeriodInclusion Type Name Type Location Products Inclusion Type Icon Currency Volume USD m³ nSitesConstr 1 maxDist 200 distanceUnitkm minimizeSitesNumber FALSE destinations(All customers) productUnitm³ sourcingPriority FALSE toSiteTranspCoeff 0.5 statsDistanceStep 100 realRoads FALSE latLonOffset 100 minPopulation 50000 newSiteIcon 2 name type GFA scenario My Supply Chain statisticsSettings GFA_FLOWS::true;d;f GFA_NEW_SITES::true;d;f GFA_DISTANCE_BY_DEMAND::true;d;f GFA_DEMAND_BY_DISTANCE::true;d;f GFA_TOTAL_DEMAND_BY_DISTANCE::true;d;f Units settings Currency::USD Volume::m³Time::day Distance::km timeType All periods startPeriod endPeriod startDate 2017-01-01T00:00 stopDate 2017-12-31T00:00 preProcessor postProcessor dashboardData Page name Chart type Accumulative Stats namesLayout dataDetalizationFilters Chart name dashboardData Product Flows CUSTOM_TABLE TRUE GFA_FLOWS0,0,36,8 Product Flows dashboardData New Site Locations CUSTOM_TABLE TRUE GFA_NEW_SITES 0,0,36,8 New Site Locations dashboardData Distance Coverage CUSTOM_TABLE by Demand TRUE GFA_DISTANCE_BY_DEMAND 0,0,36,8 Distance Coverage by Demand dashboardData Demand Coverage CUSTOM_TABLE by Distance TRUE GFA_DEMAND_BY_DISTANCE 0,0,18,8 Demand Coverage by Distance dashboardData Demand Coverage CUSTOM_TABLE by Distance TRUE GFA_TOTAL_DEMAND_BY_DISTANCE 0,0,18,8 Total Demand Coverage by Dista Total Demand Coverage by Distance customType name type Custom scenario My Supply Chain statisticsSettings DAILY_VEHICLES_SHIPPED::true;d,Type,Object,Vehicle DAILY_VEHICLES_USAGE::true;d,Type,Object,Vehicle TRAVELLED_DISTANCE::true;d,Type,Object,Vehicle DAILY_PRODUCTS_SHIPPED_INTERNAL::true;d,Type,Object,Vehicle AVAILABLE_INVENTORY_AMOUNT::true;d,Type,Object,Product,Per type;f CURRENT_BACKLOG_PRODUCTS::true;d,Type,Object,Pro type;f MAX_CAPACITY_VOLUME::true;d,Type,Obje type;f ON_HAND_INVENTORY_VOLUME type;f Units settings Currency::USD Volume::m³Time::day Distance::km timeType All periods startPeriod endPeriod startDate 2017-01-01T00:00 stopDate 2017-12-31T00:00 preProcessor postProcessor dashboardData Page name C ... 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