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| Scenarios allow users to input a range of values for a particular field, such as service level, transportation cost, or production capacity. Guru will then automatically run an optimization or simulation using the range of values specified by the user in the scenarios. This allows users to test multiple inputs quickly, without the need of copying, pasting, and running several models individually. Guru can now run a single model, with multiple input ranges in one optimization or simulation run. The outputs can then be viewed graphically or numerically in the standard guru reports. |
| Groups are used to aggregate customers, products, sites, modes, and periods in a Guru model, simplifying and speeding the model building process. Instead of creating transportation policies for every source/destination/product, users use groups to apply the same policy across a number of products, sources, or destinations. Groups are also used to automatically aggregate or disaggregate demand where appropriate. For example, network models typically aggregate SKU level demand into product groups. The grouping functionality in Guru will then automatically take the SKU level demand file and aggregate into the user defined groups. In this way, a single SKU level demand file can be used for network optimization, inventory optimization, and simulation. |
| Guru can incorporate sophisticated constraints to model flow, inventory, production, and site rules that will restrict the optimization. For example, minimium production quantities can be applied for a production line for a group of products. Similarly, minimum or maximum site constraints by period could limit the number of DC's or production sites used. Custom constraints can also be incorporated using the Mosel language - which is typically a one to two day process for LLamasoft consultants. |
| Numerous capacity constraints can be incorporated into Guru. Site level capacity is used to model a high level constraint on production or throughput at a plant or DC. These capacities can be a fixed number or users can apply a step function to model capacity and costs that shift based upon the level of capacity. Processes model multi-step production at sites, where users can apply times, resource requirements, changeovers, and lot size rules. Work centers allow users to apply detail capacity for a specific work center for a particular process. |
| Guru allows users to model processes and process steps that can represent complex production processes used by manufacturing facilities. Each site can have multiple, unique process steps, each with their own work centers, capacities, and resource requirements. In addition, upstream processes from other sites can create interdependencies across production facilities, which are then part of the overall optimization in Guru. |
| Input Pipes is an innovative technology that simplifies and speeds the collection, updating, and maintenance of key data elements used for optimization and simulation analysis. Input Pipes allows users to take complex data such as transportation costs for source/destination/products or product/plant production costs and create automated links into Guru, without the need for re-creating the tables. These data tables can be continually maintained outside of Guru, which will pull from the tables to receive any cost updates automatically whenever an optimization or simulation run is initiated. |
| Geographic information system mapping in Guru allows users to view, edit, and analyze key inputs and outputs visually. Users can apply multiple layering to filter views on key inputs such as transportation policies, key products, or apply their own user defined filters. Users can apply object properties to click on sites or lanes to view or edit cost, capacity, and other key information. Outputs such as DC to customer flows can be sized based upon quantity, weight, service distance, and other metrics. Multi-map views allow for side by side analysis of baseline versus proposed new supply chain networks. Maps can also be copied and pasted onto Power Point or other documents, and can also be exported to Google Earth for further analysis. |
| Within SC Guru are transportation rate tables for LTL, FedEx, and UPS Ground, and UPS Air services. Users can incorporate input pipes to link these rate tables to their transportation policies without the need to re-create the cost matrix. |
| Supply
Chain Guru installs natively on both 32 and 64 bit operating
systems, enabling users to model the largest possible supply
chain designs at the appropriate level of detail without system
memory constraints. Through our unique integration with SupplyChainGuru.com,
users do not even need to have a 64 bit operating system to
run extremely large models. With one click from the Supply
Chain Guru user interface, models can be uploaded to SupplyChainGuru.com
and run on the LLamasoft cloud-computing environment. Results
can be shared directly on SupplyChainGuru.com or downloaded
back to the local system. |
| In addition to the use of input pipes for quick loading of external data, import/export wizards can be used to quickly load data used for a Guru model. Users can simply right click on any data table, click export to Excel, and the table and its headings are placed in Excel to be populated, saved, and then imported back into the model. Outputs from a Guru model can also be exported to Excel for detailed analysis and reporting. |
| Scripting allows the modeler to incorporate real world business rules and custom costs and statistics into a simulation. It is an object oriented programming language that has been developed specifically to interact with SimServer, LLamasoft’s proprietary simulation engine. It is powerful not only because it makes the simulation output more meaningful by making the input logic more realistic, but also because it can be done by the individual modeler, thus eliminating the need for a software enhancement |
| SC Guru incorporates model verification and infeasibility analysis that allows the user to identify errors in model input and design prior to running the optimization, saving time. Model verification runs through over 40 different checks for referential integrity, consistency, and missing fields. Both errors and warnings are viewed, with specific messaging to point users to the cause of the issue. Infeasibility analysis checks for network structure, demand/supply imbalanaces, and detailed constraint violations prior so that users can identify and correct inputs that may cause a model to be infeasible, before the optimization is run. |
| SC Guru contains the GHG emissions rate for all major transportation modes including diesel train, coal train, electric train, inland ship, marine ship, long air, medium air, short, air, and road freight. These rates are then applied to the weight per unit of product and per unit of distance shipped. In addition, users can input GHG emissions applicable to production and warehousing, giving a complete picture to the supply chain's carbon footprint. |
| Transportation assets - such as a private fleet - and containers - such as pallets or storage units - can be modeled in SC Guru to understand their impact on cost and capacity in a supply chain. Users can model these assets in an unconstrained fashion and have Guru determine how many trucks or pallets were needed. Conversely, these assets can be used as a constraint to understand potential bottleneck issues in the supply chain. |
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