Development of dynamic supply chain simulation model for Tata Steel UK (2 plants, 28 production centers including 3 casters, 49 external warehouses). The model embraces production scheduling, WIP and finished products inventory management as well as transportation by rail and sea. The model is used to identify system bottlenecks for different demand profiles. Another purpose of the model is to develop, test and evaluate algorithms of prioritizing production and customer orders.
Period: February 2017 – February 2018
Industry: Metallurgy
Client / Partner: Tata Steel / Goldratt Research Labs
Project objective
- Develop a plan of production and supply chain
- Determine the bottlenecks of the chain
- Evaluate the effect of changing the algorithms for prioritizing production and customer orders
The main stages of work and characteristics of the model
- Performing data gathering and transformation
- Development and testing of a simulation model on the AnyLogic platform
- Verification and validation of the simulation model in cooperation with client’s team
- Technical and methodological support of the client’s team at the stage of scenario analysis
Model input data
- Information about used materials (materials group, technological production chain, planned delivery time, etc.)
- Location and capacity of production centers and materials storage locations
- Inventory balance in storage locations
- Route sheets that set production parameters
- Costs of materials, storage, transportation, and packing
The main structural elements of the model
- Input data file of scenario in MS Excel format
- Simulation model with interactive presentation
- Data aggregation module that allows to generate MS Excel files with the simulation results
Model output data
- Customer service level
- Stock movement of end-products and work in progress, materials turnover
- Total costs of production chain and costs by cost category
Project result
Simulation-based tool for integrated planning of rolled steel production and logistics, quantitative estimation of effect of changing the algorithms for prioritizing the production and customer orders