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Hydrogen

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Decision making

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Python

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The image shows a supply chain sustainability report illustrating CO2 emissions from different transportation methods. A distribution center supplies goods to customers through three routes: (1) via road (120 km), air (1450 km), and road again (700 km); (2) directly by road for 200 km; and (3) through road, sea, and road again. Each mode of transportation highlights the distances, representing the CO2 emissions linked to the transportation network’s sustainability calculated with Python.

Diagram illustrating the driver allocation problem in a transportation network. A factory sends goods to two warehouses — North and South — via an ERP system. Both warehouses are served by a transport company, which allocates drivers (D1, D2, D3). Black arrows represent balanced driver allocations to the North Warehouse, while red arrows indicate an unbalanced allocation to the South Warehouse, causing delays. This introduce Lean Six Sigma with Python using Chi-Squared Test.

Diagram illustrating the “Parcel Packing Problem.” comparing two configurations for packing parcels in an e-commerce fulfillment center. The first case, “Single Line,” shows one conveyor belt with two parallel packing stations. The second case, “Multiple Lines,” shows two separate conveyor belts, each with its dedicated packing station. The objective is to determine the most efficient setup for parcel packing using the Queueing Theory with Python.

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