KNIME for Supply Chain Analytics

Build customized end-to-end workflows

 

Discover the fusion of supply chain management and data science expertise with Log-hub and KNIME, a leading open-source data analytics platform. Our partnership delivers tailored end-to-end data workflows, seamlessly integrating AI-based supply chain solutions directly into KNIME.

Gain deeper insights into your supply chain data and experience optimized operations, reduced costs, and enhanced decision-making.

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Extending KNIME Capabilities

Whether it’s optimizing transportation routes, managing warehouse operations, or conducting network design studies, Log-hub’s specialized nodes seamlessly integrate with KNIME to deliver robust solutions that address specific challenges faced by Supply Chain Management professionals.

What you get

Access to Expertise

With Log-hub’s team of experts, you get decades of combined expertise in supply chain management and data science, ensuring solutions are tailored to your unique supply chain challenges.

Cutting-Edge Technology

Access KNIME’s data analytics platform, and perform sophisticated data analysis, predictive modeling, and optimization without extensive programming knowledge.

Seamless Integration

Log-hub’s AI-based solutions integrate seamlessly into KNIME via specialized nodes, enabling you to access and leverage cutting-edge technology directly within KNIME’s platform.

Tailored Solutions

Collaborate closely with Log-hub and KNIME to customize and implement solutions tailored to your supply chain needs. Stay ahead of the competition by making data-driven decisions.

Comprehensive Support

Throughout your supply chain journey, from initial customization to ongoing optimization, rely on the support and expertise of both Log-hub and KNIME to ensure the success of your initiatives.

Expertly Crafted Supply Chain Data Workflows Tailored to Your Projects

Manipulate, transform, analyze, simulate, optimize, and visualize data without the need for extensive programming knowledge.

We help you build end-to-end data workflows for your sophisticated supply chain projects. Log-hub’s team of seasoned supply chain and data experts stands ready to customize and implement KNIME’s end-to-end data science capabilities specifically for your supply chain challenges.

Supply Chain Management use cases of KNIME

 

Discover the most common business cases we resolve with our expertise.

Center of Gravity Analysis in Excel, Network Design Optimization, Nearest Warehouse
TRANSPORT OPTIMIZATION

✔ Route and Tour Optimization – Ship, Road, Rail

✔ Fully automated Sustainability reporting based on your transport network

✔ Simulations of routes and tours

✔ Network Design Study

✔ Tariff Optimization

✔ Rail Cockpit

✔ Truck distribution across locations

✔ Identification and Monitoring of Failed Routing

✔ Lead Time per Location

WAREHOUSE OPTIMIZATION

✔ Warehouse optimization based on different scenarios

✔ Warehouse – live dashboard

✔ Warehouse – Cockpit

INVENTORY OPTIMIZATION

✔ ABCD analysis under consideration of semi-finished products

✔ Inventory Master Data Management

✔ Material Compliance transparency

✔ Product Management Cockpits

✔ Demand forecasting with AI

SUPPLY CHAIN MANAGEMENT VISIBILITY

✔ SCM Analytics infrastructure

✔ SCM Dashboard harmonization

✔ SCM Human resources planning (platform and dashboard)

✔ Risk monitoring with optimization recommendation

✔ Supply Chain Visibility Cockpit – 360°

✔ Order fulfillment status – Overview (near-real time)

✔ Automated Forecasting of Next Day Workload

OTHER

✔ Predictive Maintenance

✔ Supplier Performance Management

✔ Excel Automation

✔ Cost Allocation across Companies

✔ Pallets and Containers Monitoring

✔ Pallets and Containers Quality Monitoring

✔ Structured initiation of dashboard tools

✔ Report & dashboard harmonization

✔ SCM Cloud strategy

✔ Worktime-Analysis and Compliance validation

Transform Your Perspective and Your Supply Chain Management Processes

Schwandweg 5, Schindellegi

Switzerland 8834

Tel: +41 41 560 03 99

support@log-hub.com

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