Supply-chain & predictive-maintenance solutions
MB Engineering Group · Supply chain / Manufacturing
- Client
- MB Engineering Group
- Industry
- Supply chain / Manufacturing
- Scope
- AI training and test implementation of three AI systems for a major industrial group.
Photographs from the briefing
Solution
Epsilon trained the group's teams and implemented and tested three AI systems for one of the region's largest industrial groups — SupplyCha.INS for supply-chain intelligence, ManufactINS for manufacturing, and an offline Epsilon assistant.
Our approach
We implemented and tested three systems for one of the region's largest industrial groups — SupplyCha.INS for supply-chain intelligence, ManufactINS for manufacturing, and an offline Epsilon assistant — each mapped to the group's operating priorities, and trained the teams who use them. The supply-chain system models an Egypt control layer across representative nodes (Cairo, Alexandria, Port Said, Suez, Ain Sokhna, 10th of Ramadan, Borg El Arab, Damietta) connecting demand and inventory forecasting, supplier performance, logistics exceptions, warehouse capacity and port/customs status. No measured business results are published for this engagement.
Proposed Performance Targets
Proposed target
55%
Target reduction in assessed management-reporting time
- What is measured
- Compare existing and AI-assisted approaches to producing management summaries from equivalent operational data, with consistent requirements for accuracy, completeness and relevance.
- How it would be evaluated
- Matched reporting exercises completed before and after an AI Copilot workshop.
- What this figure is not
- A controlled reporting-task target, not a claim of group-wide cost savings or deployed-system performance.