IBM > Case Studies > Analytics used to precisely plan and schedule production

Analytics used to precisely plan and schedule production

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Company Size
1,000+
Region
  • Asia
  • Europe
Country
  • Italy
Product
  • IBM ILOG CPLEX CP Optimizer
  • MBM Italia S.r.l — GPS 64b (Global Planning System)
Tech Stack
  • Mathematical Optimization
  • Simulation
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Cost Savings
  • Productivity Improvements
Technology Category
  • Analytics & Modeling - Predictive Analytics
  • Analytics & Modeling - Process Analytics
Applicable Industries
  • Metals
Applicable Functions
  • Discrete Manufacturing
Use Cases
  • Advanced Production Planning and Scheduling
  • Flexible Manufacturing
Services
  • System Integration
About The Customer
Danieli & C. Officine Meccaniche S.p.A. is a large company based in Europe that designs, constructs, and sells plants and equipment for the metallurgical industry, such as steel and iron. The company has factories in five countries across Europe and Asia. The company's operations involve the complex process of building steel mills and the related equipment, which requires the orchestration of thousands of components, workers, and machines.
The Challenge
Building steel mills and the related equipment is a highly complex process that requires orchestrating thousands of components, workers and machines. Lacking modern planning software, Italy-based Danieli & C. Officine Meccaniche S.p.A., a steel plant builder with factories in five countries in Europe and Asia, struggled to coordinate materials and resources, compromising efficiency and jeopardizing timelines.
The Solution
Danieli chose a mathematical optimization solution that takes into account all production constraints of every single plant, enabling the builder to develop optimal production schedules that align with order requirements, delivery dates and manufacturing goals. If changes in production plans occur, what-if scenarios show their effect on workloads while the solution runs multiple simulations and results are delivered in a few seconds, helping Danieli schedule its flexible manufacturing system (FMS) machine operations.
Operational Impact
  • With a centralized installation, Danieli can now calculate production costs much quicker, saving one hour for the first scheduling in the kick-off phase.
  • An additional benefit was the reduction of nonoperative time, or downtime, on machinery, which helps improve the ROI on expensive equipment.
  • Unlike before, the company’s flexible manufacturing system (FMS) machines are now working 24 hours per day, resulting in huge savings in terms of increased efficiency and equipment ROI.
Quantitative Benefit
  • Saved one hour for the first scheduling in the kick-off phase
  • Reduced nonoperative time on machinery
  • FMS machines are now working 24 hours per day

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