The client needed to optimize the shop floor schedules across three different production processes summing up more than more than 30 machines.
Process wise, roles & responsibilities were lose with multiple daily changes to production schedules contributed to low equipment overall efficiency (OEE) and longer lead times.
The solution must accommodate customer driven business rules & various constraints inherent to the production process & machinery.
The context is a quite profitable Tier 1 manufacturing plant for the Pulp & Paper industry.
Operational performance needed a level-up in monitoring and control of execution and development of critical management tools.
Manual, Excel & paper based business process.
Scheduling was people-driven, not system-driven.
Machine Sequencing Mathematical Optimization Using Python
OPERATIONAL PLANNING & SCHEDULING
Implementation of Master Plan to match demand & capacity based on mix.
Redefinition of high-level & detailed Operational Planning process from monthly view to daily dispatching.
Formalized Roles & Responsibilities (RACI).
Dispatching process: Definition of daily/shift deliverables at WO level.
INDUSTRY 4.0 & OPTIMIZATION
Integration of Business Rules & Constraints,accommodating all the usability requirements demanded by stakeholders.
Mapping of inputs and parameters impacting an optimal sequencing: a system-driven approach.
Mathematical algorithm to optimize sequencing, resulting in 5% production time improvement and 12% set up time reduction.
Automated reporting integrated with BI tool.