PlanningVis: A Visual Analytics Approach to Production Planning in Smart Factories.

Area of Science:

• Manufacturing Systems Engineering
• Data Visualization
• Operations Research

Background:

• Effective production planning is vital for manufacturing resource utilization and cost reduction.
• Industry 4.0 generates vast data, offering opportunities for data-driven production planning.
• Challenges include data volume, product dependencies, and dynamic market/plant conditions.

Purpose of the Study:

• To develop a systematic visual analytics approach for production planning.
• To enable detailed comparison and exploration of production plans.
• To support rapid adjustments to production plans due to unforeseen incidents.

Main Methods:

• Proposing PlanningVis, a visual analytics system with three detail levels: plan overview, product view, and production detail view.
• Integrating an automatic planning algorithm with interactive visual exploration.
• Conducting case studies with real-world data and expert interviews.

Main Results:

• PlanningVis facilitates exploration and comparison of production plans at multiple granularities.
• The system supports efficient optimization of daily production plans.
• It enables quick responses to unanticipated incidents in manufacturing.

Conclusions:

• PlanningVis effectively addresses limitations of previous studies by providing detailed comparative analysis.
• The system enhances the optimization of production plans and adaptability to disruptions.
• Demonstrated effectiveness and usability through real-world case studies and expert validation.