In today's manufacturing world, real-time transparency on the store floor is essential. Store floor data collection (SFDC) and machine data collection (MDC) provide the necessary information to effectively plan and optimize production. While PDC is a must as a prerequisite for our AI-based detailed scheduling , MDC is the "cherry on top"
BDE & MDE: The database for smart production planning
PDC systems record important operating data such as production times, machine set-up times and production status. MDC, on the other hand, focuses on machine data such as running times, downtimes and faults. Together, they enable precise analysis of production processes and provide the basis for well-founded decisions in detailed scheduling. But data alone is not enough - it only develops its full potential when it is used intelligently. This is exactly where Advanced Planning and Scheduling (APS) comes into play.
What is PDC (production data acquisition)?
Production data acquisition is aimed at the manual or semi-automated recording of production-relevant process data. It documents processes and statuses that are usually initiated or confirmed by humans.
Typical BDE data:
- Order start and end
- Good and scrap quantities
- Set-up and downtimes
- Staff times (e.g. attendance, start of shift)
- Feedback on work steps or production progress
What is MDE (machine data acquisition)?
Machine data acquisition, on the other hand, takes place fully automatically directly at the machine - in real time and without manual intervention. It provides objective information about the technical condition and activity of the systems.
Typical MDE data:
- Machine running times
- Cycle times
- Machine downtimes (with fault reason)
- Energy consumption
- Sensor or measurement data (e.g. temperature, vibration)
APS: Dynamic detailed scheduling for the modern store floor
APS systems use the data collected in real time from PDC and MDC to continuously and dynamically optimize production plans. Machine availability, capacity limits, material flows and personnel resources are constantly taken into account.
What does this mean in practice?
1. higher resource utilization
- Less idle time thanks to automatic reallocation of orders when machines are idle
- Better set-up optimization through clever order sequencing (e.g. paint sequence for painting systems)
2. shorter throughput times
- Avoidance of unnecessary waiting times, e.g. due to material availability
- Faster cycle times for bottleneck machines thanks to dynamic prioritization
3. high responsiveness in the event of faults
- Automatic rescheduling for:
- sudden machine downtimes (MDE)
- Urgent orders with higher priority
- Staff shortages or material delays
4. transparent simulations
- "What-if" analyses enable well-founded decisions:
- What happens if a machine breaks down tomorrow?
- How does an additional night shift affect delivery deadlines?
Workflow management: efficiency through integration
By integrating PDC, MDC and APS into a comprehensive workflow management system, companies can seamlessly control their production processes. This leads to improved transparency, faster response times in the event of faults and an overall more efficient production chain.
Conclusion: Networking data, leveraging potential
The combination of PDC, MDC and APS forms the foundation for modern, efficient and transparent production planning. Companies that integrate these systems are better equipped to meet the challenges of Industry 4.0 and continuously optimize their production processes.
