Architecture and knowledge modelling for self-organized reconfiguration management of cyber-physical production systems

Figures & data

Figure 1. Contribution to the overall concept of self-organized reconfiguration management for cyber-physical production systems.

Figure 2. CPPS architecture for self-organized reconfiguration management.

Figure 3. CPM information model.

Figure 4. Production order information model.

Figure 5. Stateflow simulation model of a system configuration (example).

Figure 6. Optimization utilizing a simulated annealing algorithm (example).

Figure 7. EMF based modelling and XML file creation workflow.

Figure 8. Unity simulation of the modular production system.

Figure 9. Principle of the applied SBC.

Table 1. Defined evaluation scenarios.

#	Trigger	Complexity	Start config.	Production order	Description
1	New production order	Low	1	Cover sheet 1	Cover sheet with logo and holes
2			2	Spacer disc 1	Spacer disc with holes
3			3	Spacer disc 2	Additional threads
4		Medium	4	Cover sheet 2	Additional reduction in height
5			5	Cover sheet 2	Additional reduction in height
6		High	6	Machine part	Workpiece with troughs and threads
7			7	Machine part	Workpiece with troughs and threads
8	Component failure	Low	8	Cover sheet 1	Failure in PunshingB
9			9	Spacer disc 2	Failure in PunshingCheckingC
10		Medium	10	Cover sheet 2	Failure in PunshingCheckingB

Figure 10. Resulting XML file.

Table 2. Results of the evaluation scenarios.

#	Production order	Existing reconfiguration demand?	Correct result?	Prediction accuracy
1	Cover sheet 1	Yes	✓	85,90%
2	Spacer disc 1	Yes	✓	97,60%
3	Spacer disc 2	Yes	✓	98,50%
4	Cover sheet 2	Yes	✓	98,72%
5	Cover sheet 2	Yes	✓	96,56%
6	Machine part	Yes	✓	82,52%
7	Machine part	Yes	✓	79,03%
8	Cover sheet 1	Yes	✓	96,68%
9	Spacer disc 2	Yes	✓	95,19%
10	Cover sheet 2	No	✓	-