Assessment of MAS use cases in LSCM ordered by logistics network resilience potential
| Use case | Short description | PLNR | IQRPLNR | CVPLNR (%) | PP | IQRPP | CVPP (%) | CI | IQRCI | CVCI (%) | Δ PP-CI | Δ PLNR-CI |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| UC10 | Automated risk/event management | 4.2 | 1 | −9.6 | 3.2 | 1 | 0.0 | 4.1 | 1 | −33.3 | −0.9 | 0.1 |
| UC4 | Automated transport planning | 4.1 | 0.8 | 0.0 | 4.3 | 0.8 | 0.0 | 3.8 | 1 | −10.5 | 0.5 | 0.3 |
| UC6 | Automated rescheduling and production plan optimization | 4.1 | 0.8 | −9.6 | 4.4 | 1 | −12.9 | 4.5 | 1 | −27.2 | −0.1 | −0.4 |
| UC5 | Automated combination and optimization of transport and production plans | 4.0 | 0 | −33.3 | 4.4 | 1 | −20.8 | 4.3 | 1 | −7.4 | 0.1 | −0.3 |
| UC3 | Automated inbound supply planning and purchasing | 3.8 | 0.8 | 0.0 | 4.3 | 1 | 0.0 | 3.9 | 0 | −20.9 | 0.4 | −0.1 |
| UC11 | Simulating supply chain networks for optimization purposes | 3.8 | 1 | −24.7 | 3.8 | 1 | −6.8 | 4.0 | 1 | −2.5 | −0.2 | −0.2 |
| UC1 | Automated partner/supplier search | 3.6 | 1 | −7.5 | 3.4 | 1 | −9.4 | 3.4 | 1.8 | 0.5 | 0 | 0.2 |
| UC7 | Automated personnel scheduling | 3.6 | 1 | −20.4 | 3.9 | 0.8 | −4.6 | 4.0 | 0 | −13.4 | −0.1 | −0.4 |
| UC9 | Automated order processing/prioritization | 3.6 | 1 | −22.0 | 3.9 | 0 | −4.5 | 3.1 | 0 | −11.2 | 0.8 | 0.5 |
| UC8 | Automated in-house planning of intra logistics components | 3.4 | 1 | −21.7 | 4.0 | 1.5 | −4.4 | 3.4 | 1 | −16.4 | 0.6 | 0 |
| UC2 | Automated negotiations with suppliers | 2.9 | 1.5 | −10.1 | 3.5 | 1 | −14.7 | 4.0 | 1.8 | −13.0 | −0.5 | −1.1 |
| Short description | PLNR | IQRPLNR | CVPLNR (%) | PP | IQRPP | CVPP (%) | CI | IQRCI | CVCI (%) | Δ PP-CI | Δ PLNR-CI | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Automated risk/event management | 4.2 | 1 | −9.6 | 3.2 | 1 | 0.0 | 4.1 | 1 | −33.3 | −0.9 | 0.1 | |
| Automated transport planning | 4.1 | 0.8 | 0.0 | 4.3 | 0.8 | 0.0 | 3.8 | 1 | −10.5 | 0.5 | 0.3 | |
| Automated rescheduling and production plan optimization | 4.1 | 0.8 | −9.6 | 4.4 | 1 | −12.9 | 4.5 | 1 | −27.2 | −0.1 | −0.4 | |
| Automated combination and optimization of transport and production plans | 4.0 | 0 | −33.3 | 4.4 | 1 | −20.8 | 4.3 | 1 | −7.4 | 0.1 | −0.3 | |
| Automated inbound supply planning and purchasing | 3.8 | 0.8 | 0.0 | 4.3 | 1 | 0.0 | 3.9 | 0 | −20.9 | 0.4 | −0.1 | |
| Simulating supply chain networks for optimization purposes | 3.8 | 1 | −24.7 | 3.8 | 1 | −6.8 | 4.0 | 1 | −2.5 | −0.2 | −0.2 | |
| Automated partner/supplier search | 3.6 | 1 | −7.5 | 3.4 | 1 | −9.4 | 3.4 | 1.8 | 0.5 | 0 | 0.2 | |
| Automated personnel scheduling | 3.6 | 1 | −20.4 | 3.9 | 0.8 | −4.6 | 4.0 | 0 | −13.4 | −0.1 | −0.4 | |
| Automated order processing/prioritization | 3.6 | 1 | −22.0 | 3.9 | 0 | −4.5 | 3.1 | 0 | −11.2 | 0.8 | 0.5 | |
| Automated in-house planning of intra logistics components | 3.4 | 1 | −21.7 | 4.0 | 1.5 | −4.4 | 3.4 | 1 | −16.4 | 0.6 | 0 | |
| Automated negotiations with suppliers | 2.9 | 1.5 | −10.1 | 3.5 | 1 | −14.7 | 4.0 | 1.8 | −13.0 | −0.5 | −1.1 |
Notes:
PLNR = potential of logistics network resilience; PP = potential of productivity increase; CI = complexity of implementation; IQR = interquartile range; CV = convergence rate