Very good paper - Link
Key Notes (Copied/ summarized)
The impact areas are
- Technology (from IoT to autonomous driving),
- Value Add (from on-the-go production to product monitoring),
- Control Tower (from central planning and control unit to asset sharing along the supply chain)
- Green Logistics (from emission avoidance to return logistics).
Four major future trends
- Modern sensors enable self-controlling products in the supply chain
- Logistics data in real time (e.g. through IoT and 5G) will significantly improve order processing and logistics processes
- Digital services
- Parallelization of production / Transport
- Participants
- Supply chain management looks at the cross-company material flow, from the raw resources to the finished products, and optimizes all transport processes along the value chain
- The goal is cost-efficient planning
- Chain to dynamic networks transformation
Influencing Factors
- Demographic changes
- Digitization / connectivity
- Globalization
- Urbanization
- Mobility
- Knowledge culture and information society
Cause and Impact
Technology (production and IT technology)
- Future manufacturing processes
- The guiding principle of "Uberization"
Value Add (market-expanding additional services)
- IoT in means of transport and load carriers
Control Tower (central collaboration center)
- Centralization could regulate the flow and exchange of relevant data in a comprehensive and, most importantly, neutral manner
Green Logistics (ecological sustainability)
Technology
- Machine learning, deep learning and predictive analytics
- Improve the accuracy of the demand forecast
- Identify anomalies in manufacturing accuracy
- Reduced freight costs
- Avoidance of empty runs and dynamic route optimization
- Another step in the field of artificial intelligence is
- self-learning algorithms: these learn from their positive and negative decisions and thus increase their prediction and decision quality over time
- Especially autonomous loading via OneShot-Loading and the subsequent autonomous unloading at the destination increase the autonomy.
Value Add
Control Tower
- Central data storage
- Orchestration and support for worldwide supply chains of country-specific regulations
- Exchange / trading of data
- Uberization for means of transport, load carriers
- Cross-vendor orchestration and last mile optimization
- AI for individual or holistic optimization of capacity utilization
- Optimization of routes, delivery corridors / slots at the loading ramp
- Automatic document creation or error analysis in documents
- Control of return logistics e.g. using a platform.
Green Logistics
1. Know and report emissions for transport and products
2. Reuse parts / components or individual raw materials
3. Compensate or reduce emissions
Recommendations
Supply chain Speed
- Customers are demanding shorter lead times in the supply chain
- Ensure the resilience of logistics networks in difficult times (natural disasters, trade embargos, shutdowns due to epidemics etc.)
- Parallel networks need to be set up to mitigate the probability of failure
- Container transport by sea from Asia to Germany vs. transport via the Silk Road
Autonomous infrastructure
- OneShot-Loading and automatic battery charging processes hold a high potential for savings
Planning accuracy and prediction mechanisms
- The most important added value in the future will be the (automatic) recommendation of what to do next (Prescription).
- IoT-based real-time data transmission instead of manual transmission
- Not only in the primary chain (producers), but also in the secondary chain with partners (logisticians, banks, personnel service providers etc.)
- In addition to the classic logistics events (customer requested change, delayed truck, production disruption)
- Drones and delivery robots better assign the transports to the correct delivery medium
Data culture
- Which functions are direct and which can be sold as additional services with the help of IoT solutions
- Which data can / do I want to monetize and which data do I need for this
- The availability of GPS transmitters on pallets or ideally at the product level
Data sharing along the supply chain
- Proactive messages to the next process steps in a supply chain (e.g. dynamically determined arrival time of a truck at the sea terminal for the delivery of a sea container)
- Capacity requirements for transport services, both from the production/trade industry
Production techniques
- 3D / 4D printing processes
Environmental protection
Very Very good paper, A lot of insight into use cases / future technologies / centralized system/network.
Keep Learning!!!
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