Has worked with logistics teams for years to implement inform and improvement Tools for advanced logistics.
To prepare for the transition to a circular economy, they have Additional requirements to manage the collection and classification processes.
What are the additional processes we need to monitor and optimize?
In this section, we will briefly cover several examples of process design requirements with associated analysis solutions.
Descriptive Analytics: Product tracking and traceability
Due to regulations, you must ensure that products are used and processed as sustainably as possible.
Therefore, logistics teams must be able to clue and trace products throughout their life cycle.
For direct logistics, products are tracked from the factory to the store.
- Master data databases will include (Stock Keeping Unit), SKU number, product information (size, color, packaging)
- Production systems You can provide the batch number (useful if you need to call items), production date and factory location.
- Warehouse and Transportation Management You can track the product throughout the logistics chain, from receipt at the warehouse to delivery at the store.
How can tracking of returned items be supported with advanced analytics?
For reverse logistics, logistics requests your support in monitoring the flow of “returned” products from the collection box toward sorting center.
Different logistics systems that record transactional data can be used as data sources to create automated flow monitoring tools:
- Enterprise resource planning (ERP) records customer returns in the store with Store locationSKU ID, Quantity, Collection Box ID and Pickup time.
- Transportation management systems records collection of collection boxes, including store location, collection box ID, and collection time.
- Warehouse management systems Tracks items from receipt to the end of the sorting process with SKU ID, pick box, receipt time, sort completion time, and final destination.
Business Intelligence methodologies that use a central data warehouse can support the creation of harmonized tracking data sources that can be used for audits or reporting.
If you need more details on how to implement it, check out this article.
Now that you have provided transparency to operations, let's focus on process optimization.
Prescriptive Analytics: Classification Network Design
Logistics teams would like to design a network of sorting centers that minimizes environment impact of the reverse flow.
The optimal network may differ from the current one, as it is necessary to collect after-sale items and reintroduce recycled materials into the chain.
They shared with you
- A list of possible sorting locations with their capacity. (Units/Day)
- Store reverse flow volume forecasts. (Units/Day)
Ask: Where should we place sorting centers to minimize costs and CO2 emissions?
This will remind you of the supply chain network optimization problem for which you need to design a factory network.
Market demand must be met by factories with limited capacities and different costs to produce and deliver goods.
Linear programming is used to select appropriate factories that minimize overhead costs while respecting a set of constraints.
For more details, take a look at this detailed example.
How can we adapt this solution to the classification network design problem?
This can be easily adapted to this new problem.
- Demand => Units collected from stores (Units/Day).
- Factory Capacity => Classification Capacity of each Center (Units/Day).
You can then select the optimal set of sort locations based on your goal.
- Minimize total costs?
The algorithm will consider the transportation costs (from the stores to each sorting location) and the classification costs from each center. - Minimize CO2 emissions?
The algorithm will try minimize distance from the store to the selected centers.
Now that you have selected the optimal set of sort centers, you can organize reverse flow.
Prescriptive Analytics: Reverse Flow Optimization
The transportation team requests your support in designing a tool to assign the appropriate sortation center to each store.
In fact, as volumes and capacities evolve, you'll be better off dynamically assigning a sortation center to each store on a weekly or daily basis.
Ask: For each store i, which center should sort the returned items to minimize transportation costs?
In a previous article, I addressed a similar problem: the supply planning problem.
Several factories supply distribution centers that store products and deliver stores.
To answer this problem, we also use linear programming to
- Optimize upstream flows from factories to distribution centers.
- Deliver each store from the right warehouse
This solution can be used after slight adaptations
- Define (or forecast) volumes from sorting centers to final recycling location.
- Define the capacity of each sorting center
You can then follow the approach (and use the code) detailed in this article.
Now that we have designed the network of sorting locations and developed a tool to optimize reverse flows, we can work on monitoring performance.
