A system for identifying production plan feasibility and calculating containers to deliver raw materials
January 2021 – present
Tetla de la Solidaridad, Tlaxcala, Mexico
Learn how we quickly and cost-effectively helped our client:
Identify a solution to their delivery management problem
Minimize time-consuming manual processes and human error
Lower labor costs by automating work done by an analyst
Reduce shipping costs through optimized container use
Decrease storage costs to retain clients and attract new ones
Ensure software interoperability and scalability
The first version of our client’s load planning system provides core functionality for:
Calculating availability of materials/components
Comparing calculations based on changing parameters
Planning the number of containers needed to fulfill the shipment
Updating production plans based on updated delivery plans
Client’s video testimonial
01 BUSINESS CONTEXT
123 Sourcing is a fourth-party logistics company that provides services like transportation, consolidation center storage, picking and packing, inventory forecasting, order fulfillment, packaging, and freight forwarding.
The company supplies manufacturing plants with raw materials from multiple suppliers to ensure uninterrupted production. This process was fraught with difficulties due to urgent changes on both the manufacturers’ and suppliers’ sides:
Manufacturers had to contact the company to update delivery plans. Only based on these updated plans could the manufacturers’ schedulers update their production plans to check if they were still feasible.
The company’s staff had to manually recalculate and rearrange the delivery plan in response to changes via phone calls to suppliers and manufacturers. This process was time-consuming and resulted in errors.
Production plan changes made it difficult for the company to know how many containers to book.
To reduce lead time and errors, our client decided to automate their delivery management. To meet this business need, Yalantis invented a web service that unburdens the client from playing the role of an intermediary between manufacturers and suppliers.
Identifying production plan feasibility
The calculator we designed considers production plan data and arrival dates of components to the consolidation center.
The manufacturer’s scheduler interacts with the calculator in the following way:
1. They define the production plan, which includes its implementation date, the number of products to produce, the bill of materials, and the production lead time.
2. The manufacturer’s scheduler asks the calculator if it’s feasible to deliver raw materials and components to the client’s consolidation center to implement the production plan.
3. The calculator states if the plan is feasible or not. If not, the system provides the context (e.g. suppliers A and C will meet the deadline, while supplier B won’t).
4. The scheduler decides what actions to take if some parts can’t be delivered to fulfill the production plan. Based on this decision, the consolidation center decides how many containers it has to book or cancel.
Identifying the number of containers needed
By using the calculator, our client’s staff can estimate the least number of containers required to allocate all components. The calculator considers container filling by weight and volume.
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03 YALANTIS' APPROACH TO DEVELOPMENT
Our client sought a software solution partner experienced in logistics development and able to analyze the company’s processes to offer an effective, cost-efficient, and fully customized solution.
Defining the client’s “as is” and “to be” processes
We took the following steps to identify the bottlenecks and future state of our client’s business processes:
1. Identify and describe the current state by eliciting requirements and creating corresponding business analysis artifacts
2. Quantify and document the current state's bottlenecks
3. Define the future state by identifying its success metrics
4. Research similar ready-made solutions (none fully covered
the client’s needs but was useful as a source of ideas)
5. Describe the future state and its realization by creating documents including a value stream, roadmap, activity diagram, and feature map
We needed to quickly develop a cost-effective proof of concept system that would lay the foundation for future integrations and add-ons. Let’s see how we accomplished this task:
To ensure proper interoperability, we considered our client’s current technical stack and aligned the architecture of our solution with available technologies.
The client also wanted to be able to make fast changes in the system. We laid the basis for a multi-tenant architecture that can easily be deployed after moderate modifications.
02 Optimized calculation of containers
To optimize the calculation of containers needed to fulfill a shipment, we researched and selected the most relevant solution. We chose Google OR-Tools, a suite of algorithms that helped us ensure fast and cost-efficient development.
03 Smooth and effective data management
For the first product version, all data used for calculations is taken from JSON files uploaded to the system by users. A user can change the data — such as the type of container, its size, or a production week — and the result of the calculation will change respectively.
04 PROJECT RESULT
A manufacturer had to keep additional inventory in the client’s consolidation center, as production planning took a long time and involved many steps and roles. If the production plan changed, our client’s staff had to recalculate the delivery plan and make numerous phone calls to suppliers and carriers, leading to human error.
Any compulsory recalculations initiated by changes from manufacturers or suppliers are carried out in a matter of seconds instead of hours.
An analyst is no longer needed to calculate the production plan feasibility, saving labor costs for the client.
There’s no need for overstocking, as the manufacturer’s scheduler receives an updated shipment plan based on an updated production plan. This helps our client’s customers save on storage costs, ensuring their satisfaction and loyalty.
Human errors like improper delivery planning, unoptimized container filling, and forgetting to make important phone calls are minimized.
Shipping costs are optimized thanks to proper planning of the number of containers needed to fulfill the delivery.