Production Planning:12 wk pilot implementation

Objective: Develop a production planning MVP solution that can determine an optimal schedule based on planned orders and factory constraints using OR techniques

Key Challenges Addressed:

1. Inability of traditional production planning solutions to respond to rapidly changing customer orders
2. Suboptimal production quantities not aligned with customer demand, resulting in shortages for certain SKUs and excess inventory for other SKUs

How do we address your challenges: Tredence’s smart MPS optimization tool employs OR algorithms to optimize production planning and simulate scenarios to visualize impact on plan by changing planning parameters or planning objectives. This results in an increased revenue by reducing lost sales and lowered finished goods inventory by manufacturing the optimal quantity of products to meet the demand.

POC Outcome: A tactical MVP solution which can generate weekly production schedule and insights on cost metrics and asset Utilization associated with fulfilling the predicted demand.

Implementation Plan The break-up of the implementation plan is as below:

1. Week 1 to Week 3: Conduct data discovery and set baselines
2. Week 3 to Week 10: Develop optimization and simulation tools
3. Week 10 to Week 12: Validate and refine model output and handover the pilot solution

This implementation uses the following native Azure components:

1. Azure Data Factory: For data extract-transform-load (ETL) to deal with data coming from disparate production systems.
2. Azure App Services: For developing web apps for users to consume insights and provide inputs on production plan
3. Azure Databricks: For developing optimization and simulation models to generate the ideal production plan