To handle operational complexity, manufacturers turn to real-time manufacturing operations management systems.
Learn a story of our client who wondered how to improve the capacity and efficiency of the production resource management.
Our customer, a manufacturing company in the chemical industry, faced the growing demand of its customers for small, tailor-made batches of products delivered quickly, often within just a few days of ordering. It contrasted with the company operations designed for large volumes of standard products with production runs measured in weeks or months. In addition, the massive increase in the complexity of operations management forced managers to look for real-time planning and scheduling methods, especially when equipment goes down, critical employees get sick, or the truck drivers meet unexpected failures.
AI can comb through and extract insights from data much more quickly than any human planner. That is why we concentrated on delivering a solution that ensures smooth and predictable production powered through real-time data from IoT sensors, information from RFID chips, and logistics data.
Using the power of AI, we developed a solution for managing decisions regarding production scheduling in real-time based on precise rules and parameters set by production managers. As a consequence, they got a system for the maximum optimization of working time and resources.
We allowed the system to automatically download the data from ERP and other sources to give on fly visibility to managers from different business areas, help plan a better balance of services, inventory, and people, and make appropriate adjustments when necessary.
How did we overcome obstacles
The introduction of an AI-based system for our client’s production planning appeared to be a wide-ranging digital transformation of his business. Therefore we had to capture all the nuances of the production process to show the value step by step and provide adequate support in time and after implementation. That is why we: