According to Little’s Law, the cycle time or transit time of Work in Process through any process is equal to the number of units of Work in Process (WIP) divided by the rate at which units exit from the process1. Therefore, we wish to release the minimum amount of WIP into the process which is consistent with the customer demand and the operating parameters in the factory – customer demand, WIP in each Job’s routing, setup time, run time, downtime, etc. This requires us to calculate the minimum batch size per job that should be released. The resulting reduction of WIP results in a dramatic reduction of cycle time and assures 95% on-time delivery. Production efficiency is increased due to the application of AI Generic Setup time reduction methods2 which results in a 75% reduction. Examples of a few of the calculations performed by the AI Accelerator Minimum Cycle Time Program are contained in the reference below3.
The AI Min Setup Time Job Sequences results in the fastest delivery time consistent with existing production parameters. The quantity released on each job is dynamically calculated prior to each released based on the knowledge of WIP at each Pull Station in the router of each Job. This yields a powerful competitive advantage in delivery time which consistently increases Revenue in today’s stressed Supply Chains. Minimum inventory which is immediately shipped improves cash flow and virtually eliminates any losses due to excess Finished Goods inventory.
“Lean Sigma in the Age of Artificial Intelligence”