Smart manufacturing initiatives are not just about factory floors. Its positive impact will propogate across related functions, as overviewed below:
Marketing: Marketing will be able to offer faster delivery times on a higher variety of products at lower cost and with a competitive delivery time that the market defines. AI data mining of revenue and factory margin by part number will define opportunities and challenges for marketing, engineering and operations.
Engineering: Engineering can use interquartile analysis to eliminate and prevent outliers and evaluate the accuracy and scope of data collection by part number, and standardize internal processes such as routings, setups and tool part numbers. They can work with production control to minimize cost using AI neural network tools that are impossible for humans to detect on a daily basis.
Accounting: Accounting can measure daily manufacturing eficiency to track the metrics and work with engineering and operations on AI corrective action plans on low factory margin products and to find trapped waste. The goal is to increase production capacity and EBITDA, thus dramatically increasing ROIC.
Operations: Operations can create systems like AI pull system groups to replace existing lean pull systems. This will increase the number of different part numbers at Neural Networks and hence the probability of shared setup. It can work with engineering and accounting to focus on excess cost part number and create a daily AI pull production system schedule that minimizes total setup time and delivery time using a Neural Network scheduling method.
Quality Control: Quality will be inspecting more and smaller lot sizes with AI and may evaluate and adopt optical pattern recognition software with greater than 99% acuracy, which is superior to human inspection.
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