Artificial intelligence (AI) for high productivity advanced manufacturing (ProductivAI)

ProductionAI将为印刷电路板制造和真空镀膜行业开发一种新的工艺优化工具包，从而提高工艺效率，从而减少能源消耗和浪费，并提高满足具有挑战性(和商业吸引力)的规格和缩短周转时间的能力。当前的精益六西格玛方法通过在流程迭代过程中遵循高度手动的程序进行持续改进来提高效率。ProductionAI将使公司在具有挑战性的规格和严格的质量标准下实现“第一次正确”生产的能力发生重大变化，同时通过更高的产量、更有效的工艺和更快的生产能力来减少能源消耗、浪费和成本，并有可能实现显著的年度节约。这些好处将通过使用机器学习优化方法来实现，该方法首次专门针对电子和涂料行业的需求而定制，并集成在精益的六西格玛框架中。该系统将自动化并大幅加快工艺改进和历史数据的再利用，以优化工艺条件。我们方法的新颖方面包括使用特殊的两阶段优化过程，即使对于复杂的过程也能提供快速的全局优化，并使用数据合成来实现更快和更准确的模型培训。这种新的技术方法将被集成到精益的六西格玛框架中，供上述行业的从业者快速采用。这些算法将在一个软件平台中实施，以便于使用并与其他质量和企业软件工具集成。该工具包的有效性将通过印刷电路板制造和真空涂层的两个使用案例进行演示，为这两家先进制造行业公司在工艺性能方面提供直接收益。

ProductivAI will develop a novel toolkit for process optimisation in PCB manufacturing and vacuum coatings industries, enabling process efficiency improvements resulting in reduced energy consumption and reduced waste and improved ability to meet challenging (and commercially attractive) specifications and short turnaround times. Current lean six-sigma methodologies provide efficiency gains through continuous improvement following highly manual procedures over process iterations. ProductivAI will make a step change in the ability of companies to achieve "right first time" production output to challenging specifications and stringent quality criteria whilst reducing energy consumption, waste and cost through higher yields, more efficient processes and faster throughput with potential for significant annual savings.These benefits will be achieved through the use of a machine-learning optimisation approach tailored, for the first time, specifically to the needs of electronics and coatings industries and integrated within a lean six-sigma framework. The system will automate and massively speed up process improvement and reuse of historical data to optimise process conditions. Novel aspects of our approach include the use of a special two-stage optimisation process which provides rapid global optimisation even for complex processes and the use of data synthesis to achieve faster and more accurate model training.This novel technological approach will be integrated into a lean six-sigma framework for rapid adoption by practitioners within the aforementioned industries. The algorithms will be implemented in a software platform for ease of use and integration with other quality and enterprise software tools. The effectiveness of the toolkit will be demonstrated trough two use cases in PCB manufacture and vacuum coatings, providing the two advanced manufacturing industry companies with direct gains in process performance.