Intelligent Manufacturing Systems: Monitoring, Optimization and Control

Dear Colleagues,

Current manufacturing systems are required to produce both extreme tight tolerances and anomaly free safety-critical parts, but this is becoming very difficult to maintain and causes huge bottlenecks within the current supply lines. In addition, current methods rely on destructive tests on coupons which often have nonreplicated machine processes and are also not to scale, which does not represent the true nature of the material characteristics as experienced by the actual part during actual machining. It is not possible, however, to make destructive tests on the actual part due to no damage tolerance being present for in-service part(s). By using advanced methods of intelligent NDT, such measurements can be made to the part whilst also adhering to noninvasive compliance. This is one method that promises to address such bottlenecks; however, there are other aspects of intelligent manufacturing that also address such bottlenecks, such as improving efficiency through optimization, minimum wastage through intelligent control, as well as in situ monitoring, where parts are inspected during the manufacturing process to give further information in terms of machining conformance. In-situ monitoring also works in tandem with NDT methods. Such monitoring technologies can be made to function with autonomy and intelligence; such integrated systems act as advanced tools used to improve manufacturing.

All four areas within intelligent manufacturing systems can be applied to recycling materials where there is a huge need to reuse and remanufacture products or even, extend their life through remanufacturing/refurbishment. This reuse of materials is less energy-intensive than manufacturing a raw product from scratch. Whilst on the topic of recycling, the use of multipurpose 3D printing with CNC under intelligent manufacturing systems will also be considered for this Special Issue.

Dr. James M. Griffin
Guest Editor

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• fundamental investigations for understanding intelligent manufacturing systems
• manufacturing-monitoring technologies
• NDT/monitoring applied to difficult-to-cut materials
• high removal rates and tool condition monitoring
• sensors condition monitoring
• intelligent control of coolants and lubricants
• flexible control systems
• intelligent preparation and maintenance
• micro and precise intelligent machining technologies
• using intelligent manufacturing systems towards achieving zero-carbon manufacturing
• optimized algorithms for optimized design for CNC machining or 3D printing