Unlocking the Hidden Wealth Of Knowledge In Investment Casting: A Call For Data-Driven AI Integration


By David Ford, Former Director, Rolls-Royce Research Foundry Former Secretary General, EICF and Carlos Olabe, CEO European Investment Casters’ Federation


“It’s life, Jim, but not as we know it.” — Dr. McCoy to Captain Kirk, Star Trek


This prophetic line might well describe the future


for investment casting engineers in the age of Artificial Intelligence (AI).


The Role of Knowledge in Investment Casting nvestment casting


and fundamental data. Engineers tasked with defining manufacturing routes must interpret engineering drawings, specifications, and quality requirements while applying insights gained through years of exposure to the nuanced and variable nature of the process. With over twenty critical operations contributing to the


I


investment casting workflow - from wax pattern creation and shell building to pouring and solidification - expertise is often embedded in the tacit knowledge of seasoned professionals. It is this experiential foundation that AI must complement, not replace.


The Opportunity: AI and the Wealth of Existing Data It is increasingly evident that Artificial Intelligence will play a transformative role in our industry. The potential for AI- based process optimization, predictive modeling, and decision support is immense - if it can be fed with relevant and structured data. Fortunately, our sector possesses an underutilized


treasure trove of knowledge: • Conference proceedings from EICF, ICI, and national IC associations


• Research papers and collaborative project 10 ❘ April 2025


® is fundamentally a knowledge-


based industry, one in which success is derived from a delicate balance between empirical experience


reports involving industry, universities, and national laboratories


• Historic studies held in physical archives, often unpublished in digital format This repository of information - currently scattered


and in many cases inaccessible - represents a goldmine for AI-driven data mining, machine learning, and pattern recognition.


Engineering Judgment Meets AI Limitations Despite the impressive power of modern algorithms, AI is not a silver bullet. There are still many phenomena in IC that remain elusive, including: • Shell strength variability • Gating-related casting defects • Master heat variations • Random solidification anomalies • Dimensional instability • Process material fluctuations These irregular and often non-linear issues currently require the diagnostic skills of experienced engineers. Yet, with sufficient historical data and intelligent analysis, AI could one day help identify patterns or preconditions that humans may not easily discern—particularly across large datasets or multivariate relationships.


Examples of Valuable but Underexploited Resources Within the UK alone, several major national research programs have generated high-value technical datasets relevant to AI integration:


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