It is well known to the Investment Casting Industry, that the Investment Casting process is a process of processes and, as such, variability becomes an issue, which, in its last manifestation, could lead to increased scrap rate and derived problems.

Process Control is the discipline to have this potential variability under control. Because of that different monitoring and control tools are extensively being implemented in the manufacturing processes. However, the new opportunities and functionalities that the digital transformation brings along create a new scenario in which the possibilities for process control are being enhanced and the type and amount of data to be monitored and analysed are much more abundant. This new scenario claims for a rationalized and integrated revised philosophy of process control.

Aim of the course

The primary objective of this course is to provide participants with advanced knowledge and practical skills in leveraging Industry 4.0 technologies for enhanced process control in investment casting manufacturing. The course aims to equip participants with the ability to optimize production, improve product quality, and maximize efficiency in investment casting through the integration and application of cutting-edge technologies and methodologies. 

The main methodology that governs an effective control performance in continuous improvement evolution is PDCA (Plan, Do, Check and Adjust) starting from the design of the product, comprising all the development stages to finally get to the in-time delivery of the components manufactured with the expected quality and price. These stages are empowered with a smart and digitalized control that needs to be accurately defined and deployed.

1. Advanced design control. A complete digitalization strategy must be developed to generate a smart process to carry out complex data processing and precise decision making. Digital audit is fundamental to fix priorities for the integration of industry 4.0 technologies in the manufacturing process. In parallel, final product development needs an advanced quality development strategy (APQP) supported in tools (flow chart, control plan, FMEA) to assure that the delivery of samples and batches is made in time and with the quality and price committed with the customer. It is worth mentioning how tool and mold design and construction are key stones in this process, requiring the coherent use of concurrent engineering, advanced design rules like Niyama and lean production criteria to assure the final expected evolution in Key Performance Indicators (KPIs) 
2. Integrated and synchronized process controls. Critical criteria in process performance are 1) the quality and accuracy of controls supported in the implementation of tools such as X-R, working instructions, technical data sheet and purchase specification 2) productivity by means of OEE, SMED, Lean manufacturing and 6σ and 3) service by the in-time delivery of the product to the customer using FIFO, production capacity and advance scheduling tools.
3. Digital process control integrates new digital capabilities of equipment for data capture and transmission with the centralization, preprocessing and linking of process data. The target is to make data management and business/process decision making simpler and more accurate by facilitating the access to specific datasets to make advanced consultations and settling correlations between parameters/data. The representation of process condition is supported in digital twins so deviations can be detected in real-time and corrected before they could affect main KPIs. These aspects are managed by tailored smart orchestration platforms that integrate all the operative algorithms and digital modules and offer personalized information deployed through friendly interfaces and specific action-outputs.
4. Accurate product controls. Final product must be manufactured according to drawing and specification defined with the customer. Because of that measuring has to be accurate. To assess the needed precision analytical tools like capacity measurements and MSA are used. Robust control techniques must be defined and correctly used, comprising destructive (such as microstructure, chemical analysis, and mechanical tests) and non-destructive techniques (like penetrant testing and X-Ray). All these techniques must be tightly implemented following procedures that include operative aspects, equipment, and training to assure the repeatability and reproducibility of measurements.
5. Efficient management. The definition of main KPIs is the first step to be able to follow up the evolution of the process and product performance in a coherent way.  The digitalization of the process represents an opportunity also for the general management of the company: the access to information is faster and the information is more reliable and valid, as far as it is obtained in real time. The integration in the digital and smart system of continuous improvement techniques such as Pareto or Ishikawa links process and product variables with main KPIs and makes decision making more agile and accurate. 

Getting a deeper insight of what is going on in every step of the manufacturing process and being able to link manufacturing parameters with the end features of components is key to a successful and robust manufacture. 

ICT tools keep evolving hand in hand with data analysis and Artificial Intelligence. Digitalization and process monitoring are named to revolutionize the way castings are manufactured; and to keep its space and competitiveness among the manufacturing technologies of the future, the industry cannot stay aside of this transformation. 

For sure, new solutions in digitalization and scheduling will keep arising.  In this framework, these must be tightly followed by technological surveillance and digital strategic decisions will have to be taken using competitive intelligence.

Philippe Hoste, September 2023