Software applications, commonly known as apps, have become an integral part of our day-to-day personal and professional lives. Computer integrated manufacturing and automation have been widely adopted in the metal casting industry since the Industry 3.0 revolution of the ’70s and ’80s compared to other competing manufacturing processes. Figure 1 depicts an overall manufacturing software system schematic example.

Over the past two decades, hardware has become lot faster, especially with multi-core processors, GPUs, hyper-threading, and high-performance parallel computing, making various complex engineering software applications practical and valuable in the real, production-agile environment. In the coming years, I envision specifically solving the complex differential equations driving metalcasting physics with the use of quantum computers with greater speed and accuracy.

The software engineering industry is going through a significant change as technology continues to advance at a rapid rate. The emergence of cloud computing––which began well over a decade ago––is one of the major driving forces behind this change. Cloud computing can be thought of as the transmission of computing services via the Internet. In other words, it makes it possible for people and organizations to utilize computing and storage resources as needed, without the need for specialized hardware or infrastructure, a node locked, or multiuser floating network licensing as currently exists with most of these tools, relevant to metalcasting.

Cloud computing has revolutionized the way businesses operate by providing instant access to customizable computing resources, including networks, servers, storage, applications, and services, via the Internet, enabling a new level of productivity, flexibility and efficiency. As the advancement and adoption of cybersecurity software tools come into play, cloud computing will become more viable and attractive.

In selecting the right software tool for a company’ needs, users must consider the cost of acquisition, training, and annual maintenance, as well as quality of the service and support provided by the vendor––along with the hardware and operating system required.

Following is an overview of the current availability and advancements of metalcasting design and manufacturing software tools. Disclaimer: The author’s company, PDA, has either used or is familiar with most of the software tools discussed in this article, but we have no vested interest in promoting any one of them––the order in which they are listed has no significance to their market position or preference. The key to our ability to solve complex problems has been the continuous acquisition and upgrade of technologies, both hardware and software tools, as they have emerged over the past 30 years. These tools are periodically and continuously upgraded with newer releases, and users must keep up with these updates to get the most value out of them, which requires a provision in the annual budget.

Design and Engineering

CAD and CAM. In the current digital era, almost all the casting designs are created in a 3D CAD system––very few legacy parts still use 2D drawings created on the drawing board or CAD tools. The number of OEM engineers who are knowledgeable about castings is diminishing, so foundry engineers are getting more involved with the new product development, conversion, and redesign. To provide that value-added engineering support to their customers, progressive foundries are equipped with the CAD capabilities (SolidWorks, Creo/Pro-E, NX, CATIA, Inventor, Fusion 360, SpaceClaim to name a few). Typically, one CAD software tool is sufficient to get the 3D CAD data files either in the native file format or using STEP, IGES and STL neutral file formats and then collaboratively using virtual web meetings and sharing tools to develop new casting designs that are manufacturable. Also, a CAD tool is a must for accurate and timely quoting the costs of tooling, fixturing, raw casting, machining, and other secondary operations.

For tooling design and fabrication engineering, CAM software is also required to generate the tool path for milling with 3–5 axis CNC machines. Most of the CAD software tools have CAM extensions; additionally, there are specialized CAM tools such as MasterCAM, PowerMill, DUCT, to name a few.

AM Printers. Polymer 3D AM printers (e.g., FDM, SLS, SLA) are also becoming common place in foundries for prototype tooling, as well as for building rigging elements, which require the design of support structures and internal honeycomb core structures. Tools that facilitate this work include Cura, Simplify3D, Fusion 360, NetFabb, and Magics. Most of the 3D printers require STL file input and have their own slicer software.

For legacy and obsolete parts, there is a need for reverse engineering capabilities from a sample casting, using either a touch probe like CMM or 3D scanning with laser, white light, or CAT scan radiography. These hardware tools are also used in the inspection and dimensional validation of the tooling and castings, and they require software tools to build 3D models from the point cloud scan data and dimensional deviation analysis. Figure 2 shows an example of a 3D scanned iron casting made using a 3D printed sand core  compared to the 3D model. Brand name tools include PolyWorks, Artec Studio, Wrap, Volume Graphics, to name a few.

Modeling & Simulation. Modeling and simulation technology has matured tremendously since the 1980s and are being widely used not only by progressive foundries, but also by complex casting designers and end users. Top tools today include MagmaSoft, Pro-Cast, Flow3D, CAPCast, Novacast, SolidCast. Some of them use FDM (Finite Volume) or FEA numerical method to solve simple Bernoulli’s to complex Navier Stokes equations coupled with energy balance and heat transfer by conduction, convection, and radiation modes. Current software tools simulate most of the prevalent casting and molding processes and alloys. The choice of the tool depends on the overall size, complexity, section thickness, in addition to the ease of use and accuracy of the results desired.

Comprehensive casting process modeling software tools are capable of simulating mold filling, solidification, and cooling, and predicting micro-structure, mechanical properties, residual stress and distortion, along with filling- and solidification-related flaws such as primary and secondary shrinkage porosities, hot tearing, the tendency of gas and pin holes, mold erosion, reoxidation, inclusions, and dross formation. Figure 3 is an example of predicting hot tear in an investment cast Ni based alloy with correlation to the actual hot tear seen in the casting.

These are very effective tools, not only for validating the casting design, but also for assisting, validating, and optimizing the rigging (risering and gating) design and process parameters. Multi-phase- and multi-physics-driven solvers and tools are on the horizon.

All these engineering software tools––FEA, CFD, Casting Process Modeling––require an immense amount of data for every material being used to make castings. Metalcasters must consider casting alloy engineering properties at room as well as operating temperatures, thermo-physical properties (thermal conductivity, specific heat, density, latent heat to mist a few), as well as thermo-mechanical properties from room temperature to the pouring temperatures. To provide myriad pedigree property information to design and foundry engineers, PDA, in collaboration with AFS, has developed a web-based tool called CADS – Casting Alloy Data Search, which is available online at www.afsinc.org or at www.afscads.com. Data includes composition, section thickness of the test bar, and molding process. Figure 5 shows the homepage with three search options available for CADS tool. This online resource has over 400 alloy data sets––series of aluminum and magnesium alloys; complete set of iron alloys; and some steel and copper based alloys widely used by the industry and OEMs. All the reference reports from which the data is extracted are linked and accessible through AFS’s Virtual Library portal. CADS also has some data sets that have been incorporated into the Metallic Materials Properties Development and Standardization Handbook maintained by the Federal Aviation Administration through DOD/DLA-funded research efforts by AFS over the past 15 years. This is an ongoing effort to incorporate more data into the portal and has been found to be very valuable to the design and engineering community of metal casting.

Quotation and Legacy Systems

Typically, each foundry has its own activity-based costing software for generating cost estimates and quotation––these can be as simple as a home-grown excel file or using a CAD software that can generate cost estimates. Foundries can also employ a dedicated cost-estimation software like Priori or a comprehensive ERP/MRP legacy software system. Legacy software allows the foundry to track individual part cost and count, inventory at various stages, direct labor and material costs, production planning and scheduling, purchasing operations, supply chain integration, on-time delivery performance, preventative maintenance scheduling, and other enterprise performance and forecasting using data analytics and financial reporting.

Production Manufacturing

Foundry process engineering data communication to shop floor workers has drastically changed from the of using Polaroid camera photos with hand written instructions–– today we have tablets with 3D models of the tooling with rigging, and we even see AR- and VR-driven process instructions on the horizon, which will be especially valuable for the training and communicating the newer workforce in various areas of the foundry operation, including maintenance.

Numerous software tools are being used in various areas: charge calculator in the melting department; metallurgical and sand testing laboratory monitoring the quality; molding line tracking and traceability; casting scrap and rework Puerto for quality assurance. While Excel files are still used, adoption is increasing for more advanced SPC tools such as Minitab, Tableau, and meta data reporting and dashboard software tools such as PowerBI and Domo.

Casting dimensional inspection using touch probes (traditional gantry type CMM or portable arms) or non-contact 3D scanners using laser or white/blue light are driven by software tools for inspection, which report the deviation analysis after comparing it with the 3D CAD design intent data to the customer. (These are the same tools discussed under reverse engineering capabilities.) In the near future, we will see wider adoption of AI-driven software tools assisting quality workers for casting visual inspection, micro-structural image analysis, and quantification.

Specialized software tools and viewers are used for digital radiography, such as Volume Graphics or hardware embedded with similar 3D viewers for characterizing and reporting various discontinuities with severity and locations to customers/end users, especially in the complex automotive, aerospace, and defense/safety-critical areas of casting manufacturing.

Robotic process automation (RPA), also known as software robotics, uses automation technologies to mimic repetitive tasks of human workers in harsh foundry environments such as de-gating, grinding, wax pattern dipping in investment casting, casting extraction, and die spray in high-pressure die casting. RPA combines APIs and user interface (UI) interactions to integrate and perform repetitive tasks between enterprise and productivity applications, sensing the environment around the robot(s). By deploying scripts that emulate human processes, RPA tools complete autonomous execution of various activities and transactions across unrelated software systems.

This form of automation and intelligent machine uses rule-based software to perform business process activities at a high-volume, freeing up human resources to prioritize more complex tasks. RPA enables decision-makers to accelerate their digital transformation efforts and generate a higher ROI from their staff, especially in the current skilled-worker shortage environment.

Robot programming is programming the PC/SBC/microcontroller/PLC inside a robot for performing a specific application using actuators and feedback from various sensors. Robot applications include pick and place of the object or moving a robot from A to B, and most of the hardware vendors have embedded programming software that communicates with various controllers, both offline and online.

Secondary Operations

Some of the comprehensive casting process simulation software tools go beyond the shakeout time or temperature boundary condition into simulating various heat treatments like annealing, normalizing, and quenching. However, specialized software tools have emerged such as Dante as well as classical thermal FEA software that performs heat treatment modeling, including “hipping” (hot isostatic pressing). Some software tools are able to predict the pressing and straightening of the distorted castings, such as Deform, for example. CNC machining of complex castings, as discussed under engineering, need CAD and CAM software tools.

Connected Digital Manufacturing

Additive Manufacturing (AM) is an important sub-set of Industry 4.0, and the foundry industry has adopted AM very widely over the past decade with the use of binder jet 3D printers to make 3D printed cores, molds, wax-like patterns for investment casting, and direct ceramic-printed shells using digital light processing AM technology. These are all tooling-less digital metal casting processes and require specialized engineering slicer and build-box layout software. Most of the hardware vendors provide them––Fusion 360, Netfabb, Magics, to name a few. In addition to a CAD tool, an STL viewer is also very useful to validate the quality of the 3D geometry, ensuring against leaks or open loops that could disrupt the 3D printer operation.

In the era of digital transformation and Industry 4.0, foundries must create a connected, data-centric enterprise, which is an additional burden of software integration on top of their day-to-day production. However, survey and research indicates the payback is tremendous with Industry 4 adoption: improved efficiencies by reducing waste, improved throughput and profitability with better utilization of resources, and near real-time visibility of the overall and individual areas of the foundry’s operation and efficiency. To achieve operation connectivity, IIOT devices (sensors, PLCs, hardware data acquisition devices) collect data from various areas and, using AI/ML-driven data analytics tools, generate a tremendous amount of output data in near real-time for decision-making at every level of the organization. The ultimate goal is to build a process and system digital twin, which is a virtual model designed to accurately reflect a physical object for greater accuracy and reliability of the operation.

AI- and ML-driven meta models and algorithms derived from historical production data are being developed to predict and compute corrective actions to aid foundry process engineers to make decisions in near real time.

Numerous open source codes are available, such as R, which develops custom tools––foundry engineers should be familiar with the Python, Jeson-type scripting programming language, and Matlab-type software tools for data mining and sorting. [KP1] Open source codes like NodeRed are going to be a norm for IIOT connectivity and data acquisition in various foundry operations using sensors, Raspberry Pie, PLCs and IOT (IT and OT) devices in this exciting Industry 4.0 era. For building a connected operation, tools like Ignition, Azure, and Woderwave are now in use, and the list is going to grow. One important point: There is no silver bullet solution software tool or a provider that covers all of Industry 4.0, which makes adoption challenging and requires resourcefulness.

With the wide use of the Internet and digital threads connecting various operational areas both onsite as well as offsite, and geographically dispersed with remote operators and locations, we are opening up our manufacturing systems to a range of new cybersecurity risks and threats. Foundries need to have the cybersecurity plan and software tools in place, and this could be challenging for small- and medium-sized enterprises with limited resources and investments.

Jiten Shah has over 38 years of metalcasting design, manufacturing, and contract research and development experience in various alloys and processes. He finds solutions of various complexity using different CAE and casting process modeling tools, rapid prototyping, AM, AI/ML-driven meta model development, and Industry 4.0 adoption. He can be reached at jiten@pda-llc.com.