FOUNDRY processes are very energy-intensive and, in many cases, cause considerable environmental concern.1 Therefore, smart manufacturing principles that can reduce waste and increase efficiency can be extremely beneficial. The term Industry 4.0 is often known as Foundry 4.0, or Logistics 4.0.2 Foundry 4.0 refers to the inclusion of stated Industry 4.0 principles into the foundry industry. This needs a centralised control system where customer orders are placed via a system by using integrated Material Requirements Planning/Enterprise Resource Planning (MRP/ERP) software. This controls the factory through its supply chain and production needs autonomously. A lot of technological advancements need to be made to fulfil them. Most of these advancements are grouped into nine pillars of Industry 4.03 as shown in Figure1. Industry 4.0 describes a state of industry characterised by thorough digitisation of economic and production flows. It requires horizontal integration at every step of the production process, in interaction with machines. In the globally interconnected world of Industry 4.0, machines also interact with one another.
In aluminium foundries, digital tools help to reduce part-load energy consumption for melting and ensure dosing and holding furnaces are always fed with exactly the right amount of liquid metal at the right time. For die casting machines, one can digitally track predefined time, maintenance actions, and monitor sensor values. Most of the high pressure die casting foundries are highly automatised. Everything, from metal pouring, over die spraying, to part ejection is usually performed by robots. Collecting, tracking, and analysing shot-blast process data helps operators to spot emerging problems and tackle cost drivers like abrasive consumption, energy use, and excessive maintenance. On the other hand, sand foundries are often far less automatised, although there are sand foundries that employ automated guided vehicles and a wide array of robots. In the green-sand process, Industry 4.0 tools can be applied at every stage, from mixing sand to shake out and quality control.
Industry 4.0 is built on nine technology pillars. These advancements bridge the digital and physical worlds and make autonomous and smart systems possible. Supply chains and businesses are already using some of these innovative technologies, but the full completion of Industry 4.0 comes to the front when used together.
The IIoT refers to the networking and connectivity of all devices within one organisation. Each machine and each product are equipped with a wide array of sensors giving a complete insight into every detail of the production process. Radio-frequency identification (RFID) uses electromagnetic fields to automatically identify and track tags attached to objects. An RFID system consists of a tiny radio transponder (wireless communications), a radio receiver, and transmitter. When triggered by an electromagnetic interrogation pulse from a nearby RFID reader device, the tag transmits digital data, usually an identifying inventory number, back to the reader. This number can be used to track inventory goods. Individual machines and smart products can communicate and exchange data over one single network.4
The Industrial Internet of Things is so central to Industry 4.0 that the two terms are used interchangeably. Most of the physical things in Industry 4.0 – devices, machinery, robots, products, equipment, – use sensors to provide real-time data (real-time data is data that is available as soon as it is created and acquired. Rather than being stored, data is forwarded to users as soon as it is collected and is immediately available – ‘without any lag’ (which is crucial for supporting live, inthe-moment decision-making) about their performance, condition, or location. This technology lets organisations run smoother supply chains, rapidly modify and design products, stay on top of consumer preferences, prevent equipment downtime, track products and inventory, and much more. Foundry 4.0 concept relies heavily on system integration and utilisation of big data to promote data-driven decisions. Therefore, promoting IIoT and acquiring ‘smart’ machines equipped with an adequate number of sensors and actuators is the first step toward the realisation of Foundry 4.0.5
Analytics based on large data sets has come out recently in the world of manufacturing, where it optimises quality of production, improves equipment service, and saves energy. Big data analytics in Industry 4.0 is in the context that the comprehensive evaluation and collection of data from many different sources – production equipment and systems and organisation. Huge data collected from IIoT needs to be methodically arranged and analysed. Now things have started to change, and several foundries have implemented machine learning algorithms. For example, predictive models were successfully implemented in a high pressure die casting foundry for the prediction of cold shut and porosity defects.6
Manufacturers in many industries have used robots to tackle complex assignments, but now they are progressing towards greater utility. They are becoming more flexible, autonomous, and cooperative. Hence, they will interact and work safely with humans and learn from them. These robots and analytics chatbot will be economical and have a more excellent range of capabilities than those used in manufacturing today. A cyber-physical system (CPS) is an integration of computation with physical processes whose behaviour is defined by both cyber and physical parts of the system (Figure2). Embedded computers and networks monitor control the physical processes, usually with feedback loops where physical processes affect computations and vice versa.7
These systems should not be confused with industrial robots that are currently extensively used in foundries, e.g. fettling robots. Most current fettling robots follow pre-programmed paths with additional elastic tool suspensions (passive systems), or sensors (adaptive control) in order to compensate for variations in casting dimensions and positioning tolerances. True CPS autonomous robots of the future-
would be able to adapt to specific casting, as much as a human. For example, by image recognition or 3D scanning, the system will be able to detect positions where flash is present and perform operations only on those areas, thus reducing the time necessary for fettling operation. In a more distant future, one can imagine a system that will be able to compare geometries of a scanned casting and ideal 3D model (with tolerances), automatically select the right tool and machining parameters, and then perform all required machining operations autonomously.
Horizontal and vertical integration of cyber-physical systems is very dependent on connectivity and the internet. The risk of hacking and data breaches in such systems is real and constantly growing. The existing cyber security systems need to be upgraded and present one of key enablers for the implementation of Foundry 4.0 concepts. A closer look at a digital journey shows that foundries typically start by applying Industry 4.0 tools to individual machines or processes, and then build out their infrastructure in stages to eventually support their entire operation. Machine sensors, foundry networking, and edge devices are the foundation stones.
Horizontal integration predicts constant communication between individual subsystems within the production process in order to respond autonomously to changing production conditions. Every system at the same level, e.g. production level, is connected with all other systems. The process is, as much as possible, planned and adjusted by the machines themselves and decision-making is decentralised. This integration is to be achieved within a single enterprise, e.g. between pouring, moulding, and finishing systems, but also across the entire supply chain. For example, as soon as a production order is placed, or current supplies fall under a predetermined level, the system in command of the melting process should be able to directly connect with the dispatching system of a supplier and order additional alloying elements or fluxing agents. All this should be done automatically and without any human intervention. This goal requires the development of new standardised industrial internet protocols and data formats. Current systems from different suppliers are often too heterogeneous. This increases the time and cost of system integration.
Industry 4.0 allows companies, departments, functions, and capabilities to become much more cohesive. Cross-company, universal data integration evolves and enables truly automated value chains. Vertical integration is a strategy that allows a company to streamline its operations by taking direct ownership of various stages of its production process rather than relying on external sources. Vertical integration aims to connect all layers within a single organisation from the production floor, through the research and development department, quality control, sales, and marketing up to the executive level. Information is transparently shared in order to follow several parameters simultaneously and finds the best compromise between them based on first principles. However, this approach is just a small step toward full implementation of simulations as envisioned by the Foundry 4.0 goals.
In addition to process simulation, the concept of Foundry 4.0 implies extensive use of plant simulations. By creating digital twins (a digital twin is a virtual representation of an object or system that spans its lifecycle, is updated from real-time data, and uses simulation, machine learning, and reasoning to help decision-making) of the physical systems and processes one can shorten interruptions and prevent potential scheduling problems. All changes in machine parameters and production planning are first tested in a virtual environment, and only after successful optimisation are transferred to the actual physical system. Currently, such systems do exist.
Foundry 4.0 is important because it allows die casters to execute the die casting process in a smarter way. It involves the use of software programs that can monitor the die cast process and provide data about each step in the process. This software then can analyse the data and make decisions to resolve any thing it determines is an error in the process. Thus, the use of automation reduces those problematic defects. The outcome is a more efficient process.
Numerical simulations of foundry processes are in development since the 1950s and are extensively used in the industry for more than 30 years. Commercially available software packages can predict filling and solidification patterns, residual stresses, distortions, microstructure, and mechanical properties with or without heat treatment. This enables detection of possible casting defects before the first casting is poured and optimisation of casting technique with respect to process robustness. Simulations are typically performed and analysed by highly trained and experienced engineers. The alternative is to go for Foundry 4.0 and invest in modules for autonomous optimisation.8
By utilising this route, foundry engineers do not need to spend significant time manually running numerous simulations to find optimal process parameters. The software currently used in most of the IT systems is not fully integrated. Organisations, customers, and suppliers are rarely closely linked. Functions in the organisation are not fully integrated. From plants to products to automation lack complete integration. But with Industry 4.0, organisations, functions, departments, and capabilities will become much more firm, as cross-organisation, universal data-integration networks evolve and enable truly automated value chains.
Horizontal integration predicts constant communication between individual subsystems within the production process in order to respond autonomously to changing production conditions. Every system at the same level, e.g. production level, is connected with all other systems. The process is, as much as possible, planned and adjusted by the machines themselves and decision-making is decentralised. This integration is to be achieved within a single enterprise, e.g. between pouring, moulding, and finishing systems, but also across the entire supply chain. For example, as soon as a production order is placed, or current supplies fall under a predetermined level, the system in command of the melting process should be able to directly connect with the dispatching system of a supplier and order additional alloying elements, grain refiners, and fluxing material. All this should be done automatically and without any human intervention. This goal requires the development of new standardised industrial internet protocols and data formats. Current systems from different suppliers are often very heterogeneous. This increases the time and cost of system integration.7.
These technologies can enable easier interactions between humans and cyber-physical systems. For example, with augmented reality eyeglasses, a worker can be guided by the system to find and mount appropriate patterns or perform specific fine-tuning as detected by embedded sensors. Or virtual reality can be utilised to perform a detailed analysis of the foundry’s digital twin from another physical location, e.g. from the comforts of one’s home. Foundry workers wear augmented reality LAEMP ear lenses that transmit real-time video of their visual field to remote technicians that are guiding them through maintenance, training, or fine-tuning tasks. Established communication is two-way. Remote technicians have the possibility to share visual information with foundry workers in real-time. For example, they can share machine schematics or point an arrow to the bolt that needs tightening by superimposing images into the workers’ line of sight.9
Another possible use of virtual and augmented realities is the training of new workers. One example of this approach in the foundry industry is the development of a virtual die casting machine simulator. The simulator uses a 3D gaming engine to create a virtual environment where new operators can be trained with realistic interaction. The training is connected to numerical simulation software so that the trainee can visualise how his or her actions influence the final process and properties of produced castings.10 With AR, employees gain experience and skills much faster.
Additive manufacturing technologies are already part of the everyday production process of many foundries. First to use additive manufacturing techniques were the investment foundries. First stereo-lithography and later fused deposition modelling techniques were utilised to produce patterns for prototype or low volume productions.11 More recently, some investment foundries started using additive manufacturing techniques for producing highly complex ceramic cores used for the production of parts for the aerospace sector.12 Selective laser sintering was found as a useful technique for the production of complex tool inserts and cores for high pressure die casting tools. Additive manufacturing enables the use of conformal cooling channels that offer significant advantages over geometries that are possible to produce by classical machining techniques.13
If this technology can be made cost-effective, one can imagine that this technology could revolutionise high pressure die casting industry. Tool inserts could be made in-house and enable shorter production runs. Benefits of high pressure die casting could be utilised for parts that are not produced in extremely high volumes. One could envision vertical integration where tool geometry is automatically transferred from the simulation software to the 3D printer. After production, tool inserts would be mounted onto standardised dies and put into casting production. This vision is not achievable in the near future and requires the development of a wide range of different technologies, but gives insights into exciting new possibilities of Foundry 4.0 concepts.
The author can be contacted at ashok. firstname.lastname@example.org
This article has been reprinted with the kind permission of the publishers of the Indian Foundry Journal, vol.69, issue 5, May 2023