In the evolving landscape of modern manufacturing, the drive towards intelligent production and digital workshops is becoming pervasive across industries, with the foundry sector being no exception. Faced with intensifying market competition, the imperative to reduce costs while simultaneously enhancing product quality has never been greater. The industry is increasingly turning to smart control technologies and information management systems to upgrade both shop-floor equipment and enterprise-level management. Within casting methodologies, lost foam casting stands out for its exceptional performance. This process not only simplifies the overall technique but also yields castings with high dimensional accuracy, excellent surface finish, and a superior yield rate, significantly reducing the need for post-casting machining. However, the lost foam casting pouring process is inherently complex, involving a continuous sequence from molten metal tapping to pouring, pressure holding, and cooling. To effectively manage the operational status of various equipment during this critical phase, continuous measurement, monitoring, and recording of relevant variables are essential. Although many enterprises have deployed automated equipment for pouring systems, a significant gap often exists: individual process stages remain siloed, with production equipment operating independently and lacking effective information exchange. This fragmentation hinders the comprehensive monitoring of multiple device parameters across different工序. Therefore, establishing a robust pouring monitoring system is of paramount importance. It empowers production technicians with real-time oversight and remote management of casting equipment, a crucial step towards improving production efficiency, reducing energy consumption, minimizing operational hazards, and enhancing the overall level of digital integration within the workshop. This article details the design and application of such a monitoring system developed for an automated lost foam casting line.
The core of the automated pouring process in lost foam casting lies in its tightly orchestrated sequence. The process begins with the transfer of a molded flask to the pouring line. Once the next ladle of molten iron is positioned at the pouring station, its unique batch ID is scanned and uploaded to the Manufacturing Execution System (MES). The MES responds with the specific flask numbers and product information eligible for pouring with that particular ladle. Prior to initiating the pour, the temperature of the molten metal is verified. The system then detects the target pouring station and navigates the pouring machine to that precise location. Concurrently, the vacuum system is activated to draw a negative pressure within the flask, bringing it to a predefined setpoint. The pouring operation commences, with simultaneous monitoring of the ladle weight. Upon completion of the pour, the system initiates a pressure-holding cycle according to the product’s specific recipe, allowing the metal to solidify and take shape. Finally, the flask is transferred to a shakeout station for sand removal and casting extraction. This entire workflow is continuous and demands precise synchronization. The production layout typically involves multiple parallel lines to maintain production rhythm and output. For instance, a common configuration might include two molding lines feeding into three dynamic pouring lines and one return line. The three pouring lines operate in a staggered cycle: one line actively pours, another holds pressure and cools, while the third transfers cooled flasks to the return line for shakeout while simultaneously receiving newly molded flasks, creating a continuous, efficient loop.
The architecture of the pouring monitoring system is designed as a multi-tiered, distributed network, ensuring robustness, real-time performance, and scalability. The system can be decomposed into four primary layers: the Supervisory Control and Data Acquisition (SCADA) layer, the Programmable Logic Controller (PLC) control layer, the data acquisition module layer, and the data transmission infrastructure.
The SCADA layer, serving as the operator’s window into the process, is built around MCGS configuration software running on an industrial PC or Human-Machine Interface (HMI). This platform is responsible for the deep-level parsing of equipment status data and processed information collected by the PLCs. It provides real-time graphical visualization, historical data trending, alarm management, and allows for manual setting of operational parameters. Processed commands from this layer are transmitted downstream to the PLC controllers.
The PLC control layer forms the backbone of real-time control. It employs a distributed philosophy, where each major subsystem (e.g., pouring machine control, vacuum system control, conveyor control) is governed by its own dedicated PLC controller. For this application, Siemens S7-1500 series PLCs serve as the central master controllers, while S7-200 SMART PLCs are deployed for individual subsystem control. These controllers execute logic based on sensor inputs and SCADA commands to drive actuators like motors, valves, and cylinders. A key design feature is the peer-to-peer communication between mobile subsystems, such as the pouring machine and stationary line controllers, which is facilitated via a wireless AP Client network architecture to ensure seamless data exchange without restrictive cabling.
The data acquisition module layer is responsible for gathering critical process variables. This includes:
- Molten Metal Weight: Acquired from load cells under the ladle.
- Molten Metal Temperature: Measured using wireless thermocouples.
- Flask/Vacuum Pressure: Monitored via pressure transducers on the vacuum lines.
- Pouring Station & Flask Identification: Achieved using Radio-Frequency Identification (RFID) technology.
- Ladle Batch ID: Captured using industrial barcode scanners.
These signals, whether analog (4-20 mA, 0-10 V) or digital (serial communication, Ethernet), are read by the respective subsystem PLCs.
The data transmission infrastructure is the nervous system of the monitoring system. It is bifurcated into an upper-level information network and a subsystem control network. The upper network utilizes a redundant Gigabit Ethernet backbone with industrial switches, often employing fiber-optic links for noise immunity and long-distance communication between the control room and the shop floor. The subsystem network primarily uses a star topology with wired Ethernet. Crucially, to accommodate mobile equipment like the pouring carriage, robust industrial wireless Access Points (APs) and Clients (in AP Client mode) are deployed to create a stable and fast wireless data channel, ensuring reliable control and data acquisition without the limitations of trailing cables. The network configuration parameters are summarized in the table below.
| Network Segment | Topology | Technology | Key Components | Purpose |
|---|---|---|---|---|
| Upper Management | Redundant Ring | Gigabit Ethernet | Industrial Switches, Fiber Optic Cables | SCADA-PLC data exchange, MES integration |
| Subsystem Control (Fixed) | Star | Ethernet/IP, PROFINET | Managed Switches, Ethernet Cables | Communication between stationary PLCs, HMIs |
| Subsystem Control (Mobile) | Point-to-Multipoint | Industrial Wireless (802.11a/n/ac) | Wireless APs & Clients | Data exchange with mobile pouring machine, AGVs |
The hardware design is meticulously crafted to ensure reliability in the harsh foundry environment. Electrical isolation is paramount for protecting sensitive control electronics from power line disturbances and noise. A three-phase dry-type isolation transformer (380V to 220V) with a capacity of 2000 VA provides clean, isolated power for the entire control system. Power distribution and protection are handled by circuit breakers (e.g., C65N series), while control signal interfacing and amplification are managed by 24V DC power supplies (e.g., LRS-150-24) and intermediate relays (e.g., MY2N).
The subsystem core revolves around the Siemens S7-200 SMART PLC. A typical configuration includes a CPU module (e.g., CPU SR20) for logic execution, signal modules for I/O interfacing (e.g., EM AE08 for 8-channel analog input), and communication modules (e.g., SB CM01 for RS485/RS232). This modular approach allows each subsystem—whether it’s the vacuum pump station, the conveyor drive, or the pouring machine itself—to operate with a degree of autonomy. A failure in one subsystem does not cripple the entire line, enhancing overall system availability.
The data acquisition modules are selected for accuracy and durability. Molten iron weight is measured using a 2-ton-capacity electronic weighbridge with an accuracy of ±2 kg. The weight indicator features an RS232 serial port, communicating with the PLC using a defined protocol (e.g., 9600 baud, 8 data bits, 1 stop bit, no parity). Temperature measurement employs a KZ-300BW wireless pyrometer system, which transmits a 4-20 mA signal proportional to temperature to the PLC’s analog input module, eliminating the need for fragile thermocouple extension cables in high-traffic areas.
A particularly innovative aspect is the use of RFID for flask tracking and pouring station positioning. In the challenging environment of a lost foam casting shop—filled with dust, vibration, and electromagnetic interference—traditional optical or ultrasonic positioning methods often falter. Ultra-high frequency (UHF) RFID tags are mounted at known grid points along the pouring line (e.g., every 150 mm on X and Y axes). An industrial UHF RFID reader on the pouring machine, triggered by a proximity sensor, reads these tags as it traverses the line. The decoded X/Y coordinates are transmitted to the PLC, which calculates the machine’s precise position and identifies the target flask’s location. The hardware specifications for this subsystem are critical for reliability.
| Component | Model/Specification | Key Feature | Role in System |
|---|---|---|---|
| RFID Reader | SG-UR-I81 (UHF) | IP67, RS485 Modbus RTU | Reads position tags, communicates with PLC |
| RFID Tag | SG-UT-405MT (UHF) | High-Temperature Resistant | Passive tag providing unique location ID |
| Barcode Scanner | Honeywell 1902GSR | Wireless 2D Imager | Scans ladle batch ID, sends to MES |
| Wireless AP/Client | Moxa AWK-3131A-EU | Dual-band, Industrial Grade | Provides network connectivity for mobile pouring machine |
The software design is bifurcated into low-level PLC control logic and high-level SCADA application development, both integral to the lost foam casting monitoring system.
The PLC programming, accomplished using Siemens STEP 7-Micro/WIN SMART and TIA Portal software, follows a structured, modular methodology. This is essential for creating flexible, maintainable, and fault-tolerant code that can adapt to dynamic production changes. The program for the pouring machine master PLC exemplifies this. It continuously polls for the machine’s real-time position and travel direction, converting raw sensor data (from RFID and encoders) into a graphical coordinate for the HMI. Critical interlock logic prevents operational errors: for instance, the system ensures only one pouring line’s vacuum sealing cylinders are raised at a time to prevent collisions with moving flasks on adjacent lines. Flask sequencing is constantly validated via RFID reads at line entrances; a sequence error triggers an immediate alarm, prompting manual intervention via the HMI.
Specific functional blocks handle critical tasks. The weight acquisition routine uses the PLC’s Freeport mode to configure the serial port for communication with the weighbridge, parsing the incoming data string to extract the current ladle weight. This weight value, $W_{current}$, is used in a simple control algorithm to determine pouring stop point. If the target weight for a casting is $W_{target}$, a pre-defined stop offset $W_{offset}$ is applied to account for the inertia of the flowing stream, improving yield and speed. The stop condition is:
$$ W_{current} \leq (W_{initial} – W_{target} + W_{offset}) $$
where $W_{initial}$ is the ladle weight at the start of the pour.
The RFID communication is implemented using the Modbus RTU protocol, with the PLC as the master. The `MBUS_MSG` instruction block is used to send read requests to the RFID reader’s Modbus address. The received position data is then processed and mapped. To prevent data loss during unexpected power outages, critical variables like current flask sequence numbers and machine position are declared as retentive and stored in non-volatile memory.
The SCADA application is developed using MCGS Pro configuration software, chosen for its powerful graphical capabilities, database management, and seamless driver support for Siemens PLCs. The development involves several key steps: device driver configuration (to establish communication with the S7-1500 PLC via Ethernet), real-time database definition (to create tags for every monitored and controlled variable), and sophisticated user interface design.
The HMI is the central dashboard for operators. The main monitoring screen provides a holistic, animated overview of the entire lost foam casting line. Dynamic graphical elements represent physical equipment: the pouring machine icon moves along a track corresponding to its real-world position; flasks are color-coded to indicate their status (e.g., waiting, pouring, pressure-holding, cooling, ready for shakeout). Real-time data is displayed prominently: ladle weight, molten iron temperature, vacuum pressure, and current batch information. Control widgets allow operators to start/stop the vacuum system, initiate manual overrides, and scan ladle batch IDs. The interface employs a tabbed structure for accessing specialized screens without clutter.
| HMI Screen | Primary Function | Key Visual Elements & Data |
|---|---|---|
| Main Monitoring | Overall process overview & control | Animated line layout, dynamic flask colors, real-time weight/temp/vacuum, control buttons. |
| Sequencing Window | Flask tracking & manual sequence management | List of all flasks in line with status, manual update buttons for error correction. |
| Alarm History | Event logging and diagnostic | Chronological list of alarms with timestamp, description, and value. |
| Parameter Setting | Recipe management | Forms to input/change pouring parameters, pressure setpoints, timers. |
| Trend View | Historical data analysis | Graphical plots of key variables (temp, pressure) over selected time periods. |
Alarm management is a critical subsystem within the SCADA. Events such as low molten iron temperature, vacuum pressure deviation, sequence faults, or communication timeouts are configured with specific priority levels. When triggered, these alarms activate visual and audible indicators on the HMI, log an entry with a timestamp to a database, and can be configured to send email or text notifications to maintenance personnel. This proactive monitoring is vital for preventing quality defects and unplanned downtime in lost foam casting.
The system has been deployed in a production lost foam casting workshop specializing in heavy-duty components like transmission housings. The operational results demonstrate significant improvements across multiple metrics.
Process Monitoring and Efficiency: The system provides comprehensive surveillance of pouring parameters. For a typical component like a 100 kg transmission housing (Part No. 186856-15C), the system enforces and monitors the optimal process window:
- Vacuum Pressure: -43.3 kPa
- Pouring Start Temperature: 1450 – 1500 °C
- Average Pouring Time per Casting: < 35 seconds
- Pressure-Holding Time: 6 minutes
Compared to traditional manual ladle pouring, the automated system guided by this monitor has drastically reduced labor intensity and associated safety risks. More importantly, it has optimized the pouring rhythm. By precisely controlling the stop point using the weight-based algorithm, the system minimizes “over-pour” waste and reduces the time the ladle is open, conserving heat. For a standard ladle, the cumulative time saving across all castings poured from it can reach up to 180 seconds, directly increasing throughput.
RFID Positioning System Performance: Extensive testing was conducted to validate the RFID-based positioning system. After parameter optimization (FCC band 902-928 MHz, reader power 18 dBm, read distance 150-200 mm), the system underwent a rigorous 7-day production trial. The accuracy was measured by comparing the system-identified flask/stposition with the known physical location. The results were exceptional, as summarized below:
| Test Metric | Result | Implication |
|---|---|---|
| Read/Write Cycles | 4,000 – 8,000 per tag | High durability for production environment. |
| Positioning Accuracy Rate | 100% | Flawless identification of target pouring stations. |
| Fault Alarms Generated | 0 (related to misreads) | Extreme reliability; no false sequencing alarms. |
The system successfully identified every flask at every station without error, proving its robustness against the environmental challenges of the lost foam casting process.
Network Communication Quality: The stability of the wireless link for the mobile pouring machine is crucial. Network diagnostics were run using packet analysis tools between the central monitoring host and the HMI on the pouring machine at its farthest point from the wireless AP. The test results confirmed the network’s suitability for real-time control:
- Packets: Sent = 6,226, Received = 6,226, Loss = 0%.
- Round-Trip Time (ms): Minimum = 1, Maximum = 233, Average = 3.
The negligible packet loss and low average latency ensure that control commands and data updates are transmitted reliably, making the wireless link virtually indistinguishable from a wired connection for this application.
Data Integration and Broader Impact: Beyond real-time control, all production data—including pour times, temperatures, weights, and alarm events—is timestamped and stored in the MCGS historical database. This data is also synchronized with the plant’s MES, providing a complete digital thread for each casting. This enables traceability, production analysis, and lays the groundwork for deeper quality analytics and predictive maintenance, moving the lost foam casting operation closer to full-fledged Industry 4.0 standards.
In conclusion, the designed and implemented monitoring system for automated lost foam casting represents a significant technological advancement for foundry operations. By integrating robust PLC-based distributed control with a powerful, user-friendly SCADA interface, the system achieves centralized supervision, precise control, and effective management of the entire pouring line. The innovative use of wireless networking for mobile equipment and RFID for precise positioning solves critical challenges in the automation of lost foam casting. The results from production deployment confirm the system’s success in meeting core objectives: it enhances production efficiency through optimized cycle times and reduced waste, improves workplace safety by reducing manual intervention, and substantially raises the level of workshop digitalization and information integration. This system provides a practical and effective blueprint for the digital transformation of casting workshops, demonstrating a clear path towards smarter, more efficient, and more competitive manufacturing in the realm of lost foam casting.