EFFICIENT AUTOMATION FOR DATA-DRIVEN FOUNDRIES
Many foundry lines still operate almost completely manually. If operators make even the smallest errors in timing or machine settings, scrap increases, production slows or the line stops altogether.
To maximize casting quality, output and uptime, foundries are increasingly implementing data-driven process automation. By seamlessly interfacing the automated systems handling moulding, pouring, cooling and shakeout to each other – known as machine-to-machine (M2M) integration – the casting process becomes faster and consistently produces higher quality components.
Automating some or all of a process helps get the most out of investments like fast moulding machines and the data gathered builds a digital picture of operations. Comprehensive M2M integration also requires fewer experienced operators with years of specialist experience. With fewer workers involved overall, operations become safer too.
Automating different parts of the line
A green sand line mostly just needs supervision during steady production. But following pattern changes or other stoppages, manual input is required. With just-in-time production now the norm, foundries have to cope with more, much shorter runs these days.
Pattern changing itself used to be the bottleneck but equipment like DISA’s Automatic Pattern Changer (APC) can change plates in as little as one minute. That doesn’t leave much time to set up the rest of the line for new moulds and castings. This is where automation and synchronization come into their own.
Automating mould transport to control in-mould cooling time following pouring is a good example and is probably the most widely used M2M application seen today.
After a pattern change or other stoppage, poured castings will have cooled more than usual so the line can run faster for a while, perhaps at the maximum speed of the moulding machine. Go too slow and you are wasting time but, if you run too fast, you risk sending castings into shakeout and cleaning while they are still too hot. In fact, it’s almost impossible to manually set the ideal line speed required to maximize production after a halt. A line speed far below optimum is the only safe manual option.
But if the system controller knows where each mould is to a fraction of an inch, how long production has stopped and all the other relevant parameters, it can easily calculate how fast the moulding machine and transport can run after a stoppage – and then exactly when to slow down again so the moulds poured post-stoppage have enough time to cool before shake-out.
Shakeout and casting cooling
After a pattern change, the operator has to move from the moulding machine down to the shakeout control unit, manually change to the new settings once the first new castings start appearing, then go all the way back to the moulding machine.
With automation, the shakeout table or vibration conveyer control system (PLC) “knows” to change its settings right when the first new mould reaches it after a pattern change. For a vibration conveyer, that mean each casting type gets exactly the right speed and vibration frequency it needs. Manually set the frequency too low and they can pile up and cause stoppages.
The same applies to sand and casting cooling automation. Run manually, the operator has to move to the end of the line, choose the settings – water dosage, cooling time – and apply them at the right moment. Too little water and the castings are too hot, operators can’t remove gating systems after shakeout and the castings get damaged during shotblasting. Too much water creates a pile of mud in the drum and the line has to stop while someone shovels it clear.
With automation, the cooling drum’s sand/iron/water ratio and cooling time for each casting – the “recipe” – is defined once in the database and set correctly every time that casting is produced. Once again, that changeover occurs just as the first new casting reaches the drum.
Sorting before shakeout
Automation’s built-in mould tracking also knows where any groups of bad moulds are on the line. Conventionally, if metal testing shows a bad magnesium treatment, many perfectly good castings have to be discarded to avoid shipping scrap to customers. That’s because they look identical to good castings and operators only have a vague idea of where the bad batch starts and finishes on the line. In fact, it’s common to isolate two batches before and two batches after a bad batch.
With digitalization, operators can mark those moulds as bad in the system, then make sure to sort them out before they are mixed up in shakeout. That might be as simple as a red/green light that tells manual sorters when to remove bad castings but sorting can be completely automated too. That way, when the first bad mould arrives, the central system triggers a robot arm or other device at end of the cooling transport to start isolating them.
The same can be done with other bad moulds, perhaps one with a wrongly set core. The operator can immediately mark it as bad at the moulding machine, knowing it will be safely sorted out before shakeout.
Pouring – the acme of automation
To keep pace with the high speed of vertical moulding, more foundries have adopted automated pouring along with techniques like double index pouring (pouring two moulds simultaneously). Automated pattern changes further increase efficiency, but then the bottleneck often becomes manually repositioning the pouring device after a pattern change.
Fully synchronizing pouring and moulding – seamless pouring – is the answer and is particularly valuable for foundries challenged by multiple shorter runs. Coordinating both functions in all possible situations requires deep M2M integration and, again, the key is knowing exactly where each mould is all the time. That lets the pouring unit calculate where and when to pour the next mould and, if required, adjust the pouring device’s position to suit.
During steady production, that’s relatively simple. The mould string moves forward by the same distance after each pour – the mould thickness – and the pouring device stays in the same position. Compensating for any minor variation in mould thickness requires only small adjustments.
But for vertical moulding, when the pattern changes, so does mould thickness. That’s because the DISAMATIC process varies mould thickness to keep the sand-to-iron ratio constant and take pattern heights into account. That enhances quality and minimizes resource consumption but, after a pattern change, the moulding line will be producing one mould thickness while the pouring unit is filling another.
During the transition period, the automated system must adjust the pouring position each time it pours the remaining moulds from the previous pattern. If the new moulds are thicker, the moulding machine will occasionally have to wait while two moulds are poured. If the new moulds are thinner, the pouring unit must also be able to skip pouring for one moulding cycle.
Seamless pouring at Ortrander
Germany foundry Ortrander Eisenhütte operates three DISA moulding lines, producing around 100 tons of castings daily in short runs of one hour or sometimes even less. It changes patterns frequently.
Ortrander found manually positioning the pouring device and pouring moulds was too slow, required more operators and was prone to errors like overpours. Its staff eventually became tired, lost concentration and made mistakes like adding slack. Now its furnaces, moulding lines and pouring are all digitally controlled and synchronized, running almost completely automatically.
Following a pattern change, the pourTECH pouring controller calculates where to position the pouring device based on data from the CIM system. It knows exactly when the first new mould reaches the pouring device and automatically switches to the new pouring sequence. If the pouring device ever reaches the end of its travel, the moulding machine pauses while the pouring device repositions itself – all automatically.
Changeover time has dropped from 4.5 minutes to under two. With between eight and 12 pattern changes, pattern changing occupies around 30 minutes per shift – less than half the time pre-automation.
Seamless pouring’s extra consistency plus more ability to optimize the process has cut scrap by 20%. Only two people run the whole line instead of the previous three; during some shifts, three people operate two lines. Besides monitoring, all they do is select the next pattern, manage sand mixing and transport melt.
Although operators do require some training for automation, the extra process information it supplies aids correct decisionmaking, so fewer experienced staff are needed. In future, the machine may make all the decisions itself.
The data dividend
Synchronizing automated moulding with other sub-processes like pouring, cooling and shakeout delivers a faster process with lower scrap. Add automatic pattern changes and the line effectively runs itself with minimal manual input.
Each foundry will need a slightly different tailored solution but the technology is well proven. First launched in the 1990s and constantly updated ever since, Monitizer | CIM is already implemented in some form by around half of DISA customers. The M2M integrations described here, including seamless pouring, are currently operational in multiple global locations and are well within the reach of all modern foundries.
As well as functions like recipe management and process alarms, digitalization also provides an Industry 4.0-compliant foundation for data collection, storage, reporting and analytics. Ortrander collects around a thousand parameters for every mould it pours. Foundry management can view detailed reports and drill down into the data, helping to reveal the root causes of complex, interlinked casting problems.
If surface inclusions appear in castings, supervisors can immediately check for out-of-tolerance parameters. Or they can gauge how pouring level and temperature affect mould filling for each individual pattern.
The process database is also the starting point for automated analytics like machine learning and AI. AI-driven full process optimization is proven to radically improve performance; multiple foundries have reported scrap reductions of 40% or more using the Monitizer | PRESCRIBE service.
In the past, a foundry’s biggest assets were its patterns and the experience of its workforce. Now, with wider automation allied to Industry 4.0 systems, digital is rapidly becoming the third pillar of casting success.