Fabricating automation requires both robust machinery and intelligent software
November 1, 2010
Automating metal fabrication requires more than just high-speed processing. The actual equipment—the brawn—is only half the equation. The other half is the software—the brains of shop automation.
A production manager rushes into his boss’s office holding an e-mail printout from a customer, who’s wondering where his parts are. It turns out the shop fabricated some, but not all, of the parts the customer requested.
Or perhaps the customer submitted design changes that never made it to the shop floor, and he’s calling to ask why he now has bins of parts based on outdated drawings.
Or the customer’s latest revisions have bad drawings with open geometries and other inconsistencies, and hence require unplanned hours at the engineer’s desk—hours the customer isn’t paying for.
Or maybe the customer submitted an order but canceled last-minute, but news of this never got to production, which means the customer has a batch of parts he doesn’t want on his doorstep—and he’s not about to pay for them.
These and other headaches have become all too common. In this post-Great Recession world, customers are wary to let go of cash or build up significant inventory, so they wait until the last possible moment to submit an order, and expect parts back within days. On top of this, they may change the design, volume, and other variables up to the last moment before production.
To help matters, fabrication shop managers have turned to automation. And nowhere is automation more visually obvious in contract metal fabrication than the primary cutting operation. Those machines feed everything else in the shop; any cutting bottleneck affects everything else downstream. So it’s no surprise shop owners look to automated material handling towers, offload tables, and the like to shorten lead-time and make part flow as lean as possible.
But the machines themselves—the “brawn” of automation—are only half the equation. The other half—the “brains”—includes software integrated with machine and production control, all focused to streamline the handling of customer information.
Automated machinery and lightning-fast manufacturing time don’t count for much if customers receive incorrect parts. A shop may have to juggle numerous small orders and revisions and deal with last-minute changes or even cancellations. This has made the efficient, accurate handling of customer information more challenging than ever.
Machinery is vital, too, of course. Short lead-times can be just as difficult to achieve if an operator spends his days pushing buttons on an overhead crane to load sheet while an expensive mass of iron with high-speed drives and advanced laser optics sits idle. The point is that the most effective implementation of automation involves both the brains and the brawn—the machines and intelligent software. Remove either, and a shop significantly reduces its return on a major technology investment.
Machines and material handling systems make up the traditional heart of automation. People take one look at them in action and immediately see the benefits. But integrating a system requires careful analysis.
Attaching a material handling system to a laser machine not designed for automation often isn’t the best solution. In fact, such patchwork machine integration can have dire consequences. To run unattended, a laser system must have integrated safety systems. If a system is programmed to run different materials, there’s a small chance that the exhaust bellows can catch fire, which can be catastrophic—especially if no one is in the plant. Machines designed for unattended operation have real-time monitoring systems to prevent such events.
All elements of an automated system should be able to handle similar materials (see Figure 1). A laser system capable of cutting 1-in. carbon steel may not be utilized as much as it could be if it’s attached to a material handling system capable of carrying stock up to only 0.625 in. thick.
Towers can hold thousands of pounds of raw stock per shelf (see Figure 2). The towers help shops manage raw stock; at any given time, the automated system controller shows exactly what raw stock is where, eliminating that all-too-familiar material hunt. If a rush job comes in, the production manager knows exactly where the needed material resides and so can immediately trigger the job into action. The material is carried to load/unload tables, which enable job changeover times to be measured not in minutes but in seconds.
Towers can be integrated with multiple lasers, and modular systems can be designed to grow laser automation with the business. A shop may invest in a single tower-laser system, but know that one day it may add more laser machines to increase capacity and, depending on the laser power in those new systems, be able to handle a greater variety of material types and thicknesses.
Such towers can shorten the time it takes to ready a new job for production, but by themselves they may not necessarily make life easier for workers on the floor. No matter how efficient and flexible cutting systems are, they create headaches if they just flood the floor with work-in-process (WIP).
Workers may scurry to organize cut parts and move them to the appropriate downstream operations, which are likely to be less efficient than the primary cutting center. It takes a few seconds to cut a flat part, but it may take several minutes to bend it. Balancing production like this isn’t easy. The part flow can become even more challenging if one sheet has cut parts for multiple jobs requiring different secondary operations.
Part flow is a balancing act. Grouping like jobs together can increase material utilization and beam-on time (fewer lens changeouts, etc.), but sometimes can cause excess WIP if those like jobs have disparate due dates. This is where an often-overlooked area of cutting automaton can help: strategic cut-parts storage.
Some companies prefer to store cut parts in the tower. The system controller knows exactly where those parts are, and parts can be pulled as downstream processes need them. This does, however, limit the tower’s storage capacity.
Another method involves a kind of pass-through system using a series of offload tables. As with anything else in automation, offload table capacity should be balanced with other elements in the system (see Figure 3). Say a shop has a 20-shelf tower capable of holding 120,000 pounds of material, with one offload table capable of holding only 4,000 lbs. The shop probably can run for two and a half hours before someone has to remove finished parts. While this may be OK for a first or second shift, it certainly isn’t adequate for running unattended overnight or over the weekend (see Figure 4).
Time studies help determine the offload table capacity needed. If a shop processes 1,000 lbs. of metal an hour, a 4,000-lb.-capacity offload table will take four hours to fill. Adding another offload table may provide enough to run over an eight-hour shift; several more may be enough to run unattended over a significant part of a weekend.
Such a system allows a shop to manage WIP and part flow better while maximizing material utilization. Of course it doesn’t give the cutting center permission to flood the floor with work, but it does allow fabricators to present just enough parts to downstream operations at the right time, while still maximizing beam-on time and material utilization, leaving only sparse skeletons to scrap. And it can allow for an efficient (though carefully monitored and limited) buffer to hedge against unforeseen events.
Ensuring parts are manufactured and sorted on the correct offload table at the right time isn’t easy. This is where the other half of the automation equation comes into play: the brain.
Production meetings at job shops cover some seriously complex problems. Personnel may review a list of, say, 24 orders requiring six different materials, with assemblies that may consist of multiple components, each with different secondary processing requirements. After cutting, some may need to be deburred, some need to be bent; while other flat parts are just sent directly to powder coating, assembly, or directly to packaging. And all these parts must be processed over the next two shifts. But production management has gotten very good over the years. They carefully schedule work so that everything arrives at the right process at the correct time.
Then, the laser operator doesn’t show up for work, a rush job comes in that morning—and all that detailed production planning just goes out the window. The scrambling begins. Where’s the laser material? Where’s the laser lens for this new material? Is the lens condition good enough to cut this job? Is there a part that needs to be replaced? Firefighting ensues, and hours or even an entire shift of cutting time may be lost.
Communicating customer information arguably has become the most challenging aspect of running the modern job shop awash in a great variety of short-run orders. The most high-powered laser and efficient material handling system don’t count for much if both machines and people can’t access the information they need. Machines need the correct program with the latest part revisions, while people need to know the current schedule status as well as machine performance data, so they know when to schedule maintenance.
Laser cutting machines will cut only the program files they’re given. They don’t know whether or not the program is based on the correct part drawing revision; they just follow instructions and don’t ask questions.
In a sense, though, software does ask questions, at least in the algorithmic sense. Software algorithms sort job priority by due date, determine most efficient nesting, and communicate with existing enterprise resource planning (ERP) and material resource planning (MRP) software to juggle various jobs. The goal is to reduce manufacturing time and meet or beat quality requirements and due dates.
The goal also is to reduce shop floor decision-making. Once a job goes into production, all variables should be thought out and accounted for. The time a shop floor worker spends juggling schedules could be viewed as lost manufacturing time.
Once the job hits the floor, it’s off to the races. Workers focus primarily on throughput and quality, with one eye on part edge quality and another eye on the next job coming in the queue. When an operator pulls up the next job, he should see a nest that goes by a job schedule that may have been updated only minutes before. The operator should be given a heads-up about any change in the next job, so he can ensure the correct material is fed to the correct machine (or in a stand-alone system, he can retrieve the material ahead of time to minimize downtime between jobs).
If a hot job comes in the door, the software looks at the existing schedule in the MRP or ERP system and determines which parts need to be produced when. It then pulls the part files; cleans them up by eliminating open geometries and so forth; nests them; and then fits the parts into the next available sheet, shuffling other components as necessary. All decisions the software makes correlates the due date with material utilization and shop capacity, and all of it happens in real time.
This happens only if everyone is on the same page in the front office. Administrators as well as salespeople may type in orders. Engineering may prepare drawings for manufacturing and work with the customer on some design-for-manufacturability issues. That information can affect material requirements and the production schedule. And all these variations may affect the company’s books and cash flow, so finance needs to be in the loop as well (see Figure 5).
ERP and production management and nesting software serve as a kind of communication hub and resource for all shop information, accessible within the shop and remotely over the Internet. An administrator may start to enter an order but then see immediately that a salesperson already did—eliminating duplicative efforts. The more comprehensive and transparent the flow of information is, the smoother actual manufacturing becomes.
There remains a direct and intimate connection between automated equipment and production management software, and this link involves more than just part programs and nesting. Today certain systems offer closed-loop control feedback that helps a shop’s maintenance effort.
Software supports shop maintenance in both a preventive and predictive fashion. It may send reminders about scheduled tasks and needed parts, so parts can be ordered and be at the ready for the scheduled maintenance. Such systems also can even order those parts; the system sends an e-mail to a manager who, with one click, sends a purchase order to parts suppliers.
Modern systems also aid predictive maintenance. Several hundred sensors placed throughout an automated cutting system send back real-time data that maintenance personnel can act upon. For instance, if a laser is experiencing an overcurrent situation that could lead to machine failure, the sensors would detect this so that the situation can be addressed before a failure occurs.
Better maintenance makes any operation more reliable and predictable. It also may allow managers to reduce WIP buffers, which in turn reduces overall inventory and—most important these days—frees up cash on the balance sheet.
Let’s be honest. Customers probably don’t care how automated your shop floor is; they care about receiving quality parts on time. They also care about how flexible a supplier is to changing demands. Software allows managers to take calls from customers and, after a few clicks on the computer, tell them the job status and, if needed, make last-minute changes.
In the post-credit-crisis world, the days of long order backlogs may be behind us. Successful shops have adapted by being able to react immediately to customers’ ever-changing demands. Today’s automated systems, if integrated properly, should help a fabrication shop do just that.