How good data will shape the nature of work in metal manufacturing


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Jul 17, 2023

How good data will shape the nature of work in metal manufacturing

Information transparency will drive the Industry 4.0 shop. Images: TRUMPF Change

Information transparency will drive the Industry 4.0 shop. Images: TRUMPF

Change is afoot in the sheet metal industry. Someone entering the business 30 years ago became an expert in the craft after years of experience. Today, a fabricator with modern lasers, punching machines, and press brakes can turn a manufacturing novice into a productive employee extraordinarily quickly.

In fact, the knowledge required to be productive is substantially less than it used to be. Skill still matters in the modern factory, but the learning curve for new employees is shorter. To grow and progress, though, people still need knowledge, but they also need to apply that knowledge in new ways.

As metal fabrication moves toward Industry 4.0, new career paths will lead to new opportunities, especially for those open to change and new ways of thinking—much of it spearheaded by data-driven intelligence within machines and software. Those eager to learn, who look beyond the part they’re forming or the nest they’re cutting, will reap the benefits.

The now decades-long skilled labor shortage has pushed machine and software makers to answer the need with technology that allows the less experienced to produce more and with higher quality than ever before. Traditional knowledge has been "baked into the cake" as software performs the work that tradespeople 30 years ago used to calculate with a pencil and paper.

This shift has changed how people spend their careers. Those starting out on the shop floor 30 years ago likely spent their entire career there. They might have progressed in a single department or moved through various departments, perhaps eventually becoming a department lead or supervisor. Today, sheet metal novices could start as a machine operator but then progress to machine programming or become a CAD/CAM technician. Technology also frees operators from having to specialize in one type of machinery and makes it easier to cross train throughout the shop.

The 3D model helps make such a digitally oriented career path more common than ever. Early in their careers, perhaps even during their first days or weeks on the job, new employees see the 3D models of the parts they’re making. Those 3D representations become imbedded into their working life.

At some shops, new employees won't know what a paper traveler is. A work ticket, dot matrix code, or barcode will be all they need. Part markings will eliminate the need for accompanying paper. And the blueprint, the 3D model, work instructions, basic training materials—they access it all on screen, be it a tablet, laptop, computer terminal, or on the machine control itself. They’ve interacted with software their entire careers, and they know the realities of the shop floor, so moving from the shop floor to the office isn't a giant leap.

The separation between the "office" and "shop" will become less distinct. The 3D model starts in the office, flows through programming and scheduling—where processes are simulated, programmed, and sequenced in an optimal way, foreseeing potential bottlenecks. On the shop floor, frontline employees view screens to see what's next. They’re not shuffling through mountains of paper or firefighting an unexpected bottleneck. They’re doing what customers are paying for: They’re making good parts.

In the old world of fabrication, an operator might start her day going through packets by the jobs staged on pallets near the machine, then look up to see her supervisor walking swiftly toward her. He's spent the past 30 minutes walking frantically between offices and the shop. A customer needs something immediately, and now he's asking the operator to drop everything to make it happen.

So, the firefighting starts. The operator talks with the department lead, waits for the fork truck driver to deliver blanks (maneuvering around all the work-in-process), checks again with her supervisor, then commences bending. For all that time, the press brake ram hasn't moved. She changes out her tooling, performs a few test bends, then—at long last—commences the run. Meanwhile, the collection of WIP-filled pallets by her workstation hasn't diminished.

Instead of paper travelers, all information operators need to know will be available on screen.

In the new Industry 4.0 world of fabrication, the brake operator arrives for her shift, checks the shop dashboard, then views her work schedule on her tablet adjacent to the brake. The first item on the list happens to be a job that a customer changed at the last minute and now needs immediately. No matter—the operator sees it as just the next job on the list. She ensures she has the right tools and commences bending.

Such automated flow of information requires less hands-on management. Intuitive controls, visual cues, and other technologies have made setup easier, so she need not rely on a dedicated setup person. As a new operator today working on modern equipment, she won't spend her days manually calculating bend deductions or developing bend sequences and gauging strategy to ensure she meets the required tolerances. All that intelligence is built into software.

Still, she knows how a radius forms in a V-die and how slight changes in material thickness affect the result. In fact, she sees a process simulation right on her machine controller. She knows how important machine utilization is—and, in fact, can see her machine utilization report right there on screen.

In this new world of fabrication, data is in the driver's seat. Operators work less in the process and more on the process. During production (when they’re working in the process), they see only what they need to run next. They won't need to worry about how much work they have to complete for an entire shift. They will start generating parts, then run what appears next on the screen. At this point, software has optimized job sequences to ensure optimal flow. If a customer requests a change, the software reshuffles the flow.

All this time, the operator continues to make parts. An automated forklift, or AGV, arrives at the work center with a pallet of blanks. The next job appears on the operator's screen, who changes tools as necessary, calls up the program, and commences bending.

In this new world, output at a specific work center—like pounds per hour or pieces per hour—matters less, simply because everyone knows how variable it can be. After all, the cycle time for a single-bend part will be a lot shorter than an eight-bend part. Instead, machine utilization becomes more important than ever—and it's here where operators become true process owners. Sensors track machine utilization automatically. During an end-of-shift huddle or a brief meeting the next morning, operators and team leaders talk about the utilization numbers in context of the jobs run the previous shift. Why was this machine idle longer than expected? Was it waiting for material? Why?

The more automated a fabricator is, the more important utilization figures become to steer production. A 12-kW laser without automation might have low utilization simply because people can't keep the machine fed. If that same laser in an automated setup experiences low utilization, something is amiss. Are we lacking material? Was there an unexpected breakdown?

Regarding those breakdowns, those entering the field today will experience reactive maintenance as a rare occurrence. Thanks to predictive maintenance, machines now can effectively "tell" people they’re getting sick before breaking down entirely. Maintenance technicians interact with machine vendors via smartphone apps. Often, machine vendors reach out as they detect a series of error messages on the controller. The maintenance function is now entirely data-driven.

Imagine new operators stepping on the floor for the first time. They see fellow operators working at a steady pace. They have time for breaks, of course, but when they’re away from their machine, they’re not running around to solve a crisis. They’re studying metrics like machine utilization from the previous day, or perhaps the previous hour, and talking about how the operation could be improved. When they’re not away from the machine, they’re steadily making parts, changing over as needed, and efficiently working through one job after another.

That team of novices begins their training. Many undergo online training classes that help them get up to speed in a virtual environment, learning the basics of blueprint reading but also getting familiar with the 3D model environment. They’re not just passing multiple choice tests, either, but instead become immersed in a digital twin of the operation.

Careers in the Industry 4.0 shop will be varied, but they’ll all share a common thread throughout metal manufacturing: Good data will drive decisions.

With some combination of online and traditional training, they’re making good parts within just a few days or weeks after being hired. Still, the training doesn't stop. Using virtual learning tools, they continue to absorb process fundamentals, and they undergo multiple training sessions over the ensuing weeks and months. They learn about software, but they also learn how different metals react to specific fabrication processes. The training helps new employees embrace metal fabrication fundamentals. They also learn to see software as a tool that helps them make the most of that knowledge to get the job done as efficiently as possible.

These new employees have a multitude of potential career paths in front of them. They could embrace the solid model and work their way up to machine programming, or even move into a CAD/CAM technician or engineering role. Or they could embrace the process and work their way up to operations management, data analytics, or a continuous improvement role. In fact, the Industry 4.0 operation likely will employ more people in some kind of improvement role, analyzing the entire process flow from quote to ship. Most important, they make decisions based on data, not on hunches or just because something is familiar.

Alternatively, employees could work their way up to roles in sales, estimating, or purchasing—though in the world of Industry 4.0, those job functions might be very different from what they are today. Robust data allows the entire operation to produce closer to customer demand, with less WIP between work centers and less raw stock, which in turn reduces the amount of working capital in the shop.

Say a tower at a laser cutting center has 10 sheets of 0.25-in. material. The shop has nested five of those sheets. At the same time, software knows that an incoming order will require eight more sheets. This triggers purchasing into action, which orders material immediately.

Industry 4.0 won't eliminate the need for raw stock, of course. Shops need buffers, as recent supply chain challenges have proved all too well. That said, Industry 4.0 will allow purchasing managers to make decisions that again are based on real data, not a gut feeling.

Those in purchasing focus on that data and work to streamline purchasing arrangements. Those in order processing do the same, sometimes connecting directly to the customer's enterprise resource planning systems. Rather than keying in a pile of purchasing orders manually, transactions occur electronically, no human intervention required.

Those in sales and estimating will focus less on "estimating" a job. In fact, good data will make quoting much more of a science, based on actual machine rates and real material and labor costs. Quoting for prototype and low-quantity orders will also become much more automated, with customers uploading 3D CAD files and receiving quotes shortly thereafter, sometime within minutes or even seconds.

The sales and estimating role will concentrate on the unusual jobs and longer-term contracts. The big difference: Armed with data, they will negotiate based on real capabilities and actual costs.

A common thread connects the career path of the Industry 4.0 shop: the importance of good data and the actionable intelligence derived from it. In many ways, data transparency will help tear down silos.

Order processing is a prime example. Historically, those processing orders would throw them "over the wall" to a scheduler, who shuffled a stack of job travelers, which then were sent to the shop floor. The plant took days or weeks to produce metrics; when they finally were available, they were useless. Problems and the ensuing firefighting had already come and gone. Conversely, in the Industry 4.0 shop, data acts as the grand uniter. Scheduling occurs electronically, and algorithms driving that schedule are perfected over time.

The Industry 4.0 employee sees the whole picture, from the initial quote to the final shipment, and data transparency fosters a culture of improvement along the entire value chain. They might not spend years perfecting the craft of cutting or bending, but they will learn how to use data to make the entire operation more efficient, less stressful, and, ultimately, a better place to work.

Understanding machine utilization becomes even more important at the Industry 4.0 fabricator.