The future of software in precision sheet metal fabrication
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Precision sheet metal fabricators make their own product, offer subcontracting services for others, or do a little of both. Some operations specialize in specific markets, like aerospace, medical, or automotive, and they offer the traceability and deliver the quality standards those markets require. Other operations might have multiple plants and even international operations, which together offer a seamless customer experience.
All this said, when you get to the primary services sheet metal companies offer, the differentiation starts to fade, and it starts with the primary cutting operation. The reality of laser cutting is that it has largely become a commodity service. Sure, some machines might have a large bed for extremely large parts, and some specialty machines can produce extremely small parts. Some operations offer other processes like tube cutting or the ability to process difficult materials with waterjet cutting or other methods.
But when it comes to most cutting operations, customers simply assume a fabricator will perform them to an acceptable quality standard. The real differences are in the security and traceability of supply, quality of service, delivery, and, of course, cost.
Subcontracting is fast moving by nature. Delivery times are short. One or two days isn’t unusual for some operations, especially those that produce prototypes or ship very small lot sizes. And herein lies the fundamental challenge of the modern precision sheet metal operation: the sheer variety of work flowing through the company at any given moment. A plant might have a few high-quantity orders mixed with a “long tail” of low-quantity jobs, each with unique demand characteristics. Some customers might order predictably, others sporadically. Some might require design assistance. Others submit drawings that might have varying levels of manufacturability issues. Some companies are open to design changes, and others aren’t.
Handling all this variety efficiently and cost-effectively is extraordinarily difficult. Some quotes go unanswered. Some opportunities are ignored or overlooked, simply because the operation is buried in the day to day. Everyone is just trying to keep their heads above water. Then, when jobs are released to the floor, information might be missing.
Whether it’s work-in-process (WIP) inventory in the shop or an unanswered email buried within someone’s inbox, jobs spend most of their journey through a precision sheet metal operation waiting for someone’s attention—and it’s here that software is having its greatest impact.
Considering the hundreds of jobs that a typical precision fabricator handles, generating enough quotations to maintain the desired workload can be a major headache. Here, automated quoting systems can help reduce the skills and hours normally required. Not only does this type of software cut down on the response time, but it also frees skilled people to tackle other production and management tasks.
Most inquiries today come in the form of CAD files, and the ability to import and, most crucially, automatically analyze processes required is essential. So is the ability to offer reliable delivery dates. This requires knowledge of the human and machine resources around the factory and the loading at any point. Planning can go right down to the trucks shipping parts to the customer.
Again, it’s about knowledge—knowing what an operation is producing now and (especially critical when quoting) what it could produce in the future. Consider the knowledge gained with a manufacturing execution system (MES) and live monitoring of what’s happening in the workshop. The operation has a complete view of raw material stocks, their costs, and delivery times, as well as the cost and delivery times for outsourced operations like powder coating. The MES is tracking manual operations like welding and automated processes like laser cutting, as well as all the exceptions and problems, like machine breakdowns and excessive scrap.
Software also can monitor the effectiveness of programming and nesting. How does the operation manage and utilize remnants? What about combining jobs from multiple customers on the same sheet of material? How does part placement affect job stability and ease of part removal?
Automation has become an essential part of any workshop. The technology can keep machines running and changing over automatically. Flexible manufacturing is a reality, and software here plays a central role, controlling the automation devices, monitoring their effectiveness, and highlighting areas for improvement.
Modern machinery can feed data automatically to software, and for manual operations, operators can feed data back with tablets or similar devices. In either case, such feedback gives live information to managers monitoring production as well as sales engineers promising delivery dates. Equipment on the market also can upgrade older machines for data collection.
Of course, data that’s automatically collected needs to be relevant. Excessive quantities of data can lead to data management problems. Also, the data needs to support requirements for downstream capacity like bending and welding. Usage data also can be immensely valuable for calculating the return on investment for future purchases.
Most sheet metal plants are high-product-mix operations and, as such, require metrics that take such product mixes into account. For instance, when it comes to capacity and utilization, overall equipment effectiveness (OEE) indicators can be valuable, but they must be analyzed in a way so that no hidden factor is misinterpreted.
For instance, the OEE quality indicator shouldn’t be analyzed as a simple percentage across the entire product mix. This has to do with highly variable material costs. A few scrapped parts of very expensive material could have a high impact on profitability.
When it comes to the availability metric in OEE, a certain amount of idle time in sheet metal operations isn’t always bad. It depends on the needs of the customer mix. A subcontractor might be reserving some capacity to ensure it can react to urgent (and highly profitable) orders, which is good for business.
On the other hand, a machine might be down because of a constraint upstream stemming from an unexpectedly challenging changeover. That downtime isn’t good, but the data needs to be interpreted correctly. Waiting for that delayed job upstream, the work center shouldn’t necessarily tackle other jobs that are ready but not required to run. In other words, the machine shouldn’t produce more just because it can, especially if it will add unnecessary WIP or make a downstream bottleneck worse.
The way to move forward is to achieve efficiency and balance of all processes from accurately collected data. This considers the cost of WIP, the cost of running machines and operations, how changes affect the cost of production, achieved delivery times, as well as each job’s profitability. Retrieving and analyzing data is complex work, requiring a cross-functional analysis. A single machine with stellar uptime doesn’t make a business more successful. Cutting data affects bending data, which affects powder coating, welding, and assembly. All this complexity makes automated data collection and analysis even more important—hence, again, the importance of software.
Subcontractors have four main objectives: maintaining a flow of new work, optimizing equipment utilization for the mix of jobs on the floor, ensuring that every job reaches the desired profitability level, and delivering jobs on time. Changes in one area affect the other three. Small shops might be able to analyze such data manually, but for companies with multiple machines and sites, analysis and effective utilization of all this information is virtually impossible.
Regarding profitability, material utilization does play a role. Still, precision sheet metal shops perform an extraordinarily complex balancing act every day, weighing the benefits of high material yield (by releasing filler-part jobs as well as more jobs further out into the schedule) against the challenges of excess WIP. There’s no magic strategy here as each business and situation requires a different approach. Broadly speaking, operations can use one of two approaches: (1) nesting kits of parts for specific jobs or (2) filling a sheet with a mixture of parts. When operations nest kits of parts, they create less WIP and require less floor space to store parts for the next stage of production. This strategy can work well when parts are very large or otherwise not easily stored. It also works when customer due dates are predictable, so planners can release orders at the optimal time for jobs to flow quickly from cutting all the way downstream to assembly and shipping.
All this said, filling sheets with a mixture of parts from various jobs also has its benefits. This strategy leaves fewer sheet remnants to manage and usually produces higher machine and material utilization. Operations can make stock parts to fill a sheet, which can facilitate quick response for repeatedly ordered jobs. It also allows an operation to rapidly shift gears in production to meet changes in customer demand.
All this agility comes at price, though, mostly paid for in WIP. Shops will need more storage space for parts, and they’ll need to devote resources to tracking and identifying all the parts on the shop floor and in inventory.
Having the right software tools gives an operation flexibility; that is, it's not forced to use just one approach or the other. Such tools also offer visibility and traceability throughout the business. Storing raw stock and WIP still requires space, but with the right software, such inventory might not require many resources to manage.
In fact, if software gives businesses good visibility about certain materials—including exactly what and how much is available and how quickly and cost-effectively more can be acquired—a plant can achieve the best nesting efficiency while meeting delivery deadlines. Software tracking remnants avoids operators spending time trying to manage them and gives programmers the flexibility to use those remnants for future nests.
A good filler part strategy does require some demand forecast visibility. But with software tracking those parts and where they’re stored, they can be linked to incoming sales orders. A customer pulling a trigger on an order immediately triggers filler-part inventory to be pulled from a specific location—no more needlessly recutting parts after a failed hunt through unorganized parts inventory.
So many challenges in the precision sheet metal business stem from all the unknowns that remain just after winning a bid. We’ve won the order. That’s great. Now what?
Challenges emerge right from the start with the type and quality of the digital file received from the customer. Sometimes shops need to work with PDFs of scanned prints; other times they receive poor-quality DXFs. Even written instructions the customer provides can be inaccurate or misleading. This is where the lack of skilled people in quoting and estimating can snowball into some major delays. A sheet metal shop might lack the engineering expertise and skills, usually gained after years in the industry, to extract relevant information for production.
A digitized sheet metal quotation workflow aims to address these problems. Precise communication with customers remains as important as ever. Still, today’s CAD systems focus on design for manufacturability, and information-rich 3D CAD has gradually become the new standard.
Moreover, quotation systems have become more advanced by incorporating features traditionally restricted to the engineering world. These advanced features can simulate a real production environment.
Driven by design optimization engines aided by AI, today’s quoting software can perform automatic feasibility checks. This can include implementing limitation logic so that a customer simply cannot order a part that’s impossible to make, as well as spotting problems or potential problems with a part—holes too close to an edge, folds across holes (causing distortion), and conflicting dimensions.
Other features can include 3D unfolding engines that incorporate tooling that’s actually used on the shop floor, drawing from a database that accounts for varying forming characteristics of different materials and thicknesses. This in turn determines the correct blank size, which is fed into advanced nesting engines.
Future enhancements might include traceability of design to pinpoint where an error occurred and, through AI optimization, develop ways to prevent that error from happening again.
Looking further out into the future, the industry could see software advancements that—again, using AI and information gleaned from machine learning—can simulate the entire factory. Software could flag what operations will need human intervention and even be integrated with systems from suppliers and outside service providers. Is enough material available? Will an outside powder coating provider have trouble masking a certain feature? In the future, an integrated quoting platform could answer these questions and more. All this could reduce the chance of error before any cutting, bending, or welding starts.
The goal is to mitigate the skills gap by letting software—powered by AI and machine learning—complete the mundane tasks. All this minimizes the chance of surprise during order execution and manufacturing, freeing skilled people to work on overall workflow, customer service, project management, personnel development, as well as top-line and bottom-line growth.
Put another way, future innovations in precision sheet metal software should allow more people to work on the business, not in the business.