How sheet metal shops profit from laser cutting

       Pricing based on laser cutting time alone can lead to production orders, but can also be a loss-making operation, especially when the sheet metal manufacturer’s margins are low.
        When it comes to supply in the machine tool industry, we usually talk about the productivity of machine tools. How fast does nitrogen cut steel half an inch? How long does a piercing take? Acceleration rate? Let’s do a time study and see what the execution time looks like! While these are great starting points, are they really variables we need to consider when thinking about the success formula?
        Uptime is fundamental to building a good laser business, but we need to think about more than just how long it takes to cut down on work. An offer based solely on time reduction can break your heart, especially if the profit is small.
        To uncover any potential hidden costs in laser cutting, we need to look at labor usage, machine uptime, consistency in lead time and part quality, any potential rework and material usage. In general, parts costs fall into three categories: equipment costs, labor costs (such as purchased materials or used auxiliary gas), and labor. From here, costs can be broken down into more detailed elements (see Figure 1).
        When we calculate the cost of a labor or the cost of a part, all the items in figure 1 will be part of the total cost. Things get a little confusing when we account for costs in one column without properly accounting for the impact on costs in another column.
        The idea of ​​making the most of materials may not inspire anyone, but we must weigh its benefits against other considerations. When calculating the cost of a part, we find that in most cases, the material takes the largest part.
        To get the most out of the material, we can implement strategies such as Collinear Cutting (CLC). CLC saves material and cutting time, as two edges of the part are created at the same time with one cut. But this technique has some limitations. It’s very geometry dependent. In any case, small parts that are prone to tipping over need to be put together to ensure process stability, and someone needs to take these parts apart and possibly deburr them. It adds time and labor that don’t come for free.
        Separation of parts is especially difficult when working with thicker materials, and laser cutting technology helps to create “nano” labels with a thickness of more than half the thickness of the cut. Creating them does not affect runtime because the beams remain in the cut; after creating tabs, there is no need to re-enter materials (see Fig. 2). Such methods only work on certain machines. However, this is just one example of recent advances that are no longer limited to slowing things down.
        Again, CLC is very dependent on geometry, so in most cases we are looking to reduce the width of the web in the nest rather than make it disappear completely. The network is shrinking. This is fine, but what if the part tilts and causes a collision? Machine tool manufacturers offer various solutions, but one approach available to everyone is adding a nozzle offset.
        The trend of the last few years has been to reduce the distance from the nozzle to the workpiece. The reason is simple: fiber lasers are fast, and large fiber lasers are really fast. A significant increase in productivity requires a simultaneous increase in nitrogen flow. Powerful fiber lasers vaporize and melt the metal inside the cut much faster than CO2 lasers.
        Instead of slowing down the machine (which would be counterproductive), we adjust the nozzle to fit the workpiece. This increases the flow of auxiliary gas through the notch without increasing the pressure. Sounds like a winner, except that the laser is still moving very fast and the tilt becomes more of an issue.
        Figure 1. Three key areas that affect the cost of a part: equipment, operating costs (including materials used and auxiliary gas), and labor. These three will be responsible for a portion of the total cost.
        If your program has particular difficulty flipping the part, it makes sense to choose a cutting technique that uses a larger nozzle offset. Whether this strategy makes sense depends on the application. We must balance the need for program stability with the increase in auxiliary gas consumption that comes with increasing nozzle displacement.
        Another option to prevent tipping of parts is the destruction of the warhead, created manually or automatically using software. And here again we are faced with a choice. Section header destruction operations improve process reliability, but also increase consumable costs and slow programs.
        The most logical way to decide whether to use slug destructions is to consider dropping details. If this is possible and we cannot safely program to avoid a potential collision, we have several options. We can fasten parts with micro-latches or cut off pieces of metal and let them fall safely.
        If the problem profile is the whole detail itself, then we really have no other choice, we need to mark it. If the problem is related to the internal profile, then you need to compare the time and cost of repairing and breaking the metal block.
        Now the question becomes cost. Does adding microtags make it harder to extract a part or block from a nest? If we destroy the warhead, we will extend the laser’s run time. Is it cheaper to add extra labor to separate parts, or is it cheaper to add labor time to a machine’s hourly rate? Given the machine’s high hourly output, it probably comes down to how many pieces need to be cut into small, safe pieces.
        Labor is a huge cost factor and it is important to manage it when trying to compete in a low labor cost market. Laser cutting requires labor associated with initial programming (although costs are reduced on subsequent reorders) as well as labor associated with machine operation. The more automated the machines, the less we can get from the laser operator’s hourly wage.
        “Automation” in laser cutting usually refers to the processing and sorting of materials, but modern lasers also have many more types of automation. Modern machines are equipped with automatic nozzle change, active cut quality control and feed rate control. It’s an investment, but the resulting labor savings may justify the cost.
        Hourly payment of laser machines depends on productivity. Imagine a machine that can do in one shift what used to take two shifts. In this case, switching from two shifts to one can double the machine’s hourly output. As each machine produces more, we reduce the number of machines needed to do the same amount of work. By halving the number of lasers, we will halve labor costs.
        Of course, these savings will go down the drain if our equipment turns out to be unreliable. A variety of processing technologies help keep laser cutting running smoothly, including machine condition monitoring, automatic nozzle inspection, and ambient light sensors that detect dirt on the cutter head’s protective glass. Today, we can use the intelligence of modern machine interfaces to show how much time is left until the next repair.
        All of these features help automate some aspects of machine maintenance. Whether we own machines with these capabilities or maintain the equipment the old fashioned way (hard work and a positive attitude), we must ensure that maintenance tasks are completed efficiently and on time.
        Figure 2. Advances in laser cutting are still focused on the big picture, not just cutting speed. For example, this method of nanobonding (joining two workpieces cut along a common line) facilitates the separation of thicker parts.
        The reason is simple: machines need to be in top operating condition to maintain high overall equipment effectiveness (OEE): availability x productivity x quality. Or, as the oee.com website says: “[OEE] defines the percentage of truly effective production time. An OEE of 100% means 100% quality (quality parts only), 100% performance (fastest performance). ) and 100% availability (no downtime).” Achieving 100% OEE is impossible in most cases. The industry standard approaches 60%, although typical OEE varies by application, number of machines and complexity of operation. Either way, OEE excellence is an ideal worth striving for.
        Imagine that we receive a quotation request for 25,000 parts from a large and well-known client. Ensuring the smooth operation of this work can have a significant impact on the future growth of our company. So we offer $100,000 and the client accepts. This is good news. The bad news is that our profit margins are small. Therefore, we must ensure the highest possible level of OEE. In order to make money, we must do our best to increase the blue area and decrease the orange area in figure 3.
        When margins are low, any surprises can undermine or even nullify profits. Will bad programming ruin my nozzle? Will a bad cut gauge contaminate my safety glass? I have an unplanned downtime and had to interrupt production for preventive maintenance. How will this affect production?
        Poor programming or maintenance can cause the expected feedrate (and the feedrate used to calculate total processing time) to be less. This reduces OEE and increases overall production time – even without the operator having to interrupt production to adjust machine parameters. Say goodbye to car availability.
        Also, are the parts we make actually sent to customers, or are some parts thrown in the trash can? Poor quality scores in OEE calculations can really hurt.
        Laser cutting production costs are considered in much more detail than just billing for direct laser time. Today’s machine tools offer many options to help manufacturers achieve the high level of transparency they need to remain competitive. To stay profitable, we just need to know and understand all the hidden costs we pay when selling widgets.
       Image 3 Especially when we use very thin margins, we need to minimize the orange and maximize the blue.
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Post time: Aug-28-2023