The Howick Frama machines produce fully processed framing for Walls, Trusses and Floors from steel coil. Input provided directly from Cad design is used to produce every wall element ready for assembly. The Frama is essentially a single axis CNC machine and similar to a 3D printer that takes a spool of plastic and produces a 3D object the Frama takes a coil of steel and creates framing ready for assembly.
Like any CNC machine the quality of the input data and raw material has a significant influence on the quality of the output. All Frama machines have proven to be the most reliable in the market and provide high capacity output all day long but ensuring quality of input is part of productivity. Just like a poorly designed wall frame with an overuse of closely grouped notching operations can weaken a frame so can the steel coil.
For example when rollforming steel with a thickness less then 1.2mm (18 gauge)it is recommended to use a minimum grade of G350 material (50ksi). If a low tensile material - G250 (33ksi) or less is used it can cause rippling or “oil canning” of the side walls due to the ductility of the material i.e. the material is too soft and thin to support itself. When an excessively hard material is used (we have seen material up to G850) it can impair the ability of the machine to actually punch the material as it is beyond the designed maximum capability of the machine. Harder coil is often found as cheap coil in the market from steel mills that lack the ability to maintain the minimum grade required. Poorly slit coil with a wavy edge can also cause tracking issues as the coil is guided through the machine by the inconsistent edge.
Howick Frama machines are designed to run all day long without missing a beat and we are amazed at the meterage of output our customers produce. We have seen some companies that check every coil they receive and with Howick machines produce fully processed framing in the vicinity of 800 metres per hour. Following these guidelines will ensure you get the quality output and throughput that you expect.
July 2017 #News