Steel Project, software solutions for steel construction

Thanks to our software division Steel Projects, we offer modular solutions that integrate automatic programming, advanced nesting and production management to optimize the entire steel fabrication workflow.

Through our software division, we now provide comprehensive solutions for the digitalized and optimized management of workshops, fully aligned with Industry 4.0 principles. These solutions focus on three main areas — CAM, Nesting and MES — automating and optimizing the connection between the engineering office and the shop floor, converting design drawings into CNC machine programs while considering real-time production constraints.

INTEGRATION WITH EXTERNAL CAD SYSTEMS

Interoperability with the main CAD software used in the industry is a key factor in ensuring continuity within established workflows. Steel Projects has developed specific expertise in importing and converting heterogeneous file formats, dedicating significant resources to the continuous improvement of these processes.

«Steel Projects – says Geoffrey Martin, Marketing Manager at Steel Projects – integrates with most CAD software in the industry and supports numerous formats, including DXF, DWG, DSTV, IFC, XML, and STEP. After importing the files, the software converts the geometries into machining operations to prepare for production. This is one of the company’s main areas of know-how, and four members of our R&D department are dedicated exclusively to improving import formats and their efficiency. The more information we can extract from the CAD software, the greater the potential for production optimization downstream. For this reason, some formats are more effective than others, depending on the amount of information they can provide».

ADVANCED AUTOMATIC NESTING ALGORITHMS

«The Steel Projects plate nesting engine – explains Martin – is particularly efficient thanks to its ability to adapt perfectly to the real characteristics of each CNC machine, especially those manufactured by FICEP. Does the machine have a gantry, or does the plate itself move? Should clamps or other gripping devices be taken into account? What are the different available methods to obtain a specific geometry — for example, a hole, either by drilling or plasma cutting? Can the machine perform common cuts or bridges to optimize processing time? All these parameters are considered both in the part placement during nesting and in the management of the machine sequences».

A simulation tool (emulator) is also available, allowing users to verify the final result before generating the program and starting production, thereby reducing the risk of errors and optimizing resource utilization.

FAST CHANGE MANAGEMENT

«The software – confirms Martin – includes an integrated drawing editor to create new components or modify existing ones. It also offers the ability to automatically apply changes to selected groups of parts, in order to optimize production or manage unforeseen situations. For example, users can replace operations, such as switching from drilling to punching, adjust hole diameters, or manage marking lines».

A dedicated tool allows users to track all modifications made to a project, enabling all stakeholders to see who made each change and when, and to compare different project versions.

«Steel Projects – adds Martin – allows users to automatically check and validate parts before sending them to production, to prevent errors. The software analyzes geometries to ensure there are no drawing issues and compares workshop capabilities with the required operations, avoiding unexpected machine errors. If an operation requested by the engineering office cannot be performed, the software generates a warning, ensuring that no part is sent to production with errors».

ARTIFICIAL INTELLIGENCE APPLIED TO CAM

«AI – concludes Martin – is a topic that remains at the core of our R&D department’s efforts. We are working on several fronts: from the development of nesting algorithms based on historical data, to advanced programming for welding and coping robots and the optimization of cutting paths. Another important area is predictive maintenance, which allows us to anticipate machine downtime before it occurs. Artificial intelligence also supports the calculation of estimated processing times and the allocation of resources based on real-time parameters, as well as the optimization of engineering projects and the automatic generation of estimates based on recorded production times.
Finally, we are exploring applications in quality control through augmented reality and optimized stock level calculations, with the goal of systematically identifying areas for improvement by leveraging all data collected from the production process».