From the collaboration between the competence centers Start 4.0 And Made 4.0 and EnginSofta software house specializing in simulation-based engineeringthe project comes to life DigitBreak. It was created to satisfy the optimization of a work cell dedicated toassembly of car brake systems of Cosberg, the leading Italian company in mechatronics, automation, robotics, vision systems and special assembly machines led by Gianluigi Viscardi, production entrepreneur, president of Cosberg and vice president of the Intelligent Factory Cluster. The project is now a demonstration system visible at the pilot line of the Made 4.0 competence center of the Politecnico di Milano. As he explains Giacomo Pepe Benedettiproject manager of Ligurian Start 4.0 competence center, “DigitBreak was developed during DigitBrainthe initiative is funded with 9.5 million euros from the European program Horizon 2020. Will help manufacturers of assembly and production lines to overcome growing challenges, such as optimizing design and engineering to meet the needs of the ever-changing market, while ensuring efficiency and productivity challenges ».
«DigitBreak is one Simulation-based digital twin (Sbdt) for production environments and offers a complete production process management experience, ”he adds Anteneh Yemaneh, EnginSoft production systems engineer. Specifically, the digital twin simulates the entire Cosberg assembly area, which consists of several workstations. The various components through several steps are tested and verified in the dedicated workstations and then assembled as an end product. This is the classic case where digital twin can help you find the best solution to secure productivity without compromising quality. The faster the process, the greater the risk of having defective parts as you know. Here, DigitBreak helps resolve this conflict by proposing to the production or factory manager the best compromise between quality and speed of the process. “The digital twin considers each station, the individual cycle times, and parameters that affect process quality, including the critical issues that can be caused by moving parts and components from one station to another,” says Yemaneh.
DigitBreak thus becomes italgorithm to achieve goals production capacity. It answers a simple question: how many products can I produce in a unit of time with predictable quality? The answers are displayed on the dashboard and offer strategic support for evaluating the “best assets”, enabling a reduction in downtime and an optimization of cycle times and resource allocation. Result? Reduction of operating costs, increase of quality, increase of service life of the machines, improvement of flexibility, increase of manageable product variants. «The story of the DigitBreak project demonstrates the value that can arise from a collaborative logic aimed at technology transferHe says Maria Rossetti, Made 4.0 project manager. It is a solution that could be further developed and give rise to a diversity of real cases ». Here are the secrets behind the new revealed system from simulation which integrates physical and virtual from the story of what appeared under “Digital Twin to optimize the design of production systems” organized by Made 4.0.
DigitBreak has been developed as part of DigitBrain, the € 9.5 million initiative funded by the European Horizon 2020 program. Here is the whole webinar
Digital twin, the production assistant to plan the production
The management of modern production systems is becoming more and more complex. New product variants, mass adaptation, smaller and smaller batches that require frequent process changes, unforeseen events, discontinuities and workloads that increase the risk of dead times and of inactivity. A nice puzzle. Often it is necessary to intervene to perform re-configurations and setups of the lines, of the individual machines or of the work cells. Not only that, ie factory managers they must be able to ensure superior quality performance despite the fact that the products are becoming more and more sophisticated. Furthermore, the flow of components and semi-finished products within the work area must be optimally controlled. In short, production planning and resource allocation are no joke these days. How to manage control costs, times And quality? Who can bear the burden? THAT plant or production managersof course, that today they can rely on a valuable and valuable assistant, the digital twin.
Evaluate all production options
As Yemaneh explains, “depending on the product to be put into production, the digital twin implemented by DigitBreak will help you choose system of target productionIs it a product that can be produced for the next two to three years without significant changes? The choice will fall on a standard production line, which despite guaranteeing poor flexibility is suitable for high mass production speed. Should production be planned with great variance? The preference will go to a dedicated workspace, a robotic or semi-automated cell. “These are all options that need to be carefully considered in the design of the production digital twinthrough its logic based on simulation helps make the most appropriate decisions by analyzing potentials kpi or performance indicators for every opportunity, ”says Yemaneh.
Knowledge of process, machine and product
ONE digital twin allows the plant managers to answer essential questions. How can I optimize the schedule? What effect will the introduction of a new on-line machine have? How to adapt the system to new product variants. How to improve performance without compromising productivity and production costs? What are the best machine and workstation configurations to maximize workflows during the day? And again, what is the best solution, layout, to prepare the processing of new products? That physical reconfiguration of the system and addition of machine modules. All aspects that, if not tested properly, can cause a deterioration in productivity and quality. Here, as Yemaneh says, “that it data collection from the field, both system and product, it provides the opportunity to acquire process, machine and product knowledge to achieve the predetermined performance indicators ».
Simulate all possible scenarios
THAT data streams that fuel for the digital twin enables decisions at multiple levels: how configure the production system as a whole and the specific machines. “Decisions,” explains Yemaneh, “can be considered hard reconfigurations, which involves a physical change of assets, of the individual line or machine ». In these cases, customization can be time consuming and expensive. So here is that simulation based on digital twin optimizes the entire reconfiguration by reducing costs and time to market. “In other cases,” the EnginSoft manager continues, “soft workflow reconfigurations will suffice. Just change control logicwithout interfering with the physical system. ”Whatever the case, the digital twin allows you to simulate all possible scenarios and orient the most valid decision before going into production.
An ecosystem of resources, skills and know-how for digital twin solutions
DigitBrain is the program Horizon 2020 which involves an international consortium of companies and partnerships from different countries (Italy, Finland, Estonia, Austria, Germany, Spain, Hungary, the Czech Republic, Denmark, but also the United Kingdom and Russia). The goal is to implement a development of the concept digital twin made available to manufacturing sms through an open platform to which everyone can contribute. “The DigitBrain program supports SMEs looking to experiment with new digital twin applications through specific use cases. Activate a new production model, named Manufacturing-as-a-Service (MaaS), which allows production on demand of specialized products, even in small quantities and in any case in an economically viable way, “says Pepe Benedetti.
By using digital twins, companies can rationalize production processes, prevent interruptions and downtime, manage maintenance in a predictable way. DigitBrain is a new approach that expands the digital twin to cover the entire life cycle of industrial products by integrating analyzes and decision support. The digital twin has access to data, models, algorithms and on-demand resources for industrial products and stores data below inthe whole life cycle of a production line or machine. The expected benefits are to accelerate the adaptation of production and products to changing conditions, enable cost-effective custom manufacturing, facilitate distributed and localized production at low cost, giving companies access to advanced production facilities within their regions or to distribute their orders among others.