RESOURCE LIBRARY

ABB Group, a global leader in power and automation technologies, covers almost every segment of the power generation and industrial process control market with its products and systems. With $1.4 billion in annual investments, the 8,500 engineers and scientists at ABB Research & Development are committed to meeting the automation industry’s ever-increasing demand for reducing energy consumption and improving reliability and performance. The design projects illustrated here highlight how ABB Group leverages optimization-based development to handle the complexity that electronic and software components entail. Looking at system interdependencies from the earliest concept phase is crucial for an effective strategy that aims at maximizing product performance, meeting reliability demands and easing the environmental impact of their products. ## Optimization-Based Development of Ultra High Performance Twin Robot Xbar Press Tending Robot System The industry challenge Industrial robots are sophisticated systems incorporating hardware and – increasingly – software components. Subsystem design (gearboxes, motors, sensors and brakes) and the interactions between elements such as machine interfaces, safety integrations, field buses, PCBAs, power supplies and drive modules must be carefully planned to assure the best possible performance. Over the years, cost pressures have made robots a commodity in terms of physical specifications. Among the many design challenges, the need for lighter components has resulted in reduced stiffness, making the control problem more complex. Furthermore, many third-party interfaces require integration and products that must comply to software, electrical and mechanical quality standards. ABB experience In the case of the Twin Robot Xbar Press Tending Robot System, one of ABB’s flagship robots, engineers considered 18 design variables (representing the gear torque, motor torque and motor speed) and managed objectives and constraints in modeFRONTIER, achieving a 12% energy saving, solely by varying the software components. “We optimized this robot ‘manually’ for 30 years and it is one of the most used. With modeFRONTIER we were able to identify a new design – requiring no implementation costs – bringing 12% of energy savings without compromising performance by changing only the software configuration. Obviously, this is something that can’t be done by hand – you need an optimization software to do it.” says Dr. Wappling, Global R&D Manager at ABB. ### Benefits “The ability to manage mechatronics is becoming increasingly important as simulation encompasses more and more systems and not just components: the impact of the mechanics, electronics and software all need to be accounted for.” continues Wappling. ESTECO technology keeps pace with evolving R&D needs and provides designers with a flexible environment that handles each delicate step of complex system analysis and enhancement. As seen in the example of the robot, inserting virtual control models in the simulation framework enables designers to apply the optimization approach, calibrate the software and identify zero-cost solutions. ## Multiobjective Optimization of a Medium Voltage Recloser The challenge Medium voltage reclosers now represent an important grid protection device that connects different grid sources, increase the network/grid reliability and make the implementation of self-healing and auto reconfiguration schemes for overhead lines possible. With a high level of renewable energy penetration, medium voltage networks are becoming bidirectional. Therefore, the associated switching devices must ensure the protection of newer types of power systems as well as new types of loads. The optimal design of medium voltage reclosers is therefore important in order to enable excellent switching capabilities. The switching capabilities of medium voltage recloser can be influenced by various parameters such as actuation energy responsible for opening and closing the device. Therefore, to maximize the lifetime of the recloser, it is essential to establish an optimized control especially related to the actuation energy. The goal of the multi-objective optimization is to identify an optimal actuation energy control strategy for the closing and opening operations. The solution ABB R&D Teams built a two-step optimization framework that incorporates the energy efficiency constraints by working initially on the electromagnetic actuator and directly optimizing the Finite Elements Model (FEM). The numerical simulation step was then completed with physical calibration via a Hardware-in-the-Loop (HIL) optimization process, ensuring that the whole system reaches the desired performance. During the first iterations, modeFRONTIER helped improve the FEM model by identifying the best configuration possible for the electromagnetic system, while satisfying the constraint imposed by the design boundary conditions. The parameterized FEM model created with COMSOL Multiphysics was connected to Matlab LiveLink so as to pilot all design changes automatically and control both models in sequence, leveraging the direct integration node for Matlab in modeFRONTIER. In the second step, the R&D Teams opted for the in-depth analysis of the system where modeFRONTIER was coupled both with the simulation model and with the hardware to further enhance the switching properties. The HIL framework enabled an investigation environment for the whole recloser system. Thanks to this approach, optimization can be applied to the control scheme implemented with CompactRIO/LabVIEW: after running one full closing-opening operation, data is transferred to Matlab for post processing and reinserted in the loop for the next runs. Since reducing overtravel and backtravel is extremely important for the product lifetime, with modeFRONTIER piloting the HIL system (1,500 runs with a DOE featuring selected parameters from the first optimization step), R&D Scientists pinpointed a new control scheme that enables significant extension of the product lifetime. “The identified control scheme enables up to 50% reduction of the overtravel and backtravel, enabling a remarkable improvement in terms of lifetime”, says Octavian Craciun Senior Scientist at ABB.

Using modeFRONTIER coupled with Rocky DEM to design a better deflector while saving up to 130 hours of computational time The Arvedi Group turned to the University of Trieste to find a solution to the uneven material distribution inside the hopper of the blast furnace in Trieste, Italy. The Mechanical Engineering Department investigated the problem and used modeFRONTIER to optimize the design of a new deflector ensuring a better distribution of the materials. Exploiting the ESTECO integration and process automation technology they coupled modeFRONTIER with Rocky DEM software to accelerate the simulation process of the material distribution. Using the proprietary algorithms available in modeFRONTIER, they were also able to find the optimal design for a new deflector. ## Challenge The project concerned the charging process of coke coal and iron ore inside the hopper. The different materials formed piles and pitches, leading to a lower performance of the plant. The uneven material distribution inside the hopper caused variations in the temperature profile, gas flow, and gas composition. To solve this problem modeFRONTIER was coupled with Rocky DEM to get a better understanding of materials behavior and optimize the design of the deflector. The integration with modeFRONTIER also allowed to meet the time constraints, reducing the computational time for each simulation. ## Solution This project was developed in two phases. The first phase concerned the calibration of Rocky DEM parameters and the simulation of hopper charge. The second phase consisted in optimizing the geometry of a new deflector for the charging process.For the calibration process, they used the parameters of Discrete Element Method as inputs in modeFRONTIER, such as particle- particle static friction and rolling resistance. The repose angle of simulated material was used as output. For the device optimization, a sensitivity analysis with Uniform Latin Hypercube allowed to run 90 designs and identify the most important design variables. Engineers then optimized three different geometries, taking these geometrical variables as inputs. The outputs were based on the material distribution, calculated by virtually splitting the hopper into 12 sectors and performing statistical analysis on the particles found in each. These values were used to define the two objectives and the constraints of the optimization. They used the ESTECO proprietary pilOPT algorithm to run the three optimization studies. Thanks to the autonomous mode they could evaluate more than 1000 designs in just a few weeks, without having to set any parameters and with remarkable benefits in terms of time. Benefits Thanks to a user-friendly graphical user interface, modeFRONTIER helped automate the simulation process. Without modeFRONTIER, engineers would have had to manually change the geometry of the deflector for every simulation, with significant waste of time. With modeFRONTIER they were able to save up to 130 hours of computational time. Finally, by automating the process, design engineers could launch the optimization and avoid the painstaking process of manually combining the output from multiple applications.

Jingyuan Yan, Ph.D in Department of Mechanical Engineering, used modeFRONTIER to develop his Ph.D research project focused on the design and optimization of the Direct Metal Deposition (DMD) process. DMD is a 3D printing process for metal, similar to welding, using powders instead of wire. It uses a continuous wave or pulsed laser to induce a melt pool on a substrate, and metallic powders are delivered into the pool via injection nozzles. The process is able to deposit different metal powders onto different locations of the powder substrate in order to manufacture multi-material parts according to user requirements at the microscale level. Despite the benefits of DMD, this process is not widely used in industry: the building powder waste, the need for reduction of energy usage and inaccurate material composition in the fabricated parts are still critical issues. The DMD system provided by Optomec was used to implement the research. During his research on DMD, Jingyuan worked on an injection nozzle designing first of all its geometry to maximize the process efficiency and investigate the relationship between the desired part’s composition and the process parameters. Jingyuan also wanted to improve the DMD process parameters considering their effect on efficiency when manufacturing multi-material parts. “In order to make the best use of powders and to minimize the laser energy consumption, we aimed at optimizing the process parameters. The bi-objective optimization problem was set up in modeFRONTIER workflow using the direct node to MATLAB. Eight design variables related to the process parameters (injection angles, velocities and nozzle diameters for the two materials as well as the laser power and the scanning speed) were set and automatically adjusted with modeFRONTIER to minimize the outputs results: powder waste and energy cost.". “The multi-objective genetic algorithm (MOGA-II)” continues Jingyuan, “turned out effective in driving the search process and identify the designs which met the constraints on the deposition of multiple materials. As we see in the scattered chart, the feasible designs show a trade-off relationship between the two objective functions. The Pareto front results, marked with green color, enable the users to rapidly select the configuration with lower powder waste.” “The calculation process took about three hours. Using modeFRONTIER, we saved about three days of calculation time compared to the traditional optimization method. In the future, the optimization method can be applied to analyze other combinations of materials used in DMD, with any powder feed rate ratio. The results will be validated with experimental tests and it will be possible to generate a database of optimal process parameters for any given condition to be reused for future DMD projects. In the long run, modeFRONTIER can help tailor the process parameters during the DMD manufacturing of functionally graded parts, in order to get an accurate material composition as desired.”

Using modeFRONTIER to integrate GT-Valve train and GT-Power models for valve event optimization Cummins Engine, a leader in the manufacturing of diesel and natural gas-powered engines for a wide range of transportation and equipment purposes, has created a new power module ready to take on the stringent US - EPA regulations. It is significantly more compact and cost-effective than medium-speed engines at the same horsepower. It took 150 engineers to design it, and modeFRONTIER helped the High Horsepower group find the optimal valve timing, hence reducing fuel consumption. ## Challenge When designing piston engines, timing when opening and closing inlet and exhaust valves is a crucial parameter impacting the fuel consumption / power output ratio. Typically, delaying the Exhaust Valve Closing (EVC) and anticipating the Intake Valve Opening reduces Exhaust Gas Residuals, resulting in lower fuel consumption. Among the complex models composing the 16-cylinder engine, Cummins designers used GT-Suite (Valve Train and Power modules) to simulate valve event performance and dynamics. For optimal engine performance, valve timing and lift profile need to be perfected for given breathing configurations defined by engine speed, and valve and port geometry and performance. ## Solution Finding the optimal valve timing configuration required a two-step process; to start, a first workflow was created in mode FRONTIER and used to automate the calibration process. Valve train parameters were automatically adjusted with modeFRONTIER to calibrate the GT model and match measured push tube load. The second phase consisted in a second workflow, which was used to investigate the design space; initially with response surfaces and subsequently with the direct optimization algorithms NSGA and Hybrid - to find the best values for 12 output parameters measuring the exhaust and intake cam timing angles, the volumetric efficiency and the Brake Specific Fuel Consumption (BSFC)1. ## Benefits During both project phases, modeFRONTIER proved highly reliable for reducing design cycle time and improving the performance of the valve train system. From the outset “it helped drastically reduce the time taken for calibrating GT models” said Ambikapathy Naganathan (Structural and Dynamics Analysis Engineer at Cummins). “modeFRONTIER has an excellent capability for integrating with multiple GT models and post processing tools.” Continued Eng. Naganathan: “in fact it helped us link those GT models more efficiently and complement the in-house optimization tool, while at the same time maintaining concurrent use by different analysts in different locations.”

Optimization time dropped from 20 to 4 days, with a 44% safety improvement SACMI is a global OEM (Original - Equipment - Manufacturer), market leader in the production of machines and complete plants for the Ceramics, Packaging (Beverage and Closures&Containers), Food and Plastics industries. ## Challenge Among other machines, the SACMI packaging division manufactures the Compression Molding Machine (CCM) able to transform plastic resin pellets into semi-finished caps. During the injection phase, a pneumatic piston allows for the melted pellet to be injected inside the mold. The piston is subject to a high acceleration rate and continuous collisions which call for a compromise between stress and weight, in order to limit the risk of failure. ## Solution The goal of the analysis was to find a light but strong piston geometry in order to improve the Compression Molding Machine performance in terms of tensile and yield strength. The first optimization study was carried out manually for a 12mm piston, while the second study on a 16mm piston took advantage of modeFRONTIER optimization platform by capturing the piston model, previously created in Solidworks and analyzed in Ansys Workbench, and improving the geometry and performance. Piston geometry modifications led to a 33% safety index increase in the case of manual analysis and 44% in the case of the model optimized with modeFRONTIER. ## Benefits modeFRONTIER enabled the CAE expert to exploit his original inspiration - which led to an improved piston geometry - by evaluating a higher number of configurations (+240%) in less time and by further enhancing the safety performances. The time for the optimization process dropped from 20 to 4 days, 3 of which were required for manual setup and 1 for automated evaluation. “I wasn’t an experienced modeFRONTIER user - says Andrea Minardi, CAE specialist at SACMI Packaging Division- so I found the Optimization Wizard very useful: it supported the choice of the number of designs, of the algorithm and of the number of iterations according to the time available for the whole analysis.” The automation of the design optimization process allowed to consider a wider range of possibilities and to analyse in depth the influence between the design parameters and the objectives.

Bottero innovates with optimized high performance mold-motion Leading in the glass industry is Bottero’s declared ambition. The recent launch of E-MOC, a family of mold opening and closing mechanisms (MOC), has challenged the hollow glass industry. E-MOC introduces a completely new cooling concept, granting the possibility to achieve the proper temperature profile, according to the type of process required for the application field. Challenge “The innovative idea behind E-MOC design is the result of our R&D team’s work: numerous constraints were limiting the possibility of changing the machinery design, so modeFRONTIER, the multi-objective optimization platform, came to our help”, says Marcello Ostorero, Structural and Fluid Dynamics Simulation Department Manager at Bottero. The mechanism had to be equipped with a universal mold holder providing efficient cooling and, when mounted, it had to be readily accessible and installable on both new and existing machines. The optimal system performance called for a smooth and precise mold motion, with fast closing time, and maximum closing and clamping forces. ## Solution The complexity of the problem was tackled with modeFRONTIER within two optimization cycles. The aim of the first one was to minimize mold motion oscillations. The results were then used to conduct a sensitivity analysis, which revealed the piston center movement as the most important variable for mechanism stability, but the geometrical constraints did not allow the piston to maintain the optimal trajectory. This unexpected obstacle was bypassed by replacing the single large piston with three smaller ones. In the second optimization cycle modeFRONTIER guided the model adjustments to minimize mechanism lability and oscillations, while keeping constant the newfound optimal values of component geometries and of piston center movement. ## Benefits “Due to the intricate nature of the required mechanism, the systematic optimization approach proposed by modeFRONTIER was the only way to obtain a functioning high-performance design”, says Ostorero, “modeFRONTIER managed to find a fine balance between a high number of rigorous constraints and adjust the model geometry to the most important mechanism specifications so as to increase its efficiency and quality, while successfully driving a number of software, each solving a single aspect of the problem, integrated in a single workflow”.