New technologies: how agricultural machinery design is changing

New technologies have entered the agricultural sector and are changing it view industrial world. But how? And what are these new technologies?

workshop”How new technologies are changing the horizon of industries” held on October 24 CNH Industrial AND Ansys in the wonderful setting of Villa Cesi in Modena, he unpacked the industrial world of the agricultural sector by explaining what was going on production cycle of agricultural machinery from all points of view, incl lack sufficiently trained experts.

First it was a drawing

The production of agricultural machinery clearly requires a design phase. That intuition the human being is fundamental, that is not disputed, but what happens next?

It’s in the next step, froman idea for a finished productthat we are watching a real revolution.

New technologies for the agricultural sector

THE technological trends which are actually already part of the agricultural landscape,”to influence the design, development and verification of new agricultural machinery – he claims Gennaro Monacelli Global Director of Design Analysis and Simulation at CNH Industrial – to this is added the need for support necessary for the farmer to farm agricultural society 4.0 and automation of some functions“.

Technological trends in agriculture.jpg

Technological trends that are revolutionizing the agricultural sector

(Photo source: CNH Industrial)

IoT and smart agriculture, GIS systems, robots and autonomous vehicles, artificial intelligence, machine learning and data analytics are all systems that can bring specific advantage on the agricultural system in the sense of increasing productivity, health of products, reduction of waste and reduction of waste, efficient use of pesticides and water.

But it is necessary Keep in mind already in process design agricultural machinery also solve problems correctly safety and reliability the machines themselves. “Digital tools are the driving forcedevelopment agricultural system” explains Monacelli.

A digital twin, a twin that suggests

A digital twin is nothing but a virtual twin identical to the physical model, able – in its simulation – also to consider some production aspects which may affect the performance of the machine.

In CNH – explains Moncelli – we work with models that run in real time and use feedback from machines in the field. Thus let’s correspond a physical machine with a virtual Twin that represents the physical model in the field moment by moment“.

Watch the Ansys Digital Twin video

By providing inputs such as engine load, engine speed, tractor speed and ambient temperature to a real-time model, we can obtain outputs on performance and reproduce real critical situations and immediately diagnose potential failures of a real machine“, continues Moncelli.

Physical testing he can’t anymore respond to all needs, you need a new mix. “Our customers – explains David Frigerio Ansys Principal Application Engineer – take advantage of our solutions reduce product development times”. We pass, says Frigerio, from 50 months (just over 4 years) required for traditional models and 24 months (2 years) s simulation technology in the automotive sector.

A simulator that makes the experience real

The presence of the simulator”Drivers in the loop” created by the CNH team led by Gennaro Monacelli – who celebrated his first birthday on October 24 – allows a hybrid approach (testing + simulation) and allows to simulate products not yet produced (for example, with new vehicle suspension and cabin suspension concepts), allowing the designer to physically get into the cabin and test the new product, even though it is still in development. concept. “WITHIt is a subjective test – Monacelli clarifies – based on standard maneuvers, which then allow objectification of the judgment of the various stakeholders in product development“.

Read also Virtual simulation and agricultural machinery. Yesterday’s future, today’s reality

So have the option virtual farms offers an immersive upgrade. “We model several farms around the world extend reliability and we also model a lot tool check operation of the entire construction site“, explains Monacelli.

Around a hundred results are obtained from the performed simulations (including dynamic ones), two or three are selected, analyzed and finally improve based on which physical prototype which, however, is already in an advanced stage of testing.

Electric and autonomous vehicle testing is also virtual

For electric vehicles says Monacelli -, the simulation method had to be adjusted by creating a road map based on the gathered needs. While – continues – when testing vehicles and autonomous drivingthe problem is not to build them, but confirm them. All it takes is one dangerous situation and development is stopped”.

Testing a self-driving vehicle using traditional methods is practical impossible for the impressive number of miles required. For this reason, in the automotive sector, investments have moved towards technology virtual testing.

Testing electric motor is carried out on 5 pillars:

  • battery pack,
  • power electronics,
  • engine,
  • gear-case
  • system integration, i.e. the integration of individual components at the system level.

“This approach – says Frigerio – significantly reduces time and costs with the offer answers also on electromagnetic compatibility and allows us to get into room tests with a solution that we are reasonably confident will pass the EMC test first time“.

AI and machine learning. Importance of data

Digital Tewin is based on new technologies such as Internet of Things (IoT), Industrial Internet of Things (IIoT), Artificial Intelligence (AI), Big Data, Multiphysics Simulation and Cloud Computing.

WhileArtificial Intelligence simulates human intelligence, Machine Learning focuses on the human ability to learn and requires data.

With classical programming, humans provide the data and rules, and the software delivers answers. Machine learning helps improve simulation software because starts from the answers create useful rules for algorithm development learning ability.

Data: Not all are the same

THE dataand target AND algorithm, are the pillars of machine learning. But for ML to work, ie data they must be:

  • accessible and available
  • respect privacy and be safe,
  • be relevant to the target
  • be fresh, representative and must not contain errors.

So data plays a role basic.

AI and ML enrich simulation, and simulation data simultaneously enriches AI and ML systems. “The Generative design – explains Domenico LoricchioAnsys Principal Application Engineer -, and future digital twin because it allows you to create new, never-before-designed models. It is not just based on the database provided as input, but uses it knowledge of the surrounding world and on the basis of physical principles it generates new innovative forms that are also valid from the point of view of fluid dynamics“.

AAA Skills and Competencies Required

But if design and validation cycle If the vehicle is brand new, companies in the agricultural sector must equip themselves new competent technical data and properly formed.

This is where they come into play University who recognize this as a rapidly developing trend in the agricultural sector, where unlike the industrial sector where the path is already consolidated, we face big challenge.

Training offer: new courses of the future

THE projects there are already others on the table. We start with MUNER – Emilia Romagna University of Motor Vehicles which connects 4 universities Emiliano Romagnoli, but also companies operating in the territory, in vertical and specific ways based on the principle Learning by doing.

In the sixth year of its activity, from September 2024 will start a new path dedicated to vehicles off the highway created through collaboration between Francesco Leali, professor at the University of Modena and Reggio Emilia, and Gennaro Monacelli’s team, it will be based in the universities of Modena before moving to Bologna for the second part of the training course. The Master also includes the creation of SSummer school at CNH and University of Bologna facilities.

Always inside MUNER, the a new Agritech Engineering projectincludes 4 pillars: environmental engineering, ICT, industrial and chemical engineering to train personalities capable of responding to the needsagriculture 4.0. The course started on October 2 and is still available new registrations.

of Polytechnic of Turinproject PIC4SeR del, works in 6 areas, inclagricultureto coordinate the activities of various research groups already operating in various departments in the field of technologies necessary for development robot.

PIC4SeR supports all the necessary development phases leading to the design, simulation and production of the essential components that will enable a new era service robot.

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