smart prodactive

smart prodactive

What does it take to boost your shopfloor? Data, traceability, process optimization. In other words, smart prodactive!

smart prodactive

smart prodactive is a product of EnginSoft SpA.

smart prodactive is the web-based platform that brings companies into the era of data and artificial intelligence in the following steps:

  • receiving data external sources (e.g., machine states, alarms, process parameters, process variables, signals from additional sources)
  • processing and transformation of the data using artificial intelligence
  • generation of useful information to increase business
  • control and improvement of the production process
  • predictive maintenance to have assets always available
  • representation of energy consumption
  • evaluation of sustainability indexes achieved with energy savings

The platform is based on a microservices architecture, easily scalable and avilable both on-premise and on cloud as SaaS. The main modules are:

  • smart prodactive.acquisition: the module offers an innovative solution to acquire and monitor industrial data, easily integrating with the existing production environment. Using smart algorithms, it enables real-time data analysis and performance monitoring, improving operation efficiency and providing a competitive advantage in the global market;
  • smart prodactive.maintenance: the module optimizes the efficiency of industrial plants through predictive maintenance, analyzing data with advanced algorithms to prevent failures and schedule efficient interventions. This proactive approach reduces maintenance costs and maximizes productivity by integrating directly with existing enterprise systems;
  • smart prodactive.energy: the module analyzes energy consumption data at various levels, enabling the identification of trends and anomalies, and providing indicators and reports to assess corporate sustainability, with a focus on reducing costs and environmental impact;
  • smart prodactive.quality: the module monitors and analyzes process quality, using artificial intelligence to identify problems and define improvement plans. Integrated with smart prodactive Acquisition, it ensures the efficiency and effectiveness of production processes, reducing waste and improving the quality of finished products. By providing detailed reports and charts, it enables users to take informed decisions to optimize processes, thus helping to ensure business competitiveness and efficiency.

The smart prodactive platform is sold on an all-inclusive basis, with comprehensive support tailored to the needs of the business. We provide our customers with platform start-up support, shop floor digitalisation consultancy, production process optimisation and sustainability and ESG modelling support.

smart prodactive - Data, traceability, process optimization

Main benefits

Request a free demo

  Faster Delivery Times

  Real-time Monitoring Active

  Scrap Rate: the involved HPDC foundry is expecting for a 40% reduction in scrap rate

  Production: flexibility, stability and efficiency is generating 10% of no-quality-cost

  Quality Control: in good exploitation scenario the cost of quality control can decrease of 40%

  Energy: energy consumption will be reduced by 5-10%, due to scrap reduction and more production efficiency with reference to the single cast part

Documentation

brochure

Brochure prodotto

Scarica la brochure di smart prodactive

smart prodactive

technical paper

Innovative control and real-time quality prediction for the casting production of aluminum alloy structural components

This work was developed within the “MUSIC” Project (MUlti-layers control & cognitive System to drive metal and plastic production line for Injected Components), supported by European Union [FP7-2012-NMPICT-FoF] under grant agreement number n°314145. The authors would like to thank the MUSIC consortium (www.music.eucoord.com).

Read the technical paper

smart prodactive

technical paper

Real-time HPDC quality prediction and optimization supported by trained cognitive model

This work was developed inside “MUSIC” Project (MUlti-layers control & cognitive System to drive metal and plastic production line for Injected Components), supported by European Union - [FP7-2012-NMP-ICT-FoF] under grant agreement number n°3141. The authors would like to thank the MUSIC consortium (www.music.eucoord.com), and particularly RDS Moulding Technology SpA.

Read the technical paper

smart prodactive

Ask the Expert

Ask the expert

Send your technical questions to our experts!
Connect you with an EnginSoft expert who can provide a reliable answer to your technical question or recommend a proven solution.

Ask the expert Request a free demo

Insights

CASE STUDY

Improved blast furnace performance with material load optimization

Combining modeFRONTIER with Rocky DEM to design a better deflector saves up to 130 hours of computation time

The Arvedi Group approached the University of Trieste to find a solution to the uneven distribution of material inside the hopper of their blast furnace in Trieste, Italy.

optimization modefrontier rocky mechanics

NEWSROOM

Stay connected with us: news, analysis and trends from our experts.

Newsroom  

MEDIA CENTER

Scroll through our Media Center to view all the videos, video-tutorials and recorded webinars.

Media Center  

CASE STUDY

High Pressure Die Casting Optimization of a Connecting Rod

A multi-objective engineering simulation study of the connecting rods manufacturing process

Connecting rods connect the pistons to the crank shaft in automotive engines and are vital components of the engine. Connecting rods are traditionally produced in ferrous metals by forging or die casting.

metal-process-simulation automotive magma

Find out more

CASE STUDY

Smarter wheels: How multi-physics optimization is shaping the future of automotive design

A collaborative project between Nissan Technical Centre Europe, RBF Morph, and the University of Rome “Tor Vergata” showcases how multi-physics optimization is revolutionizing automotive wheel design, particularly for electric vehicles (EVs). By integrating styling, structural analysis, and aerodynamics within a unified workflow enabled by advanced mesh morphing technology (rbfCAE), designers can optimize wheels for lightweight, strength, and aerodynamic efficiency without compromising aesthetics.

automotive optimization

CASE STUDY

Optimization of the SLM/DMLS process to manufacture an aerodynamic Formula 1 part

This paper presents the RENAULT F1 Team’s AM process for an aerodynamic insert in titanium Ti6Al4V. Production was optimized by identifying the best orientation for the parts and the best positioning for the support structures in the melting chamber, in addition to using the ANSYS Additive Print module, a simulation software useful for predicting the distortion of a part and for developing a new, 3D, compensated model that guarantees the best “as-built” quality.

automotive additive-manufacturing optimization

CASE STUDY

The design optimization of a small axial turbine with millions of configurations

The case for computerized optimization over manual design interventions

In this article, we show that the main turbine characteristics, such as efficiency and exit flow angle, can be sufficiently improved using parametric optimization.

modefrontier energy optimization