smart ProdACTIVE

smart ProdACTIVE

ICT platform to real-time QUALITY PREDICTION and OPTIMIZATION supported by TRAINED COGNITIVE MODE

smart ProdACTIVE

smart ProdACTIVE is a product of EnginSoft SpA.

The smart ProdACTIVE tool predicts the quality, energy and cost of the injection process in real-time, covering the 100% of products, and suggests the appropriate re-actions to adjust the process set-up and/or mechanism. It works in combination with the real time monitoring system (or Intelligent Sensor Network) to elaborate instantaneously the production data set with respect to quality/energy/cost prognosis. The client-server mechanism works in combination with the real time monitoring system (or Intelligent Sensor Network) to elaborate instantaneously the production data set with respect to quality/energy/cost prognosis. The client-server Connections, based on OPC_UA protocol that is accepted as Interface for Industry 4.0, are collecting all process data coming from all existing devices and active sensors in a centralized database.

A fundamental innovative characteristic of smart ProdACTIVE tool is the Cognitive predictive quality model integrating multi-resolution and multi-variate process data, monitored and gathered by an articulated network of sensors by means of the collection of distributed control system, advanced models linking process variables to specific defect generation mechanisms, new optimization tools and remote management of production by self-adaptive equipment. The final tool is a smart web application to visualize, share and communicate the significant data and to support the decision making with proper reactions in real-time (retrofit) based on the captured signals from the process and intelligent elaboration of data by the quality model.

smart ProdACTIVE - ICT platform to real-time QUALITY PREDICTION and OPTIMIZATION supported by TRAINED COGNITIVE MODE

MONITORING MODULE

Database
  1. Real-time acquisition DB
  2. Hystorical data storage
Sensors connectivity
Smart Data visualization
History and Traceability
  1. Advanced sensors connection
  2. Web Data elaboration: charts, diagram
  3. Web Visualization: charts, diagram, 3Dviewer, etc.
  4. Thresholds, alarms, apps

COGNITIVE MODULE

Cognitive metamodeling
Re-Active optimization
  1. Cognitive quality model (product model and training methods)
  2. Re-active optimization
  3. Predicted data elaboration & visualization: charts, diagram, 3Dviewer… thresholds, alarms, apps
Energy and Cost model
  1. Energy consumption visualization
  2. Real-time cost elaboration during production
Web-service
  1. Customized connection to MES/ERP
  2. Cloud connectivity and Apps

Main benefits

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  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

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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.

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smart ProdACTIVE

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Insights

CASE STUDY

Integrated Simulation of Commercial Pasta Manufacturing

The Virtual Optimization PAsta production process (OPAV) research project, which resulted in a simulation model

This study was part of the Virtual Optimization PAsta production process (OPAV) research project,

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CASE STUDY

Optimizing the Glass Clamping of a Pyrolytic Oven

An appreciable 30 to 40% decrease in stresses

The aim of this study was to find the best quality glass-clamping system, through parametric model optimization, for a new pyrolytic self-cleaning oven by Indesit.

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Our competences in smart ProdACTIVE

CASE STUDY

Optimizing the cable routing for a hyper-redundant inspection robot for harsh, hazardous environments

A multi-objective optimization framework to reduce the actuation loads and increase the payload

This article discusses a multi-objective optimization study to determine the optimal matrix for the routing of the actuating cable system in order to minimize the cable load on the robot and maximize the robot’s payload.

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CASE STUDY

Optimization techniques applied to centrifugal compressor design

Using RSM to save design time and speed time-to-market

Optimization tools, and specifically response surface methods (RSM), can be adapted very well in the design process to provide information around the design of a compressor stage. This article will cover two of the possible optimization uses: the search of optimum performance and data generation.

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CASE STUDY

Optimizing a cam mechanism using Adam and MATLAB

The design of a cam for high-speed production machines with various operating criteria imposes various conflicting objectives

This technical case study explains the application of a two-step methodology using the MATLAB and Adam algorithms in the modeFRONTIER software platform.

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