Disrupting the Manufacturing Industry and Public Institutions with
Artificial Intelligence Technologies
Vega Research Laboratories
Industries profit from AI in industrial operations in a number of ways. From automating IT and business to improving customer service and resolving workforce shortages, the technology-driven world provides limitless options for cost-effective development. Machine learning algorithms enhance efficiency, decrease downtime, and allow predictive maintenance by studying historical performance indicators and real-time sensor data.
In the industrial and smart city fields, VRLabs has successfully applied artificial intelligence and data analytics to circular economies in WEEE, pallet unstacking, prognostic maintenance, warehouse optimization, and team resource management.
Supporting customers in the last step of digitization
VRLabs supports Industry 4.0, innovation and investments in new tech
applying Artificial Intelligence for
- Preventive Maintenance
- Predictive demand analysis
- Inventory Management
- Key Performance Indicators Modeling
- Optimization of production
- Factory data analytics
AIRAW project
Through various processes in most industries, such as maintenance, reuse, recycling, and composting, the circular economy aims to prevent waste and restore nature.
By setting targets to meet material demand in the EU, recycling has been identified as a key contributor to the security of raw material supply.
AIRAW demonstrates how such AI technology applied to multiple recycling applications can effectively benefit the entire EU recycling ecosystem.
Printed circuit boards (PCBs) are an essential component of electronic devices we use every day, such as computers, televisions, smartphones, and laptops. Manufacturing Electric and Electronic Equipment (EEE) requires a substantial amount of materials, including Critical Raw Materials (CRM).
AIRAW project aims at closing the technological gap of sorting and identifying CRMs from WEEE by introducing in the market an Automatic Optical Inspection (AOI) system that embeds a proprietary Artificial Intelligence and Machine Learning algorithm and therefore offers a new tool to increase the recycling percentage of CRMs and enhance the EU Circular Economy.
In particular, such technology will help industries recover a higher number of different materials efficiently and use CRMs.
Fully customized AI solutions
Vega Research Laboratories delivers strong expertise gained in different industries.
CRMs recovery with using Artificial Intelligence and Machine Learning
Problem: About waste electrical and electronic equipment seeks to reduce the environmental impacts of WEEE
Solution Proposed: AIRAW project introduces an Automatic Optical Inspection (AOI) system to increase the recycling percentage of CRMs and enhance the EU Circular Economy.
Result:
VRLabs productized a highly accurate AI tool that can identify >90% of the components of scrapped PCBs and sort them within the recycling process
Savings in Inventory Management costs by increasing efficiency
Problem: Usuallly Inventory Management needs long manual fixing of item as MTS/MTO Success Stories.
Solution Proposed: VRLabs developed a dedicated Machine Learning Algorithm to optimize Inventory Management
Result:
Classification of item as MTS/MTO reached high accuracy
large savings in operating costs
Failure Prediction from Engine Control Unit Data (CUD)
Problem: Need to define an efficient way to predict typology of failure using CUD in the next three months
Solution Proposed: VRLabs proposed a sequencial classification technique based on Neural Network
Result:
High accuracy of multi-type of failure in the assigned temporal frame, Savings in post-sale interventions
AI-based inventory classification
Problem: Deciding whether particular pieces of equipment or replacement parts should be kept in stock MTS (Make to Stock) or ordered when actually required MTO (Make to Order)
Solution Proposed: Machine learning model trained according to a historical track record
Result:
The proposed AI technique achieves a large classification accuracy greater than 96%
Success Stories
- We developed a dedicated Machine Learning Algorithm to optimize Inventory Management
- Neural networks estimators for nonlinear process modeling in industrial context
- Predictive maintenance of industrial plants and devices
- Neural networks regressors for electronic noses for food qualification industry