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Artificial Intelligence in Industry and Manufacturing

Industry

IA en IndustriaAI in Industry

AI tailored to your business: better decisions, greater efficiency, higher profitability

Decision Intelligence adapts to your business, optimising strategic, tactical, and operational decisions to reduce costs by 5% to 20% and improve profitability. From process optimisation and production planning to supply chain improvement and energy consumption reduction.

value chainSee how our Decision AI optimises every stage of the value chain.

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Suppliers and raw material sourcing
1
Production and manufacturing
2
Inventory and storage management
3
Logistics and distribution
4
Commercialisation and sales
5
After-sales service and support
6

Suppliers and supply of raw materials

Production and manufacturing

Inventory and storage management

Logistics and distribution

After-sales service and support

Transition to renewable energy and sustainability

E-book: AI in Industry and ManufacturingSubmit your download request

This e-book edition is limited. Each request will be reviewed individually, and one copy will be sent per verified profile until all available units have been distributed.

Submit your download request.

This ebook edition is limited. Each request will be reviewed individually, and one copy will be sent per verified profile until the available units run out.

Use casesSome use cases

Discover how our solutions have improved efficiency and optimised operations in the energy sector.

Warehouse layout optimisation with Decision AI

  • Industry: Automotive
  • Challenge: Improve operational efficiency and reduce storage costs at a multinational in the automotive sector.
  • Approach: Implementation of Decision AI to simulate and optimise warehouse layouts, maximising efficiency and reducing costs.
  • Results: The new layout led to an 18% reduction in operational costs and a 12% improvement in order processing times.
  • Key Metrics:
    18% reduction in operational costs.
    12% increase in processing efficiency
0 %
Reduction in operational costs

Logistics transport optimisation with Decision AI

  • Industry: Logistics
  • Challenge: Reduce travel times and operational costs by optimising employee transport route planning in a multinational company.
  • Approach: Implementation of Decision AI to optimise transport routes in real time, considering traffic, weather, and schedules.
  • Results: Achieved a 20% reduction in transport costs and improved employee satisfaction due to shorter travel times.
    Key Metrics:
    – 20% reduction in transport costs | Improved employee satisfaction.
0 %
In transport costs

Supply planning to prevent stockouts

  • Industry: Retail
  • Challenge: A major retail chain faced recurring stockouts, negatively impacting sales and customer satisfaction.
  • Approach: Use of Decision AI tools to forecast demand and optimise inventories, ensuring product availability.
  • Results: The company reduced stockouts by 15%, leading to increased sales and a significant improvement in customer satisfaction.
  • Key Metrics:
    – 15% reduction in stockouts
    Increase in sales and customer satisfaction.
0 %
In stockouts.

Supply chain optimisation in industrial gas production

  • Industry: Industrial Gas Production.
  • Challenge: A leading industrial gas producer faced supply chain planning challenges, resulting in high costs and downtime.
  • Approach: Implemented an optimisation system analysing the entire supply chain, from production to distribution, identifying improvement areas and automating key decisions.
  • Results: The company achieved reduced planning times, saving between €300,000 and €500,000 annually per plant.
  • Key Metrics:
    Savings of up to €500,000 annually per plant.
    Reduced planning times.
0 €
Ahorro anual por planta

NewsNews and trends in AI applied to industrial processes, production, and supply chain

Explore how Decision AI has generated savings of up to €500,000 annually by optimizing industrial production.

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    • Power Generation

    Activa DecisionAI
    • How to optimize production to reduce costs and maximize efficiency?
    • How to anticipate infrastructure failures to avoid unexpected outages?
    • How can we improve renewable energy forecasting to stabilize supply?
    • How can infrastructure (wind farms, solar farms, production plants) be planned and optimized to obtain the most energy at the lowest cost?

    Added value of AI and analytics:

    • Production optimization: ML models adjust production based on demand and resource availability.
    • Predictive maintenance: IoT sensors and algorithms anticipate failures in generating infrastructure.
    • Renewable energy forecasting: Advanced climate models improve solar and wind energy forecasting.

    Problems solved:

    • Inefficiency in energy production, which generates additional costs.
    • Unexpected failures in generating plants, which affect the stability of supply.
    • Variability in renewable generation, improving the integration of intermittent sources.
    Contact Us

    Suppliers and supply of raw materials

    Activate DecisionAI
    • How to select optimal suppliers to ensure quality and reduce costs?
    • How to anticipate supply chain disruptions to avoid stockouts?
    • How to automate orders and adjust purchases based on actual demand?

    Added value of AI and analytics:

    • Supplier selection optimization: Models based on historical data analyze delivery times, input quality, and costs to recommend optimal suppliers.
    • Supply chain disruption prediction: Machine learning analyzes geopolitical risks, market trends, and global demand to avoid supply crises.
    • Order automation: Prescriptive systems automatically adjust purchasing levels based on demand projections and production cycles.

    Problems solved:

    • Inefficient purchasing planning, leading to cost overruns and inventory imbalances.
    • Excessive dependence on a single supplier, mitigating risks with diversified sourcing strategies.
    • Lack of visibility in the supply chain, preventing disruptions and production downtime.
    Contact Us

    Production and manufacturing

    Activate DecisionAI
    • How can you optimize production planning to reduce waste and improve efficiency?
    • How can you anticipate machine failures to avoid unscheduled downtime?
    • How can you ensure product quality at every stage without increasing costs?

    Added value of AI and analytics:

    • Predictive maintenance: Algorithms that analyze sensor data to anticipate machine failures before they occur, avoiding unscheduled downtime.
    • Production line optimization: Operational research models optimize resource allocation, reducing downtime and improving efficiency.
    • Quality control with computer vision: AI systems inspect products in real time, detecting defects without human intervention.

    Problems solved:

    • High rates of defective products, which generate losses and affect brand reputation.
    • Low production efficiency, where downtime and poor planning affect profitability.
    • Lack of preventative maintenance, which increases the risk of catastrophic machinery failure.
    Contact Us

    Inventory and storage management

    Activate DecisionAI
    • How can stock levels be optimized to avoid overstocking or shortages?
    • How can materials be distributed within the warehouse to reduce picking times?
    • How can order picking be automated to optimize productivity?

    Added value of AI and analytics:

    • Optimización de niveles de inventario: algoritmos de predicción ajustan los niveles de stock con base en demanda futura y capacidad de producción.
    • Automatización del picking y almacenamiento: robots y sistemas guiados por IA optimizan la distribución de materiales dentro del almacén.
    • Análisis de rotación de productos: machine learning identifica patrones de consumo y recomienda ajustes en la logística interna.

    Problems solved:

    • Oversupply of materials, increasing operating costs and risk of waste.
    • Lack of inputs at critical times, affecting operational continuity.
    • Inefficient manual processes, slowing down the production chain and increasing labor costs.
    • Key decisions: optimizing warehouse layout, forecasting demand.
    Contact Us

    Logistics and distribution

    Activate DecisionAI
    • How can you reduce costs and transportation times by optimizing distribution routes?
    • How can you predict geographic demand to improve product distribution?
    • How can you ensure real-time tracking and control of shipments?

    Added value of AI and analytics:

    • Distribution route optimization: Algorithms determine the best delivery routes to minimize transportation times and costs.
    • Predictive geographic demand analysis: Machine learning identifies purchasing patterns by region to improve product distribution.
    • Real-time monitoring: IoT sensors and analytical models allow order tracking at every stage of the supply chain.

    Problems solved:

    • High costs due to inefficient transportation, optimizing routes and loads.
    • Lack of control over delivery times, improving predictability and customer satisfaction.
    • Low response capacity to unforeseen events, reducing risks with real-time, adaptable logistics.

    After-sales service and support

    Activate DecisionAI
    • How can you automate customer service to improve response times and efficiency?
    • How can you reduce return rates by analyzing product failure patterns?
    • How can you optimize warranty management to streamline processing and reduce costs?

    Added value of AI and analytics:

    • Customer service automation: Chatbots reduce operational burden and improve response speed.
    • Pattern detection in returns: AI analyzes the most common causes of product failures.
    • Warranty management optimization: Algorithms classify and process claims more efficiently.

    Problems solved:

    • Slow customer service, improving response times.
    • High return rates, identifying products with recurring defects.
    • Poor warranty management, optimizing their processing.
    Contact Us

    Transition to renewable energy and sustainability

    Activa DecisionAI
    • How can we integrate renewable energy without compromising supply stability?
    • How can we optimize investment in clean energy to accelerate the energy transition?
    • How can we manage microgrids and balance supply between renewable and conventional sources?

    Added value of AI and analytics:

    • Solar and wind generation prediction: Machine learning analyzes weather patterns to improve renewable energy integration.
    • Clean energy investment optimization: Financial models suggest the best adoption strategies.
    • Microgrid management systems: Decentralized algorithms balance supply between renewable and conventional sources.

    Problems solved:

    • Lack of grid stability with renewables, improving energy integration.
    • High energy transition costs, optimizing investment.
    • Low adoption of clean energy, incentivizing profitable production models.
    Contact Us