End User

Your lines always under control, with Line Monitoring.

Compare the efficiency and KPIs of all your lines at a glance, even across multiple plants worldwide! Know the performance of each machine and find out whether there is any ongoing downtime. All in real-time and via dashboard in three modes!

Grid

List

Map

Production lines efficiency, in real time.

Complete visibility into the operation of each line.

What is the line producing? Are the process parameters under control? Which machine stops occurred yesterday? How long did the last format changeover last? All this and much more, in Line Supervision.

Line Status Batch and current recipe information.

Process variables and setpoints on 3D renders or images, also with hierarchical navigation.

History Of line stops, with causal details.

Gantt About the evolution of line states over time.

Lean Analytics 4.0

The identification of efficiency losses goes through the calculation and analysis of KPIs.

01.

OEE Analytics

What was the OEE line this week? What is the availability of the packaging machine for recipe 4?

02.

Production Trend

What is the difference between actual and expected production? Is it a problem of poor quality, low speed, or machine availability? Identify production losses and their cause.

03.

Production Traceability

Track and analyze production quantities, KPIs and critical events for each shift or production batch. Set time filters and export data in popular formats.

04.

Breakdown Analysis

What is the faults cause responsible for the most downtime? What is the shift in production where faults are most common?

01.

OEE Analytics

What was the OEE line this week? What is the availability of the packaging machine for recipe 4?

02.

Production Trend

What is the difference between actual and expected production? Is it a problem of poor quality, low speed, or machine availability? Identify production losses and their cause.

03.

Production Traceability

Track and analyze production quantities, KPIs and critical events for each shift or production batch. Set time filters and export data in popular formats.

04.

Breakdown Analysis

What is the faults cause responsible for the most downtime? What is the shift in production where faults are most common?

sustainability

monitoring

Digital in the service of sustainability.

Do you know how to calculate the production cost per unit of material? Monitor consumption of electricity, compressed air, water, raw material.Optimizing this cost and its variations is fundamental to project your company into the future and ensure the sustainability of your plants.

Digital in the service of sustainability.

Do you know how to calculate the production cost per unit of material? Monitor consumption of electricity, compressed air, water, raw material.Optimizing this cost and its variations is fundamental to project your company into the future and ensure the sustainability of your plants.

Digital in the service of sustainability.

Do you know how to calculate the production cost per unit of material? Monitor consumption of electricity, compressed air, water, raw material.Optimizing this cost and its variations is fundamental to project your company into the future and ensure the sustainability of your plants.

Digital in the service of sustainability.

Do you know how to calculate the production cost per unit of material? Monitor consumption of electricity, compressed air, water, raw material.Optimizing this cost and its variations is fundamental to project your company into the future and ensure the sustainability of your plants.

83% / Quality

Predictive Quality

Artificial intelligence can help you minimize waste by guiding your operators in setting up machines.

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02

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Measure.

The first step is the scraps analysis: what are scraps causes with the highest incidence? Which line has the lowest quality? Is there a correlation between low quality and type of item produced?

Understand.

The predictive quality model helps you understand which variables impact product quality, during which process step, and in what way. Today's manufacturing processes are characterized by thousands of quantities that relate to each other. Only a supervised machine learning model can help you explain these relationships.

Raw materials characteristics

Environmental Conditions

Process variables

Machine Faults

Recipe/program parameters

Optimize.

Use the predictive model online, during production, as an aid to operators to reduce scraps under any conditions. The model can suggest the optimal machine parameterization at any time to maintain high levels of quality and productivity.

Quality.

Manual Settings.

Codified corporate knowledge.

Your machines are perfect for MAT.

Contact us now. We'll set up a meeting as soon as possible.