AI Transformation in Manufacturing
Manufacturers face mounting pressure to decrease costs while continuing to deliver high quality products and service. Leading manufacturers are taking a proactive approach to streamlining operations. Companies that are making extensive use of AI are reaping the benefits of improved efficiency, decreased downtime while increasing customer satisfaction, which adds to their bottom line.

These companies are using AI for a number of scenarios including predictive maintenance, predictive process design, supply chain optimization and more.

Predictive Manufacturing Design

Predictive Maintenance

Suply Chain and Transportation Optimization

The Production Line Is No Longer The Bottle-neck

Machinery used on the production line enables factories to collect an increasing amount of real-time data about the manufacturing process. The focus is turning towards how this data can be harnessed to improve the quality of output.

There Is a Lot of Data, But Little Actionable Information

For data to be actionable it needs to be connected and digitalised. This will help to weed out the noise in the data so it could be analysed and the most important KPIs could be visualised.

Digitalisation is Key for Leveraging Data in Decision-Making

Automation of specific manufacturing processes has brought along a leap in production efficiency worldwide under the term Industry 3.0. The focus of Industry 4.0 is to automate decision making by using precise data from the entire production process.

Harness All Data In Your Enterprise

Every step of the production process and every decision taken by the management can and should be measured. Quite often this data is in analogue form, on paper or in the heads of management, or is only kept within the bounds of a specific manufacturing process. By digitalising the analogue and measuring information from every process step of manufacturing, an overall picture of the enterprise appears. The actual situation awareness is the key that enables fully digitalised enterprises to achieve superior efficiency to their peers.

Eliminate Human Error

Accurate Enterprise Data Analysis

Empower Decision Makers

Improve Accessibility & efficiency

Reduce Operational Costs

Safety of Data Storage

Production Parameter Optimisation

Input and output parameters for production can be significantly improved with the use of data analytics and machine learning applications. The optimisation process enables cutting production costs, increasing time-to-market and decreasing lead times

Predictive Maintenance

For maintaining stable production capacity it’s important to have control systems in place that help to monitor the day-to-day work and eliminate issues using predictive maintenance before they become critical.
Big Data analytics and machine learning can be used to detect defects in the production process before they become apparent to the human eye, therefore providing more time to proactively fix an issue and reducing machinery downtime.

Real-Time Cities and Production Line Improvements

Machine learning applications enable to influence robot movements and parameters in real-time to compensate for differences in robots and other production line fluctuations.
The aim of real-time adjustments is to keep the production output quality constant.

MONITOR ANY ASSET, ON ANY DEVICE, AT ANY TIME

The Mentatronic Platform can connect and collect data from any industrial asset, regardless of brand, age, or process. Reports can be accessed anytime, anywhere through any device with a browser — including desktops, laptops, tablets or smart phones.

Minimally invasive, high-velocity installation means no special engineering required, no additional downloads for user devices, and no additional burden on IT departments.

Scrap Rate Reduction

For keeping the production quality constant, machine learning software can further help reduce waste. It can learn from the reasons why a product was scrapped and make necessary changes in the production process or suggest possible reuses for scrapped products.
Applying Waste Prevention
Connecting Relevant Data Sources
Improving Quality in Real-time
Identifying Influential Processes
Applying Machine Learning
Monitoring Production FTT Rate

Production

Automate production line controlling, use Machine Learning to control and improve process variables.

Quality Analysis

Detect quality defects before they become a cascading problem. Predict quality changes and prevent scrap by adjusting production in real-time.

Supply Chain

Reduce fire-fighting and focus on important issues. Predict solutions before there is a problem with real-time decision making tools.

Management

Real-time KPI dashboards simplifying complex project delivery. No more waiting on reports or analysis, get full transparency and speed up your decision-making.