Production Automation

Optimising Manufacturing Processes For Better Output

Always Faster, Better, Cheaper and More Customised

The market is forcing factories to constantly look for ways of becoming smarter and leaner to keep up with competition and meet customer needs.

The Production Line Is No Longer The Bottle-neck

Machinery used on the production line is creating an increasing amount of real-time data about the manufacturing process. The focus is turning towards how this data can be used 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 reduce the noise in the data and bring out the most important insights.

Letting Intelligent Machines Support Where They Can

Machine learning can help Engineers take a leap forward in decision making and optimisation. Production processes can become faster, leaner and more efficient as several variables can be controlled at once in real- time.

Production in Industry 4.0

Automate Your Production Line With The Following Features

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 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.

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.

The Digital Transformation

Bring Production Into The New Era

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.

Our Approach

An iterative 3-step process

Prove

1-2 Months

Proof of Concept - Fastest to Goal

To prove the project can be executed a smaller scope quick win will be agreed on. This will enable users to get fast results before committing fully to a large scale project.

Improve

2-8 Months

Fully functional software

Main functionality of the software will be developed and made available to the client for testing.

Autoimprove

4-12 Months

Increased scope and ML independence

Development of additional functionality, process automatisation and modifications to the machine learning (ML) algorithms will be added. At the end of this phase the software will be fully functional.

The Team

Our Experts In Managing Production Projects
Hedi Hunt
Product Manager
Hedi Hunt
Product Manager
Hedi Hunt
Product Manager
Martin Laid
Chief Engineer
Martin Laid
Chief Engineer
Martin Laid
Chief Engineer

We are developers, technologists, operators and engineers who have worked on over 100 projects.

Deep experience in Big Data, Automation and production.

Get in touch to Arrange a demo

We are involved in projects world-wide, just let us know!

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