Case study

ZDMP

A digital platform for connected smart factories for achieving excellence in manufacturing through zero-defect processes and products.

Visit ZDMP

Visit the ZDMP website in order to learn more about the project.

What is ZDMP?

ZDMP aims at providing an extendable platform for supporting factories with a high interoperability level to cope with the concept of connected factories to reach the zero defects goal. In this context, ZDMP will allow end-users to connect their systems (i.e. shopfloor and ERP Systems) to benefit from the features of the platform. These benefits include products and production quality assurance among others. The concept of ZDMP can be simplified to a feedback and control system found in areas ranging from human/autonomous driving through to electronics. Steering the system will be the ZDMP apps composed using the projects SDK and different components. Broadly these receive (and present/actuate) information from sensors/APIs and then process the data.

About CALM

Zero-defects concept focuses on minimising the mistakes both due to humans and machines. Mental and physical states such as stress and fatigue as well as human mistakes such as account sharing, forgetting to log out are a few of the sources of human error. CALM will tackle these sources of human error by introducing continuous behavioural analysis into the Zero-defects concept. Continuous behavioural authentication combined with a higher level of behavioural analysis and anomaly detection will automatically and in real-time prevent potential defects in the production line. CALM will predict and reduce defects, increase safety and productivity as well as reduce costs and waste.

Objectives

The CALM project objectives are summarised into:

  • Research and develop an AI-powered behaviour analysis component.

  • Develop an anomaly detection mechanism based on users’ behaviour.

  • Disseminate and ensure the sustainability of the product.

Benefits to the Zero Defects Manufacturing

CALM will provide two-fold benefits to end-users as well as to ZDMP, both in terms of safety and cybersecurity.

In terms of safety, CALM will help ZDMP:

  1. early detect production line disruptions by predicting medium-long term behaviour anomalies and short-term mental conditions,

  2. improve the well-being of the workers by better understanding their mental state through behavioural patterns,

  3. improve the productivity and reduce human error of the ZDMP stakeholders, as they do not have to manually measure and understand the mental state and behaviour changes of the workers,

  4. reduce accidents for workers by detecting when they operate machinery under dangerous mental state.

In terms of cybersecurity, continuous behavioural authentication will benefit ZDMP:

  1. empower security as it combines multiple biometrics and behavioural patterns, eliminating the errors of each individual method,

  2. easiness-to-use as the system does not require any user input; a factor particularly important for manufacturing,

  3. strengthen privacy as the workers, become sole owners and having full control over their personal data and

  4. protect Intellectual Property against IP theft and fraud through the use of behavioural authentication.


Consortium

The ZDMP project constitutes of a large consortium of prestigious partners from 11 different European countries including research institutes, solution providers, integrators, manufacturers and small and large industrial organisations. Among them are the following organisations:

  • SIMAVI a large integrator across multiple sectors including manufacturing, banking, defence etc. medical devices
  • Continental a huge manufacturer for sustainable and connected mobility of people and their goods
  • Ford an American multinational automobile manufacturer
  • Tampere University is one of the most multidisciplinary universities in Finland

This project has received cascading funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 825631.