The manufacturing sector faces an intense and growing competitive pressure in global markets and has to address the challenge of producing customized products with low cost, energy, and waste. Manufacturing today and in the future has to meet a constantly increasing demand for consumer goods. One of the enabling technologies that could help to meet the requirements and to improve the competitiveness is information and communication technology (ICT). ICT offers the manufacturing a high degree of autonomy and adaptability for a balanced combination of high throughput and high accuracy production. The ICT methods and technologies such as artificial intelligence and effective human computer interaction technology offer the capabilities to perform smart interactive simulations that can support the manufacturing stakeholders in decision making.

Knowledge engineering consisting of knowledge representation (ontologies, rule base), knowledge acquisition (data mining, digitalization of real manufacturing environment), and reasoning is a core method to develop an artificial intelligent system. An effective HCI is also essential in order to make the developed intelligent system more usable for the manufacturing stakeholders. There are different technologies of HCI applicable for factory of the future, such as Cave automatic virtual environment (CAVE), desktop Virtual Reality (VR), mobile VR, mobile Augmented Reality (AR), etc.

Objective:

The main objective of this diploma thesis is to develop knowledge engineering (knowledge base representation and data mining), digitalization and human computer interaction concept for factory of the future to improve efficiency, adaptability and sustainability of manufacturing 

Work content:

This thesis consists of the following work:

• Analysis of objectives and general requirements of factory of the future, and the role of knowledge engineering, digitalization, HCI, and other related systems in the factory of the future
• Analysis of different knowledge representations that allows intelligent reasoning, such as ontologies, rules, frames, semantic networks, etc.
• Analysis of data mining algorithms (clustering, classification, association, etc.) for the knowledge acquisition from data in existing IT systems by considering the integration with the chosen knowledge representation.
• Analysis of digitalization technologies to transform the real environment to the digital/virtual environment and integration to the knowledge base, for example 3D-scanning using Kinect camera and transformation of CAD files into ontologies, etc.
• Analysis of HCI technologies to allow the user interaction to the intelligent system, for  example, CAVE, desktop VR, mobile VR, mobile AR, etc.
• Development of knowledge engineering, digitalization and human computer interaction (HCI) concept based on the strength and weakness identified in the analysis phase
• Development of integration concept and communication interface (SOAP,REST, proprietary protocols) between the involved systems
• Verification of the developed concept
• Documentation and presentation of the results