data management

A study by the German Academy of Science and Engineering (acatech) indicates that artificial intelligence (AI) is of growing importance for the success of manufacturing companies [1]. The emerging, data-driven solutions in the manufacturing field are highly diverse, both in terms of the processes and the locations (different factories, factory sub-areas, etc.) where these solutions are implemented. Often the solutions are also hardly scaled beyond the limits defined in the pilot project. When such an AI project ends, the goals of a use case are fulfilled, but this often results in another isolated solution being added to the company’s established IT system landscape. The data this solution delivers is not further used, and complex maintenance requirements negate any gains in efficiency.

The need to sometimes respond very quickly to changes requires companies to have a high degree of flexibility and speed of reaction. Application system architectures, which usually consist of old and self-developed systems, often do not allow companies to meet these requirements. However, investment funds for new software are limited, so priorities must be set when it comes to replacing legacy systems. An adaptability analysis is an efficient analysis method for planning the renewal of the application system landscape. This article describes the procedure and results of an adaptability analysis, using the example of an internationally active automotive supplier.

The digitalization in sustainability management and the creation of a consistent database for sustainability data can significantly support companies in meeting increasing sustainability requirements and transparency regarding the sustainability performance. This paper presents a service-oriented approach for the development of a platform for data-driven sustainability management in manufacturing companies.

Implementing Industry 4.0 as the digital Agenda in all manufacturing industries and thereby increasing the competitiveness is a matter of course and clearly also applicable for the food and beverage industry. With altering customer behaviours, legal requirements as well as the increasing specialization, the industrial sectors are facing continuous challenge. Even though the automation of facilities in many cases is already put into practice, the structured integration into a holistic data concept is often missing. Through the digital networking of all processes, innovative solutions are on offer. What does Industry 4.0 mean for the food and beverage industry, where the opportunities lie and which specific implementation measures are available is subject to this article.