Industry 4.0 represents a novel paradigm centered around digital factories, capa-ble of integrating information technologies and machines with intelligent prod-ucts. In this context, this article addresses the added monetary value resulting from adopting Industry 4.0 technologies in the development of a scraped surface heat exchanger equipment. This research aims to estimate the added value of a technology-based redesign of a food processing machine, considering the will-ingness to pay. The methodology employed to evaluate the integration of these technologies into the product is based on the Stated Preference (SP). The findings reveal a hierarchy among the enhancement opportunities that Industry 4.0 tech-nologies bring to the product. Consequently, in this case, incorporating features from Industry 4.0 that encompass the maintenance aspects contributes significant-ly to the product's value.

Digital twins play an essential role in manufacturing companies to adopt Industry 4.0. However, their uptake has been lagging, especially in European manufacturing firms. This can be attributed to the absence of automated methods for digitizing physical manufacturing resources and creating digital representations accessible and processable by both humans and computers. Our research addresses this challenge by automating the digitization of manufacturing resources captured on the shop floor. We employ object detection techniques on a set of images and align the results with an ontology that standardizes the semantic description of digital representations. This research aims to accelerate digital transformation for manufacturing companies, providing digital representations to their physical resources. The ontology-based digital representation fosters interoperability among diverse equipment and machines from various vendors. It enables the automated deployment of digital twins, improving the efficiency of planning and control of manufacturing systems.

The convergence of Value Stream Management with cutting-edge technologies represents a dynamic area of research, as underscored by recent studies. These studies reveal a growing emphasis on digitalization and share a common goal: proposing data-driven techniques to enhance and optimize conventional Value Stream Management struggling to adapt in rapidly changing environments. By the present paper, a digital Value Stream Map according to the Digital Twin (DT) concept is investigated. This Digital Value Stream Twin (DVST) is based on the orchestration of multiple DT, representing core elements of Value Stream Management such as material flowing through the value stream and related resources. Overcoming the fixed structure of the automation pyramid, business application systems and machine signals are merged as data sources into one model, verified by a business scenario, mainly carried out in an SAP S4/HANA (ERP - enterprise resource planning) test environment. In this context, the present study is built upon a validation using a digital value stream model according to the Digital Shadow (DS) approach. Conceptually, the expansion of the DS into a DT is described. From this, potentials regarding the value stream method are derived and investigated.