Volume 65, Issue 3 - Thematic Issue: IoPT: Internet of Processes and Things; Guest Editor: Christoph Pollak; Host Editor: Stefanie Rinderle-Ma

In the course of efforts to develop and define uniform routines for the implementation of Internet of Things (IoT) in industrial environments, it has become essential to integrate industrial communication standards such as OPC UA in the context of IoT ontologies and implications for practical implementation. The Sensor, Observation, Sampling, and Actuator Ontology (SOSA) offers the possibility of mapping OPC UA services such as read and write functions to the underlying system in the sense of IoT. As an aid for the practical implementation of industrial use cases, an architecture based on the considerations of a generic modular system is proposed. Variable elements in the implementation of OPC UA interfaces are identified and discussed. The architectural approach is being evaluated by implementing an OPC UA server and supplementary applications in order to embed machine tools with different control systems in industrial production networks.

Successful and profitable companies in the 21st century have to integrate and adapt modern technologies to reach productivity and sustainability goals. While large enterprises have the resources (human, knowledge, and technology) to incorporate automation hardware and the required computational means to support automation, for small and medium enterprises (SMEs) finding the necessary resources is much more difficult. Even though benefits from such modifications are obvious (i.e., gain new clients, improve current process performance or break into new market), SMEs often lack the human resources and knowledge to implement automation. With the development of the Internet of Things (IoT), devices, sensors and platforms are becoming more affordable and available for companies and businesses, that are not connected with IT technologies, industrial sector, etc. In order to simplify automation for SMEs, simple and standardized integration procedures and best practice examples are important. In this paper we propose the concept and design of a smart bar system that is based on the Internet of Processes and Things (IoPT) concept which is able to prepare and serve drinks to clients based on smart features.

Digital transformation affects many aspects of our everyday lives. This paper focuses on challenges and opportunities in the area of factory automation. It presents the layout and components of the Pilotfabrik Industrie 4.0 of TU Wien as an example of a modern, flexible, and highly digitized smart factory. Furthermore, the paper presents use cases that were implemented based on the available IoPT devices in the Pilotfabrik Industrie 4.0. The first use case aims to improve product quality by detecting chatter – a vibrational phenomenon in machine tools – and taking appropriate countermeasures. The second use case tries to predict tool breakage by closely monitoring the power consumption of the machine tool and, thus, reducing the probability of damaged products.

Digital transformation is both an opportunity and a challenge. To take advantage of this opportunity for humans and the environment, the transformation process must be understood as a design process that affects almost all areas of life. In this paper, we investigate AI-Based Self-Adaptive Cyber-Physical Process Systems (AI-CPPS) as an extension of the traditional CPS view. As contribution, we present a framework that addresses challenges that arise from recent literature. The aim of the AI-CPPS framework is to enable an adaptive integration of IoT environments with higher-level process-oriented systems. In addition, the framework integrates humans as actors into the system, which is often neglected by recent related approaches. The framework consists of three layers, i.e., processes, semantic modeling, and systems and actors, and we describe for each layer challenges and solution outlines for application. We also address the requirement to enable the integration of new networked devices under the premise of a targeted process that is optimally designed for humans, while profitably integrating AI and IoT. It is expected that AI-CPPS can contribute significantly to increasing sustainability and quality of life and offer solutions to pressing problems such as environmental protection, mobility, or demographic change. Thus, it is all the more important that the systems themselves do not become a driver of resource consumption.

Modern technologies such as the Internet of Things (IoT) are becoming increasingly important in various fields, including business process management (BPM) research. An important area of research in BPM is process mining, which can be used to analyze event logs e.g., to check the conformance of running processes. However, the data ingested in IoT environments often contain data quality issues (DQIs) due to system complexity and sensor heterogeneity, among other factors. To date, however, there has been little work on IoT event logs, DQIs occurring in them, and how to handle them. In this case study, we generate an IoT event log, perform a structured data quality analysis, and describe how we addressed the problems we encountered in pre-processing.