Framework for Context-Sensitive Dashbords Enabling Decision Support on Production Shop Floor

The advancing digitalization of production means that a large amount of data and information is being collected. Used correctly, these represent a significant competitive advantage. Decision support systems (DSS) can help to provide employees with the right information at the right time. Context-sensitive dashboards in the sense of decision support have the potential to provide employees on the shopfloor with information according to their needs. Within the scope of this work, a framework for the determination of the context-sensitive information needs of the staff on the shopfloor was developed. The goal was to reduce the development and adaptation effort of a context-sensitive application by classifying activities with similar information needs in advance. According to the methodology, the information needs of the employees are first analyzed and activities are summarized in terms of their general information needs. Subsequently, the information needs are weighted in order to prioritize them with regard to the processing and selection of information. The context-sensitive dashboard was then implemented using a user-centric approach to achieve a high level of user acceptance. The developed prototype, including architecture and design, was then tested and evaluated by experts. Three scenarios were compared in which experts were asked to assess the information requirements for employees in production. These results were then compared with the results of the framework. The comparison showed that for two of the three scenarios, the weighting determined in the framework matched the experts' assessments to a high degree. These general scenarios show that it is possible to generate context-sensitive dashboards based on demand using the developed framework. If the activities become more specific, it became apparent that further developments of the framework are necessary to cover the corresponding information needs. For this purpose, an iterative application to further scenarios and subsequent implementation in the framework seems to be purposeful

Business Intelligence in Industry 4.0: State of the art and research opportunities

Data collection and analysis have been at the core of business intelligence (BI) for many years, but traditional BI must be adapted for the large volume of data coming from Industry 4.0 (I4.0) technologies. They generate large amounts of data that need to be processed and used in decision-making to generate value for the companies. Value generation of I4.0 through data analysis and integration into strategic and operational activities is still a new research topic. This study uses a systematic literature review with two objectives in mind: understanding value creation through BI in the context of I4.0 and identifying the main research contributions and gaps. Results show most studies focus on real-time applications and integration of voluminous and unstructured data. For business research, more is needed on business model transformation, methodologies to manage the technological implementation, and frameworks to guide human resources training

Proceedings of the 4th Workshop on Awareness and Reflection in Technology Enhanced Learning. In conjunction with the 9th European Conference on Technology Enhanced Learning: Open Learning and Teaching in Educational Communities

Awareness and reflection can be viewed from the differing perspectives of the disciplines informing Technology-Enhanced Learning, such as Psychology, Educational and Learning Sciences, or Computer Science. A common denominator can be identified, though, and enhancing ’awareness’ of learners and other participants involved in learning processes by technology means augmenting formal or informal learning experiences, typically in real-time, with information on progress, presence, outcomes, workspace, and the like. Supporting ’reflection’ then means enabling learners to capture, adapt, re-evaluate, and share experience in anticipation of future situations it will prove relevant to. Reflection supported digitally is a creative act, adding sense and meaning to experiences made. Combining support for 'awareness' and 'reflection' bears huge potential for improving the learning and training with respect to utility, self-regulation, usability, and user experience. The ARTEL workshop series brings - for the 4th time in 2014 - together researchers and professionals from different backgrounds to provide a forum for discussing the multi-faceted area of awareness and reflection. For this year 2014, the workshop organizes discussion and meta-reflection amongst researchers around the application of awareness and reflection in practice, its impact on learners and questions of feasibility, and sustainability for awareness and reflection in education and work. This year's workshop theme is: How does computer-support for awareness and reflection need to be embedded into practical (working or learning) contexts in order for learners to benefit from such computer support

Integrated collaborative tools for precast supply chain management

Precast construction projects are associated with many activities, numerous parties, enormous effort, and different processes. For effective communication, this requires delivering appropriate and up-to-date information to enhance collaboration and improve integration. The purpose of this paper is to develop the system architecture and prototype of Context-Aware Cloud Computing Building Information Modelling (CACCBIM) for precast supply chain management. The findings of this research are grounded on the literature of cloud computing, context-awareness, building information modelling, and, ultimately, the analysis of interviews with stakeholders in precast construction. Findings determine that lack of integration, improper planning and scheduling, poor production timing, poor coordination, lack of good communication among parties, wrong deliveries, and poor control and supervision are the major issues within the precast supply chain. These issues could result in adverse consequences for the objectives and success of the precast project. Eventually, to reduce and eliminate these issues, the proposed prototype will support appropriate deliveries, efficient monitoring, facilitation of coordination, and collaboration with improved communication. It is anticipated that this research will establish a unique perception in the precast construction industry, which will finally enhance its productivity, improve its efficiency, and maximise its effectiveness

The reception pattern of the balanced scorecard: accounting for interpretative viability

‘The role of fads and fashions in shaping management accounting practices in contemporary organizations requires further inquiry’ (Malmi, T. (1999). Activity based costing diffusion across organizations: an exploratory empirical analysis of Finnish firms. Accounting, Organizations and Society, 24, 669). Against the background of the evolving management fashion literature we discuss the ‘reception pattern’ of the Balanced Scorecard (BSC) in the Netherlands. To get insight into the organizational changes induced by and associated with the BSC-discourse, we systematically discovered how the concept, since its launch by Kaplan & Norton (1992), has grown into an umbrella that encompasses a variety of interpretations and uses. The paper offers a framework to show how BSC-discourse and its actual use have developed in interrelated yet loosely coupled ways.

Situation Management with Complex Event Processing

With the broader dissemination of digital technologies, visionary concepts like the Internet of Things also affect an increasing number of use cases with interfaces to humans, e.g. manufacturing environments with technical operators monitoring the processes. This leads to additional challenges, as besides the technical issues also human aspects have to be considered for a successful implementation of strategic initiatives like Industrie 4.0. From a technical perspective, complex event processing has proven itself in practice to be capable of integrating and analyzing huge amounts of heterogeneous data and establishing a basic level of situation awareness by detecting situations of interests. Whereas this reactive nature of complex event processing systems may be sufficient for machine-to-machine use cases, the new characteristic of application fields with humans remaining in the control loop leads to an increasing action distance and delayed reactions. Taking human aspects into consideration leads to new requirements, with transparency and comprehensibility of the processing of events being the most important ones. Improving the comprehensibility of complex event processing and extending its capabilities towards an effective support of human operators allows tackling technical and non-technical challenges at the same time. The main contribution of this thesis answers the question of how to evolve state-of-the-art complex event processing from its reactive nature towards a transparent and holistic situation management system. The goal is to improve the interaction among systems and humans in use cases with interfaces between both worlds. Realizing a holistic situation management requires three missing capabilities to be introduced by the contributions of this thesis: First, based on the achieved transparency, the retrospective analysis of situations is enabled by collecting information related to a situation\u27s occurrence and development. Therefore, CEP engine-specific situation descriptions are transformed into a common model, allowing the automatic decomposition of the underlying patterns to derive partial patterns describing the intermediate states of processing. Second, by introducing the psychological model of situation awareness into complex event processing, human aspects of information processing are taken into consideration and introduced into the complex event processing paradigm. Based on this model, an extended situation life-cycle and transition method are derived. The introduced concepts and methods allow the implementation of the controlling function of situation management and enable the effective acquisition and maintenance of situation awareness for human operators to purposefully direct their attention towards upcoming situations. Finally, completing the set of capabilities for situation management, an approach is presented to support the generation and integration of prediction models for predictive situation management. Therefore, methods are introduced to automatically label and extract relevant data for the generation of prediction models and to enable the embedding of the resulting models for an automatic evaluation and execution. The contributions are introduced, applied and evaluated along a scenario from the manufacturing domain

OpenFog-Compliant Application-Aware Platform: A Kubernetes Extension

Distributed computing paradigms have evolved towards low latency and highly virtualized environments. Fog Computing, as its latest iteration, enables the usage of Cloud-like services closer to the generators and consumers of data. The processing in this layer is performed by Fog Applications, which are decomposed into smaller components following the microservice paradigm and encapsulated into containers. Current state-of-the-art container orchestrators can manage hundreds of simultaneous containers. However, Kubernetes, being the de facto standard, does not consider the application itself as a top-level entity, which limits its orchestration capabilities. This raises the need to rearchitect Kubernetes to benefit from application-awareness, which refers to an orchestration method optimized for managing the applications and the set of components that comprise them. Thus, this paper proposes an application-aware and OpenFog-compliant architecture that manages applications as first-level entities during their lifecycle. Furthermore, the proposed architecture allows the definition of organizational structures to group subordinated applications based on user-defined hierarchies. This logical structuring makes it possible to outline how orchestration should be shaped to reflect the operating model of a system or an organization. The proposed architecture is implemented as a Kubernetes extension and provided as an operator.This research was funded by the project PES18/48 funded by the University of the Basque Country (UPV/EHU) and by the PhD fellowship granted under the frame of the PIF 2022 call funded by the University of the Basque Country (UPV/EHU), grant number PIF22/188

Integrated Collaborative Tools for Precast Supply Chain Management

Precast construction projects are associated with many activities, numerous parties, enormous effort and different processes. For effective communication, this requires delivering appropriate and up-to-date information to enhance collaboration and improve integration. The purpose of this paper is to develop the system architecture and prototype of Context-Aware Cloud Computing Building Information Modeling (CACCBIM) for precast supply chain management. The findings of this research are grounded through the literature of cloud computing, context-awareness, building information modeling and, ultimately, the analysis of interviews with stakeholders in precast construction. Findings determine that lack of integration, improper planning and scheduling, poor production timing, poor coordination, lack of good communication among parties, wrong deliveries, poor control and supervision are the major issues within the precast supply chain. These issues could result in adverse consequences for the objectives and success of the precast project.Eventually, to reduce and eliminate these issues, the proposed prototype will support appropriate deliveries,efficient monitoring, the facilitation of coordination and collaboration with improved communication. It is anticipated that this research will establish a unique perception of the precast construction industry which will finally enhance its productivity, improve its efficiency and maximise its effectiveness