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(2023)
In 2021, a prominent Austria dairy producer suffered from an IT attack and was completely paralysed. Without clearly defined mitigation measures in place, major disruptions were caused alongside the whole supply chain, including logistics service providers, governmental food safety bodies, as well as retailers (i.e., supermarkets and convenience stores). In this paper, we ask the question how digitisation and digital transformation impact IT security, especially when considering the complex company ecosystems of food production and food supply chains in Austria. The problem statement stems from a gap in knowledge of key differences in approaches towards IT security, resilience, risk management and especially business interfaces between food suppliers, supermarkets, distributors, logistics and other service providers. In order to answer related research questions, firstly, the authors conduct literature research, and highlight common guidelines and standardisation as well as look at state-based recommendations for critical infrastructure. In a second step, the paper describes a quantitative and qualitative survey with Austrian food companies (producers and retailers) which is described in detail in the paper. A description of recommended measures for the industry, further steps, as well as an outlook conclude the paper.
Through mandatory ESG (environmental, social, governance) reporting large companies must disclose their ESG activities showing how sustainability risks are incorporated in their decision-making and production processes. This disclosure obligation, however, does not apply to small and medium-sized enterprises (SME), creating a gap in the ESG dataset. Banks are therefore required to collect sustainability data of their SME customers independently to ensure complete ESG integration in the risk analysis process for loans. In this paper, we examine ESG risk analysis through a smart science approach laying the focus on possible value outcomes of sustainable smart services for banks as well as for their (SME) customers. The paper describes ESG factors, how services can be derived from them, targeted metrics of ESG and an ESG Service Creation Framework (business ecosystem building, process model, and value creation). The description of an exemplary use case highlighting the necessary ecosystem for service creation as well as the created value concludes the paper.
Parametric anti-resonance is a phenomenon that occurs in systems with at least two degrees of freedom; this can be achieved by periodically exciting some parameters of the system. The effect of this properly tuned periodicity is to increase the dissipation in the system, which leads to a raising in the effective damping of vibrations. This contribution presents the design of an open-loop control to reduce the settling time using the anti-resonance concept. The control signal consists of a quasi-periodic signal capable of transferring the system’s oscillations from one mode to another mode of the system. The general averaging technique is used to characterize the dynamics, particularly the so-called slow dynamics of motion. With this analysis, the control signal is designed for the potential application of a microelectromechanical sensor arrangement; for this specific example, up to 96.8% reduction of settling time is achieved.
As the boundary between real and virtual life is becoming increasingly blurred, researchers and practitioners are looking for ways to integrate the two intending to improve human lives in a plethora of domains. A cutting-edge concept is the design of Digital Twins (DT), having a broad range of implications and applications, spanning from education, training, as well as safety and productivity in the workplace. An emergent approach for implementing DTs is the usage of mixed reality (MR) and augmented reality (AR), which are well aligned with merging real and virtual objects to enhance the human’s ability to interact with and manage DTs. Yet, this is still a novel area of research and, as such, a grounded understanding of the current state, challenges, and open questions is still lacking. Towards this, we conducted a PRISMA-based literature review of scientific articles and book chapters dealing with the use of MR and AR for digital twins. After a thorough screening phase and eligibility check, 25 papers were analyzed, sorted and compared by different categories like research topic (e.g., visualization, guidance), domain (e.g., manufacturing, education), paper type (e.g., design study, evaluation), evaluation type (user study, case study or none), used hardware (e.g., Microsoft HoloLens, mobile devices) as well as the different outcomes (result type and topic, problems, outlook). The major finding of this research survey is the predominant focus of the reviewed papers on the technology itself and the neglect of factors regarding the users. We, therefore, encourage researchers in this area to keep the importance of ease and joy of use in mind and include users in multiple stages of their work.
Purpose: Although there is an apparent potential in using data for advanced services in manufacturing environments, SMEs are reluctant to share data with their ecosystem partners, which prevents them from leveraging this potential. Therefore, the purpose of this paper is to analyse the reasons behind these resistances. The argumentation paves the way for elaborating countermeasures that are adequate for the specific situation and the typical capabilities of SMEs.
Design/Methodology/Approach: The analysis is based on literature research and in-depth interviews with management representatives of 15 companies in manufacturing service ecosystems. Half of these are manufacturers and the other half technology or service providers for manufacturers. They are SMEs or partly larger companies operating in structures that are typical for SMEs.
Findings: Data sharing hurdles are investigated in the five dimensions, 1. quantifying the value of data, 2. willingness to share data and trust, 3. organizational culture and mindset, 4. legal aspects, and 5. security and privacy. The ability to quantify the value of data is a necessary but not sufficient precondition for data sharing, which must be enabled by adequate measures in the other four dimensions.
Originality/Value: The findings of this empirical study and the solution approach provide an SME-specific framework to analyze hurdles that must be overcome for sharing data in an ecosystem.
Manufacturing SMEs can apply the framework to overcome the hurdles by specific insights and solution approaches. Furthermore, the analysis illustrates the future research direction of the project towards a comprehensive solution approach for data sharing in a manufacturing ecosystem.
The design and development of smart products and services with data science enabled solutions forms a core topic of the current trend of digitalisation in industry. Enabling skilled staff, employees, and students to use data science in their daily work routine of designing such products and services is a key concern of higher education institutions, including universities, company workshop providers and in further education. The scope and usage scenario of this paper is to assess software modules (‘tools’) for integrated data and analytics as service (DAaaS). The tools are usually driven by machine learning, may be deployed in cloud infrastructures, and are specifically targeted at particular needs of the industrial manufacturing, production, or supply chain sector.
The paper describes existing theories and previous work, namely methods used in didactics, work done for visually designing and using machine learning algorithms (no-code / low- code tools), as well as combinations of these two topics. For tools available on the market, an extended assessment of their suitability for a set of learning scenarios and personas is discussed.
Recent developments in the area of Natural Language Processing (NLP) increasingly allow for the extension of such techniques to hitherto unidentified areas of application. This paper deals with the application of state-of-the-art NLP techniques to the domain of Product Safety Risk Assessment (PSRA). PSRA is concerned with the quantification of the risks a user is exposed to during product use. The use case arises from an important process of maintaining due diligence towards the customers of the company OMICRON electronics GmbH.
The paper proposes an approach to evaluate the consistency of human-made risk assessments that are proposed by potentially changing expert panels. Along the stages of this NLP-based approach, multiple insights into the PSRA process allow for an improved understanding of the related risk distribution within the product portfolio of the company. The findings aim at making the current process more transparent as well as at automating repetitive tasks. The results of this paper can be regarded as a first step to support domain experts in the risk assessment process.