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Flexibility estimation is the first step necessary to incorporate building energy systems into demand side management programs. We extend a known method for temporal flexibility estimation from literature to a real-world residential heat pump system, solely based on historical cloud data. The method proposed relies on robust simplifications and estimates employing process knowledge, energy balances and manufacturer's information. Resulting forced and delayed temporal flexibility, covering both domestic hot water and space heating demands as constraints, allows to derive a flexibility range for the heat pump system. The resulting temporal flexibility lay within the range of 24 minutes and 6 hours for forced and delayed flexibility, respectively. This range provides new insights into the system's behaviour and is the basis for estimating power and energy flexibility - the first step necessary to incorporate building energy systems into demand side management programs.
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.
The properties of SiC and diamond make them attractive materials for MEMS and sensor devices. We innovated specific laser ablation techniques to fabricate membranes and cantilevers made of SiC or nano-(micro-) crystalline diamond films grown on Si/SiO2 substrates by microwave chemical vapour deposition (MWCVD). We started research to generate surface moulds to grow corrugated diamond films for membranes and cantilevers. A software tool was developed to support the design of micromechanical cantilevers. We can measure deformation and resonant frequency of diamond cantilevers and identify the global mechanical properties. A benchmark against finite element simulations enables an inverse identification of the specific system parameters and simplifies the characterization procedure.
Small and medium-sized enterprises often face resource deficits and there- fore depend on cooperating with other actors to stay innovative in a competitive environment. Establishing and maintaining actual co-creation and service inter- action strategies however is challenging. A reason for this is the complexity of finding methodologies and tools to create valuable outcome and the lack of knowledge of collaboration toolsets, also in virtual environments. This paper introduces an Innovation-Method-Framework consisting of innovation methods for increased service interaction and value co-creation among service stakeholders. Also, toolsets for the framework’s practical application are provided.
The paper deals with the optimization of 2x2 optical switch for photonic integrated circuits based on two 2x2 MMI splitters and two phase-modulators. The optical switch was modelled in the RSoftCAD with the simulation tool BeamPROP. The optimization was done to minimise the insertion losses and broaden the spectral band at 1550 nm by using linear tapers in a 2x2 MMI splitter topology. The 2x2 optical switch is a common element for creating more complex 1xN or NxN optical switches in all-optical signal processing.
Due to the increasing trend of photonic element miniaturisation and the need for optical splitting, we propose and simulate a new type of three-dimensional (3D) optical splitter based on multimode interference (MMI) for the wavelength of 1550 nm. We present various designs and simulations of various parameters for the optimized MMI splitter. We focus on the possibility of its integration on an optical fiber. The design is focused on a possible production process using 3D laser lithography for the prepared experiments. The MMI splitter was prepared by laser lithography using direct writing process and finally investigated by output characterisation by the near-field measurement.