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Most of todays assistance systems for the shop floor do not consistently follow a human-centered design approach. An explicit modeling of concepts for instructions, users and adaptations is required when aiming for a holistic approach. Therefore, we first define a morphological box to capture design alternatives for adaptive functionalities. Afterwards, a reference architecture is presented, consisting of several building blocks that implement an adaptation loop to continuously adapt the provided assistance and the system behavior to the current user. A selection of algorithms to realize adaptive behavior concludes our contribution. Following a human-centered design approach, three exemplary scenarios for assistance on the shop floor demonstrate the application of our approach.

Agile software development methods are widely used by software organisations, focusing on short developmental life cycles and customer satisfaction through the iterative and incremental development of software products. Despite their popularity, these methods present risks that may be underappreciated. This paper examines certain risks attributed to agile software development, with a focus on the lack of documentation, scope creep, technical debt and job satisfaction. Through the application of a multivocal literature review, we find that agile software development can greatly benefit projects. However, when agile methods are implemented inappropriately or sub-optimally, projects risk over-spending, delayed or defective software, employee turnover, and overall decreased productivity. Understanding the risks associated with agile software development can help practitioners to achieve higher efficiency and success in their software development projects.

The objective of this chapter is to provide an introduction to application software in the PLM environment. The chapter aims to give the reader a basic understanding of PLM applications and related activities. It will help readers working in PLM Initiatives to participate in activities related to PLM applications. The chapter also aims to give students who are studying PLM a basic understanding of the application software components of a company’s PLM environment.

This chapter discusses innovation in the software field including miscellaneous topics such as distributed systems, service-oriented architecture (SOA), software as a service (SaaS), cloud computing and embedded systems. We discuss the need for innovation in software engineering and discuss some recent innovations including aspect-oriented software engineering (AOSE).

This chapter deals with the importance of SOC design verification, plan and strategies adopted for verification. It defines functional simulation, functional coverage, code coverage, and other important terms used in verification. Importance of FPGA validation and how it complements the SOC design verification is explained in this chapter. Most of the simulation concept of SOC design verification explained in the chapter can be seen in the verification of the reference designs provided in Chapter 12.

There is a wide variety of commercially available products on the market. This chapter categorizes the “toolkit” of specialized products commonly used for neurointerventional procedures. Understanding the basic differences in the uses and actions of these products is intended to assist providers in evaluating and choosing the appropriate agent or device.

Context and motivation: Natural Language Processing (NLP) techniques are constantly improving their capabilities, and deep learning approaches are now used in the daily practice of several application domains. Requirements engineering (RE) research has traditionally incorporated NLP solutions to ad-dress its fundamental tasks, such as classification, tracing, and defect detection. Question/problem: However, RE research often suffers from a lack of annotated datasets, and this makes it difficult to fully exploit supervised NLP techniques in general, and deep-learning ones in the specific, thereby losing the potential advantages offered by these techniques. Principal ideas/results: To address the problem of limited annotated datasets, we propose to use zero-shot classification, and apply this learning paradigm to RE tasks that can be treated as classification problems. We experimented with the task of distinguishing between two types of NFR requirements: usability and security requirement and obtained encouraging weighted F-scores over 80% and almost perfect recall rates from a number of the tested models, without any training data and fine-tuning. Contribution: This work paves the basis for further research in the application of zero-shot learning, and towards the solution of the long-standing problem of dataset annotation in RE.

In this paper we revisit a taxonomy of client-side IoT software architectures that we presented a few years ago. We note that the emergence of inexpensive AI/ML hardware and new communication technologies are broadening the architectural options for IoT devices even further. These options can have a significant impact on the overall end-to-end architecture and topology of IoT systems, e.g., in determining how much computation can be performed on the edge of the network. We study the implications of the IoT device architecture choices in light of the new observations, as well as make some new predictions about future directions. Additionally, we make a case for isomorphic IoT systems in which development complexity is alleviated with consistent use of technologies across the entire stack, providing a seamless continuum from edge devices all the way to the cloud. peerReviewed

Blockchain is a new technology under the interest of many researchers based on the benefits it provides for various systems in different industries. One of the main applications of blockchain is the healthcare sector where security, privacy and integrity of patient data is essential. In this paper, we discuss the problems faced by healthcare systems and how blockchain technology can be used to support these systems and improve the patient journey. A new Petri Net-based blockchain framework is proposed. The framework focuses on two main layers: process layer and data layer along with a mapping of the blockchain technology into the model. The proposed framework is validated using mathematical modeling and Petri Nets.

Automated test generation is an important component in the digital transformation of education. Assessing knowledge using tests is an objective, fast and effective. Electronic tests are effective in verifying knowledge but they also can be used for self-learning. Generating tests by teachers is a laborious and time-consuming process. The development of an automatic test generation system is a key component for adapting education to the ever-changing digital environment. This paper presents a logical approach to assessing student success in the testing process. The approach satisfies the two goals of testing: knowledge testing and self-learning. A process for intelligent transition from one level of complexity of the testing system to another has been developed. This is a new and innovative approach to developing an intelligent automatic test generation system. None of our known training management systems has a self-test module with self-generated questions. The system we developed generates questions independently using templates. The system also navigates students through the different levels of complexity of the content, using the puzzle method and the curiosity function. Adding intelligence to an automated e-test generation system can be a milestone of digital transformation in education and can increase the efficiency of the teaching and learning process during a crisis. Today we are facing the crisis with COVID-19, which affects all areas of work, study and life. Our intelligent approach helps educational institutions to overcome atypical situations like the one we face now. It can also support the universities for a smooth digital transformation and better handling with future atypical situations. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

The article discusses the features of electronic document management of technical documentation of railway automation and telemechanics. The article deals with the problems of synthesizing the mathematical description of the electronic document management of technical documentation for railway automation and telemechanics. For this, an overview of the actual processes of making, checking and applying technical documentation was carried out on the example of maintaining custom specifications for automation and telemechanics systems, which made it possible to identify document flow scenarios, as well as protocols of technical documentation properties. A method for creating a model of electronic document management of technical documentation based on the apparatus of graph theory has been advanced. Methods for determining sets for the proposed model are described, an algebra of workflow of TD using graphs is proposed. To set the matrix type of document flow representation, it is proposed to use a set of flat rectangular matrices, each of which represents the state of the system in some discrete unit of time. The resulting matrices of incidents determine the graph model of the document flow of the process under consideration, and the set of these matrices sets all possible scenarios for the movement of documents in the process, describes all possible states of documents and determines possible participants. The use of the proposed method for constructing a mathematical model based on graph theory makes it possible to develop reliable applied software for solving problems of operational document flow of technical documentation.

This research paper presents Turing: an innovative tool that approaches mass-housing design and demonstrates how cloud computing and generative design can be conjointly used via an accessible web-based application to achieve a high level of user input and co-design integration. The technologies implemented are a Grasshopper cloud application with Rhino.Compute, linked to a web server and using Three.js as a visualisation engine on a website.

This paper describes a framework for using 3D simulation as a safety assessment tool based on ISO/TS 15066:2016 guidelines for a cobot work cell. A human-robot collaboration-based work cell has been developed. The digital counterpart of this work cell is developed beforehand to perform several safety assessments based on ISO/TS 15066:2016. It is observed that the 3D simulation model can be used as a safety assessment tool to ensure the safety of a cobot work cell even before its creation. The study also signifies the simulation software for safety and human factors in the design of a cobot cell.

This paper analyses the synergetic potential of Augmented Reality (AR) and offline programming (OLP) in the commission of industrial robots. We discuss that AR could utilise existing programming paradigms present in the OLP to simplify the online commission in manufacturing plants with its ability to freely combine digital and real content. Focussing on the complementary use of AR and OLP a theoretically promising use case is derived. The use case is implemented in a simplified mock-up and a user study is conducted to practicably evaluate the feasibility. Ten participants commissioned an offline created program using the developed AR application. As nine out of ten participants could achieve a valid commission by using the developed AR application, the study indicates the feasibility of the presented use case.

The article presents the main stages of developing a web-based software complex for calculating the technological parameters of chemical and technological processes taking into account a work with Wolfram Mathematica. The main stages of work, tables, modules, stages of integration of a mathematical model implemented in Wolfram Mathematica with a web-based software complex are presented. The way users and user groups function is taken from a Unix system. Thus, the system administrator is able at any time to easily hide/open a section from a user or an entire group of users. To optimize the time spent on the calculation of characteristics, all user requests (which is recorded without belonging to any user) and their results are entered into the database. If the user entered the query parameters that were already entered earlier and the result was calculated for them, then the results are immediately taken from the database without resorting to the mathematical model itself, and this is the most time-consuming step. The main task of the developed system is to calculate the required calculated parameters based on input data. The program gives a forecast about the characteristics of the resulting product and output technological parameters based on mathematical models of chemical and technological processes.

This paper mainly serves as a summary of the recent software development trend of low-code platforms. It discusses many uses of the applications, company created low-code programs, and risks and benefits in using low-coding solutions. I reach the conclusion that low-coding is still gaining momentum and will continue to increase and develop in the future. This may in fact be the future of most coding experience.

The requirements elicitation process aims to obtain a preliminary version of the requirements before their specification. However, due the nature of this process, it is very difficult to know if the elicited requirements have quality. Furthermore, there are some metrics that allow requirements engineers to measure some aspects of the elicitation process and its final product (i.e., a preliminary version of the requirements, also called pre-requirements), however there is no way of measuring and controlling the elicited pre-requirements. With the aim of understanding, evaluating, and improving the requirements elicitation process, the existing metrics for this process have been analyzed and, as a consequence, eight metrics using the GQM paradigm are proposed. Additionally, a preliminary validation of these metrics has been performed in the context of a small-sized software enterprise. The obtained results are also presented.

Recently, due to the active expansion of the Internet of Things (IoT) and Ubiquitous Computing, the neuro-augmented methods and tools for controlling software systems are on the rapid incline. But despite the existing understanding of the necessity of unified approaches for integration of neural interfaces into IoT ecosystems, those seem to be insufficiently developed. In most cases, the equipment is capable of working exclusively with a narrow range of software supplied by its manufacturer, which greatly hinders the integration process. In this paper, we propose the ontology-driven tools for the brain-computer interface integration into the IoT ecosystem. Unified high-level mechanism is provided that allows diverse software, services, and hardware to interconnect independently of particular IoT platforms. Visual editor is developed to design the integration process pipeline, describing desired devices and their behavior. Ontology-driven generator of corresponding firmware and middleware is created, which automates the software developers work. Some real-world applications based on the suggested approach are presented. Evaluation of the methods used is highlighted.

This chapter presents a structured framework that can guide designers to develop smart products with context-smartness, network-smartness, and service-smartness, the definitions of which are explained from the perspective of product development. The framework is developed based on the theoretical foundation of the Situated Function-Behavior-Structure (FBS) ontology. A systematic step-by-step design process is prescribed to leverage various data operations to support design operations involved in the process of designing a smart product with stronger context-smartness, network-smartness, and service-smartness. Some existing design methods and emerging design tools are also incorporated into the framework.

Due to the rapid development of cyber-physical systems and smart products, a new paradigm of smart product-service systems (SPSS) has emerged. The emergence of SPSS has transformed the way manufacturers deliver value to their product users, as Internet-based services enable products to be constantly updated during their use phase. Furthermore, enhancing product functions during the use stage to better meet users’ needs offers revolutionary potential to boost user satisfaction. The successful implementation of SPSS lies in manufacturers’ capabilities to anticipate and fulfil users’ real-time and contextual requirements by analysing heterogeneous forms of user data. This chapter proposes a framework to illustrate the development process and implementation of SPSS. An illustrative example of a robot vacuum cleaner (RVC) product-service design is used to assess the proposed framework’s utility.

With the rapid development of cyber-physical systems (CPS) and big data, product customization is evolving from traditional mass customization to data-driven smart customization. Data-driven smart customization is a new paradigm that highly emphasizes the reconfiguration of products in the use phase. This paradigm calls for a new architecture to enhance collaboration to perform customization. This chapter proposes a blockchain-based data-driven smart customization framework, in which blockchain functions to maintain the evolved customization data and decentralized consensus among stakeholders. A case study of smart vehicle customization is conducted to demonstrate its efficacy.

The increasing dependence of our modern society on software systems has driven the development of software products to be more competitive and time-consuming. At the same time, large-scale software development is still considered a complex, effort-consuming, and expensive activity, given the influence of the transitions in software development, which are the adoption of software product lines, software development globalization, and the adoption of software ecosystems. Hence, the consequences of software failures become costly and even dangerous. In this chapter, we thus review probabilistic software reliability models with different groups. Since nonhomogeneous Poisson process (NHPP) based software reliability models have been successful tools in practical software reliability engineering, this chapter mainly focuses on the review of NHPP based software reliability models that address various concerns in software development practices, such as testing efficiency, testing coverage, multiple fault types, time-delay fault removal, and environmental factors.

This work focuses on the requirements analysis of a modular framework to simplify developing and integrating new or existing remote experiments and laboratories. Besides this technical view, this paper also gives an organizational view on developing such a framework and managing the corresponding modules, which can also be developed by a third party. On a technical side, we provide the requirements to ultimately define the interface between different modules, enabling easy integration on different abstraction levels.

Digital Twin is the digital representation of any physical asset that can be addressed, belonging to real world. This new concept provides a new abstraction layer which serves as a common operating system, offering an enhanced experience named Device-as-a-Service, being based on calling and manipulating the assets by their function, with increased usage scenarios mainly in industry, but also in home scenarios. The purpose of this paper is to demonstrate the main benefits of digital twin implementations: using a common and vendor agnostic IoT operating system, the independence from the IoT protocol to be used and from the transmission media, user profile persistency. The described implementation is based on the open source project called Ditto.

New extensions and features to the remote laboratories currently used for undergraduate courses in automatic control laboratory at the School of Engineering of University of Applied Sciences and Arts Western Switzerland are presented. This paper shows how lab experimentation and lab simulation can be linked in a complementary way. In fact, their adequate combination offers the students the opportunity to apply classroom theoretical knowledge while conducting a real experiment. Besides, the lab-based simulation tools can be used for experiment modeling and controller design. Simulation tools also facilitate analyzing and interpreting data and finally validating the results. We discuss different technical implementing trends as well as several pedagogical approaches in the way remote lab exercises are performed including real-time data acquisition, experimentation environment within user friendly interface and simulation tools.

The peculiarities of the existing models of cloud services provision and the possibilities of their usage for software development are investigated in this work . It is shown that SAP Cloud Platform is an enterprise cloud platform that allows companies to develop their applications, extensions, or add-ons for existing SAP products or create a hybrid IT landscape by integrating cloud solutions. The analysis of the limitations and services of SAP Cloud Platform, including DevOps methodology and CALMS framework is performed. The method of business application development in the Cloud Foundry environment of SAP Cloud Platform is presented.

Currently, ontologies remain one of the most effective ways to conceptualize and formalize domain knowledge. The process of their creation requires automation and improvement including the use of various information sources. One of the domains that require the use of ontology engineering is the diagnosis and assessment of the technical state of petrochemical equipment and technological complexes. In turn, spreadsheets are one of the most accessible and common ways of representing and storing information. They are characterized by a great variety and heterogeneity of layouts, styles, and content. Spreadsheets are a valuable source of structured domain knowledge. In this paper, we propose to automate the ontology engineering in petrochemical equipment inspection tasks (including diagnosis and assessment of the technical states) based on the analysis and transformation of spreadsheet data. For this purpose, we present a new technique that provides the restoration of tabular data semantics, conceptualization, and formalization of tabular content in the form of ontologies. The main activities of our technique are the following: transforming input arbitrary spreadsheets into a canonicalized form; obtaining ontology fragments based on the analysis and transformation of canonical spreadsheets; aggregating ontology fragments into a complete ontological model; generating ontological model code in the OWL format. The technique proposed is implemented in the form of a prototype of the software that was evaluated when solving tasks of ontology engineering for industrial petrochemical equipment. Spreadsheets from reports on industrial safety inspection were used as a data source.

This chapter presents a formal statement of the problem of interaction with heterogeneous agricultural robots, describes the developed model-algorithmic support for controlling the interaction of heterogeneous robotic systems during UAV service during group agricultural tasks.

Distributed Ledger Technology (DLT) is a disruptive technology as it provides decentralization, transparency and immutability. Various DLT platforms have emerged during the last few years. These platforms can be classified based on i) Permission access-public, consortium or private, ii) Consensus algorithms and iii) Arrangement of the transactions. The underlying architecture and consensus algorithm have a significant impact on the performance of a DLT. Bitcoin and Ethereum are public DLTs with the Proof of Work consensus algorithm. IOTA and Hashgraph are Directed Acyclic Graph-based DLTs with different consensus algorithms and arrangement of transactions. This paper describes and compares public DLTs Bitcoin, Ethereum, IOTA and Hashgraph. The detailed study of architecture and consensus will help developers to leverage an appropriate DLT platform for the specific application.

Engineers are not usually confronted with empirical research methods during their education. Classical product developers thus lack knowledge and the intuition of what to consider when using methods in user studies. The problem is that user studies therefore miss potential development goals for optimized user-centered product design. To resolve these difficulties, a process approach and an in-depth guide have been developed. They provide knowledge, focused on psychology and social sciences about user studies along the ideally typical history of an empirical study in a structured, compact and comprehensible form. This enables product developers to more effectively and efficiently capture the needs of customers. At the same time, the effort required to implement user studies is reduced, errors are avoided and quality is increased. In the future, the process approach and the guide will be verified and validated.

The present study demonstrates the ongoing development of a service robot application in a campus library through the application of Design Science Research (DSR) combined with user-centered design (UCD). In particular, we involved librarians and co-created an application solution addressing two use cases: giving directions to a desired subject area/book and providing recommendations for an event/book. Additionally, we involved potential end users to evaluate the robot artifact through an onsite usability test (N = 14) already within the design cycle. This process resulted in a successful application of the robot artifact for the identified use cases and shows feasibility of combining DSR with UCD.

This paper contributes to the field of Human-Centered Design by introducing a new method for participatory visual analysis of manual assembly processes in factories to identify user requirements for digital assistance systems. The process-oriented, visual method integrates the process, need for information, automation level as well as the worker experiences within the process. With the help of the method, user requirements can be derived, and assistance potential can be identified.

Since assembly processes are continuously increasing in complexity due to the growing number of product variants, the importance of digital assistance systems for handling complexity is growing to support human work in a suitable manner. However, the configuration of the assistance system for the increasing number of product variants can be particularly complex and time consuming. This paper therefore presents a concept to support the implementation of new product variants in existing digital assistance systems in a data-based approach by facilitating the process. Thus, an approach for possible support options depending on the individual data management of companies is identified and presented. The developed approach is examined on a conceptual level which is generally applicable. Finally, to identify the most suitable support within the presented approach, a benefit-oriented evaluation is derived as an outlook.

Security Token Offering (STO) is the new and reshaped form of the famous Initial Coin Offering (ICO). The thing that distinguishes STO from ICO is the inclusion of several rules from regulators and auditors. The control by regulators and auditors will generate a trade-off between control and decentralization of the STO. We did a simulation for selecting the most suitable blockchain platform for the STO process using the Multi-Criteria Decision Model simulator to cover this issue. The simulation result shows the relation between the selected features, software quality, and the most suitable solution for STO.

The problem I intend to address in my PhD research is related to the application of DLTs in resource-constrained industrial environments. Could it be feasible and effective to design a holistic multi-DLT architecture in order to tackle most of the challenges that are encountered when applying DLTs in IIoT? Here I present a multi-DLT architecture for an Industry 4.0 case scenario where I try to tackle the limitations of DLTs for every level of the aforementioned scenario.

Defect Prevention refers to the process of ensuring that no defects occur in the first place rather than later detecting defects and correcting them. A test-driven development approach naturally contributes to defect prevention along the software development process pipeline. A generic test suite that suits the testing needs of any web application is needed. The test suite should serve a regression test suite’s purpose to ensure an application’s general health providing a confident user experience. The authors presented a generic set for checking web apps, mutation operators. In this work, the operators’ comprehensive suite is presented as an exhaustive regression test suite to prevent web application defects. Small and medium business enterprises can bank on the regression test suite proposed for customer retention while saving on their testing budgets. The test suite promises a robust web app persistent against any kind of malignant usage.