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Rapid prototyping platforms reduce development time by allowing quick prototyping of a prototype idea and achieve more time for actual application development with user interfaces. This approach has long been followed in technical platforms, such as the Arduino. To transfer this form of prototyping to wearables, WearIT is presented in this paper.WearIT consists of four components as a wearable prototyping platform: (1) a vest, (2) sensor and actuator shields, (3) its own library and (4) a motherboard consisting of Arduino, Raspberry Pi, a board and a GPS module. As a result, a wearable prototype can be quickly developed by attaching sensor and actuator shields to the WearIT vest. These sensor and actuator shields can then be programmed through the WearIT library. Via Virtual Network Computing (VNC) with a remote computer, the screen contents of the Raspberry Pi can be accessed and the Arduino be programmed.
The very first International Workshop on Software-intensive Business: Start-ups, Ecosystems and Platforms (SiBW 2018) was held in Espoo (Greater Helsinki), Finland on December 3rd, 2018 – just a day before SLUSH 2018, the world’s biggest startup event. Thanks to the collaboration with the organizers of SLUSH, many of the software-intensive business researchers and practitioners took part also in this event.
The international workshop gathered together 35 registered attendees, from Sweden, Germany, Latvia, Finland, Italy and the Netherlands representing both academia as well as industry. The event itself was sponsored by VTT Technical Research Centre of Finland and the workshop was organized by the newly founded Software-intensive Business research community together with Software Startup Research Network (SSRN).
This research addresses the question of why employees use enterprise social networks (ESN). Against the background of technology acceptance research, we propose an extended unified theory of acceptance and use of technology (UTAUT) model, adapt it to an ESN context, and test our model against data from ESN users of large and medium-sized enterprises. We use partial least squares structural equation modeling to gain insights into the determinants of ESN use. This paper contributes to ESN acceptance research by evaluating a model containing determinants of ESN use. It also examines the effects of determinants on five different usage dimensions of ESN. The results reveal that facilitating conditions are the main driver of ESN use while the impact of intention to use is comparably small. Implications for theory and practice are discussed.
Die digitale Transformation ist der Auslöser dafür, bestehende Produktionsparadigmen in Frage zu stellen bzw. weiterzuentwickeln. Sie bietet produzierenden Unternehmen die Chance, ihre Wertschöpfung grundlegend zu optimieren und neue Geschäftspotenziale zu erschließen.
Im Rahmen von Industrie 4.0 werden die aktuellen Informations- und Kommunikationstechnologien mit der Produktions- und Automatisierungstechnik kombiniert und eine neue Stufe der Organisation und Steuerung der gesamten Wertschöpfungskette über den kompletten Lebenszyklus von Produktien und Services angestrebt. Ziel ist die signifikante Flexibilisierung und Verbesserung der Wertschöpfung sowie eine Individualisierung der Produkte und Services durch eine intensive Kunden-Unternehmens-Interaktion und Vernetzung.
A new class of information system architecture, decision-oriented service systems, is spreading more and more. Decision-oriented service systems provide services that support decisions in business processes and products based on the capabilities of cloud-computing environments. To pave the way for the creation of design methods of business processes and products based on decision-oriented service systems, this article introduces a capability-oriented approach. Starting from technological capabilities, more abstract operational and dynamic capabilities are created. The framework created is based on an integrated conceptualization of decision-oriented service systems that allows capturing synergetic effects. By creating the framework, the gap between the technological capabilities of technologies and the strategic goals of enterprises shall be narrowed.
Die digitale Transformation ist der Auslöser dafür, bestehende Produktionsparadigmen in Frage zu stellen bzw. weiterzuentwickeln. Sie bietet produzierenden Unternehmen die Chance, ihre Wertschöpfung grundlegend zu optimieren und neue Geschäftspotenziale zu erschließen.
Im Rahmen von Industrie 4.0 werden die aktuellen Informations- und Kommunikationstechnologien mit der Produktions- und Automatisierungstechnik kombiniert und eine neue Stufe der Organisation und Steuerung der gesamten Wertschöpfungskette über den kompletten Lebenszyklus von Produktien und Services angestrebt.
Ziel ist die signifikante Flexibilisierung und Verbesserung der Wertschöpfung sowie eine Individualisierung der Produkte und Services durch eine intensive Kunden-Unternehmens-Interaktion und Vernetzung.
Context: Software product lines are widely used in automotive embedded software development. This software paradigm improves the quality of software variants by reuse. The combination of agile software development practices with software product lines promises a faster delivery of high quality software. However, the set up of an agile software product line is still challenging, especially in the automotive domain. Goal: This publication aims to evaluate to what extend agility fits to automotive product line engineering. Method: Based on previous work and two workshops, agility is mapped to software product line concerns. Results: This publication presents important principles of software product lines, and examines how agile approaches fit to those principles. Additionally, the principles are related to one of the four major concerns of software product line engineering: Business, Architecture, Process, and Organization. Conclusion: Agile software product line engineering is promising and can add value to existing development approaches. The identified commonalities and hindering factors need to be considered when defining a combined agile product line engineering approach.
Combining agile development and software product lines in automotive: challenges and recommendations
(2018)
Software product lines (SPLs) are used throughout the automotive industry. SPLs help to manage the large number of variants and to improve quality by reuse. In order to develop high quality software faster, agile software development (ASD) practices are introduced. From both the research and the management point of view it is still not clear how these two approaches can be combined. We derive recommendations to combine ASD and SPLs based on challenges identified for an automotive specific model. This study combines the outcome of a literature review and a qualitative interview study with 16 practitioners from the automotive domain. We evaluate the results and analyze the relationship between ASD and SPLs in the automotive domain. Furthermore, we derive recommendations to combine ASD and SPLs based on challenges identified in the automotive domain. This study identifies 86 individual challenges. Important challenges address supplier collaboration and faster software release cycles without loss of quality. The identified challenges and the derived recommendations show that the combination of ASD and SPL in the automotive industry is promising but not trivial. There is a need for an automotive-specific approach that combines ASD and SPL.
The use of additive manufacturing technologies for industrial production is constantly growing. This technology differs from the known production proecdures. The areas for scheduling, detailed and sequence planning are particularly important for additive production due to the long print times and flexible use of the production area. Therefore, production-relevant variables are considered and used for the production planning and control (PPC) of additive manufacturing machines. For this purpose, an optimization model is presented which shows a time-oriented build space utilization. In the implementation, a nesting algorithm is used to check the combinability of different models for each individual print job.