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Human capabilities to interact, interfere, support, supervise and take over different tasks in a production environment are often not considered in the context of automated and self-organizing factories (smart factories). Adaptive Task Sharing (ATS) is a method to combine the strengths of automation and human skills to provide flexible and resilient factories. ATS offers huge potential for improving and enhancing ergonomics and human factors in production. The assembly worker plays a vital role in such hybrid manufacturing as a partner and coordinator of production services. In recent years, techniques have been developed to efficiently compute production execution graphs optimized for various technical criteria, like minimum makespan or energy consumption. This paper shows how to use these techniques for a flexible production planning that incorporates human workers and investigates different scenarios of task allocation between humans and machines and their impact on production workflows. Such socio-technical interactions between humans and machines need to be at the core of resilient production systems to deal with unforeseen circumstances, provide the flexibility required in high-variability, low-volume production scenarios, and increase productivity and workplace quality of human workers.

This paper provides an update on two essential aspects related to the future support of Galileo to Advanced Receiver Autonomous Integrity Monitoring (ARAIM) service: performance assessment and Integrity Support Message (ISM) format. The first part of this paper gives a detailed measurement characterization of the Galileo performance parameters relevant for ARAIM users, with particular view on URA and Broadcast Group Delay (BGD) error overbound. This work is one of the important outcomes of the Integrity Failure Mode and Effect Analysis (IFMEA) that has been established for Galileo in the frame of the Galileo Open Service Safety of Life (GoSoL) work plan set up by the European Commission. The work presented in this paper has been conducted by ESA, EUSPA and EC together with industry. These results are an extension of the prior work presented on [13.] and [14.] considering an enlargement of the observation period for Galileo of approximately 24 and 12 months respectively. The additional monitoring period has corroborated the good performance on the SoL relevant parameters and the fulfillment of the target Psat, Pconst and URA as per Galileo SARPs [16.]. The second part of this paper addresses the Galileo ISM format that will be disseminated through the Galileo Signal-in-Space. This paper describes the initial design of the Galileo ISM message type, together with the corresponding processing logic at the user receiver. Additionally, the E1B I/NAV message stream broadcast by Galileo satellites, at a rate of one I/NAV word (128 bits) per 30-seconds sub-frame, can also accommodate ISM from other constellations.

The use cases of GNSS applications are continuously expanding and new categories of GNSS chipsets are emerging that are driven by needs including low complexity and low power consumption. Internet of Things (IoT) devices are the most prominent representatives of these new user categories. It is understood that existing GNSS signals, which are to a large extent designed to enable high accuracy, are not ideally suited for these emerging user categories. This paper introduces possible concepts identified in the frame of Galileo Evolution activities referred to as Quasi-Pilot (QP) signal that are designed to also comply with the needs of IoT devices. The main driver for the design of a QP signal is the reduction of the acquisition complexity, enabling a rapid and robust time ambiguity resolution together with the possibility of enabling a long coherent integration to achieve sufficient sensitivity in challenging environment if needed. In addition a QP signal design should enable a hand-over to existing legacy signals for the user to exploit also the high accuracy capabilities that these signals offer.

The distribution of clock correction and ephemeris (CCE) parameters in navigation messages broadcast by operational satellite vehicles (SVs) of the Global Navigation Satellite System (GNSS) is studied. For this purpose, two evaluation metrics are proposed, namely atypical navigation message structures and time to complete CCE sets (TTCS). The evaluation metrics are used to analyze three and a half years of operational Galileo F/NAV and GPS LNAV messages. The study considers arbitrary and healthy-only signal-in-space (SIS) health statuses. The frequently used receiver independent exchange format (RINEX) navigation files are shown to not provide sufficient information to determine the CCE parameters transmitted at every time instance. Due to the identified limitations, binary navigation data collected by a worldwide network of monitoring stations are used for the analysis. During operations, the maximum of the TTCS metric is shown to be impacted by the issue of data (IOD) update periods and structures with mismatched IOD parameters, potentially introducing an additional delay to the time to first fix (TTFF). The message timing requirements of dual-frequency multi-constellation (DFMC) satellite-based augmentation system (SBAS) are shown to be in line with the minimum times needed to obtain multiple complete Galileo F/NAV and GPS LNAV CCE sets.

The use cases of GNSS applications are continuously expanding and new categories of GNSS chipsets are emerging that are driven by needs including low complexity and low power consumption. Internet of Things (IoT) devices are the most prominent representatives of these new user categories. It is understood that existing GNSS signals, which are to a large extent designed to enable high accuracy, are not ideally suited for these emerging user categories. This paper introduces possible concepts identified in the frame of Galileo Evolution activities referred to as Quasi-Pilot (QP) signal that are designed to also comply with the needs of IoT devices. The main driver for the design of a QP signal is the reduction of the acquisition complexity, enabling a rapid and robust time ambiguity resolution together with the possibility of enabling a long coherent integration to achieve sufficient sensitivity in challenging environment if needed. In addition a QP signal design should enable a handover to existing legacy signals for the user to exploit also the high accuracy capabilities that these signals offer.

It is getting increasingly difficult for factories to provide the required flexibility to support lot-size-one production orders. Therefore, collaboration is especially important for manufacturing companies to ensure that they do not lose manufacturing contracts because they can only partially fulfill the requirements of their customers. This paper presents an approach for generating production plans across multiple factories, so that the production requirements for a given product can be met through collaboration with other factories. We describe two variants of an algorithm for computing multi-factory production plans based on constraint satisfaction. The approach makes inter-company logistics transparent to the product designer/seller – by managing the division of tasks, transportation between the factories, and resolving dependencies among the participating manufacturers in the network. We have designed an ecosystem management platform that will consider the product, its required quality, quantities, delivery dates, certification, logistics requirements etc. to automatically generate diverse production offers.

The characterization of Galileo Open Service signal-in-space (SiS) represents an essential input to Safety-of-Life (SoL) applications like Horizontal ARAIM (Advanced Receiver Autonomous Integrity Monitoring) and SBAS (Satellite Based Augmentation System) in particular EGNOS V3. This paper describes the IFMEA (Integrity Failure Mode and Effect Analysis) process that has been implemented for Galileo in order to conduct in a structured way the analysis of events critical for Safety-of-Life applications (referred to as Feared Events, FE) based on accumulated measurement history and design documentation analysis. The different steps of the established process are described which encompass measurement collection and post-processing, design analysis, root cause identification, reporting and archiving in form of a database. The process is leading to the identification of improvement recommendations in order to mitigate the re-occurrence of observed events. Moreover this paper provides insight into the Galileo Feared Event characterization, along with an analysis versus overall Safety-of-Life needs and the extrapolation to future Galileo configurations. It comprises the identification of anomalies in the satellites’ signal-in-space that could impact the positioning integrity. Several SiS threat offline monitors have been developed for the Galileo Feared Event characterization that allow identifying anomalies in both the navigation message and code and carrier phase observations. The focus is put on the characterization results in terms of Feared Event probabilities of occurrence and related magnitudes.The underlying mathematical approach for the derivation of the Feared Eventprobabilities as a function of the number of Feared Events and the observation period is described in this paper.The characterization results confirm the high quality of the code and carrier phase signals (based on an observation period of about 3.5 years of the Galileo constellation). For the message related anomalies including the broadcast orbit and clock prediction errors, the latest results are limited due to a limited observation period (about 2.5 years of Galileo constellation after the declaration of Galileo Initial Services). After extrapolation to a future Galileo configuration, the Feared Event probabilities achieve low and very promising levels.

The aim of this work was to develop an easy and quick technique for characterizing various lighting situations, that is, single lamps or illuminated signs and to quantify impacts on small scales like streets, buildings and near areas. The method uses a DSLR-camera equipped with fisheye-lens and the software Sky Quality Camera, both commonly used as part of night sky imagery in the light pollution community, to obtain information about luminance and correlated colour temperature. As a difference to its usual build-up, observed light emitting sources were captured by pointing the camera towards analysed objects, that is, images were taken via vertical plane imaging with very short exposure times under one second. Results have proven that this technique provides a practical way to quantify the lighting efficacy in a certain place or area, as a quantitative analysis of the direct emission towards the observer and the illumination on surroundings, that is, street surfaces, sidewalks and buildings, was performed. When conducting lamp conversions, the method can be used to characterize the gradient of change and could be a useful tool for municipalities to find the optimal lighting solution. The paper shows examples of different lighting situations like single lamps of different types, also containing various luminaires, illuminated billboards or buildings and impacts of the lighting transition to LEDs in the city of Eisenstadt, Austria. The horizontal fisheye method is interdisciplinary applicable, for example, being suitable for lighting management, to sustainability and energy saving purposes.

The aim of the paper is to analyse the distribution of update periods of Issue of Data (IOD) parameters in Galileo F/NAV and Navstar Global Positioning System (GPS) LNAV messages. For this purpose, a new method aiming at the reconstruction of IOD update periods reported by a network of monitoring stations is proposed. Over one year of Galileo F/NAV and over three years of GPS LNAV data is processed and consolidated using the proposed method. A reconstruction rate of 99.66% is achieved for the Galileo F/NAV messages. To extract the information on the consecutive update periods of IOD parameters, two metrics are proposed. It was observed that Galileo F/NAV messages can experience fast single and fast double updates. Double updates happen at worst over two subsequent Galileo F/NAV sub-frames. The obtained results suggest a possible impact on Satellite-Based Augmentation System (SBAS). In order to assess the impact on a drafted Dual Frequency Multi Constellation (DFMC) SBAS Standards And Recommended Practices (SARPs), a Galileo F/NAV IOD selector, whose task is to select a specific IOD for augmentation in SBAS, is proposed and implemented. The design of the Galileo F/NAV IOD selector takes into account the observed IOD update periods as well as relevant requirement defined in the drafted DFMC SBAS Minimum Operational Performance Standards (MOPS). The selector aims at maximising the minimum time that the SBAS user has to decode the navigation message identified by the IOD before it is selected for augmentation. In addition, the maximum time that the SBAS would be using IOD, which is no longer transmitted by the Satellite Vehicle (Sv), is also over bounded by the design. According to the analysed data, it is identified that an optimal time to trigger the selection of new IOD of Galileo F/NAV message for augmentation is 350s when maximising the minimum decoding time. The trigger time guarantees that the SBAS user would always have at least 200s available to decode the Galileo F/NAV message.

Industrial software systems are often systems of systems (SoS) that evolve continuously to meet new customer requirements or to address technological changes. Despite thorough testing of the different contributing parts, the full behavior of SoS only emerges at runtime. The systems in the SoS and their interactions thus need to be continuously monitored and checked during operation to determine compliance with requirements. In particular, after changes to one system, it is necessary to check whether the overall SoS still behaves correctly and as intended. Based on an existing monitoring framework we have been developing support for capturing and comparing event traces in SoS. Our approach facilitates and partly automates the identification of differences in event traces, which often indicate undesirable behavior introduced during evolution. In this paper we motivate the need for monitoring and evolution support in SoS using an industrial example and describe our event-based capture-and-compare approach. We evaluate the applicability and scalability of our tool-supported approach, demonstrating that it can cope with comparing event traces from an industrial SoS. We present our experiences and findings intended for researchers and practitioners working on maintenance and evolution of large-scale software systems.