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This paper studies whether a monetary union needs a fical union in particular in the Eurozone. On 1 January 1999, despite controversial debates, the rule-based Economic and Monetary Union (EMU) started without a fiscal union. I show that there is weak economic convergence in the EMU since 18 years. In addition, I argue that a fiscal union does not solve the past disintegration failures.
I demonstrate that the major flaws are domestic policy failures and not institutional failures in the euro area. Consequently, establishing a monetary union without having a political union is a risky strategy. Indeed, the rule-based architecture of Maastricht is not guilty for the crisis alone. The root causes are the political flaws aligned with the rather weak enforcement of the rules. I propose a genuine redesign of the rule-based paradigm without a fiscal union. Yet a monetary union without a fiscal union works effectively if the rule enforcement is more automatic and independent of domestic and European policy-making.
The financial crisis of 2007-2010 was probably one of the greatest, most lustrous black-swan events that people of our generation(s) will experience – and at its heart, it was a dynamic phenomenon. It is stated in the vision of the System Dynamics Society that we aspire to transform society by influencing decision-making. Yet, it seems as if system dynamics did not play any significant role in this crisis: we did not examine the markets, we did not provide insights to banks, and we did not warn governments or the people. In our presentation we describe the dynamics involved in a housing bubble, and describe what made the last one different. With the insights gained from this exercise we conclude that, from a system dynamics perspective, the dimension of the financial crisis of 2007-2009 was eminently foreseeable, which will lead us to pose the following question: where were we as a field while this crisis was unfolding, why were we not active players? We present a range of potential answers to this question, hoping to provoke some reflection… and maybe some (re)action.
Parallel grippers offer multiple applications thanks to their flexibility. Their application field ranges from aerospace and automotive to medicine and communication technologies. However, the application of grippers has the problem of exhibition wear and errors during the execution of their operation. This affects the performance of the gripper. In this context, the remaining useful life (RUL) defines the remaining lifespan until failure for an asset at a particular time of operation occurs. The exact lifespan of an asset is uncertain, thus the RUL model and estimation must be derived from available sources of information. This paper presents a method for the estimation of the RUL for a two-jaw parallel gripper. After the introduction to the topic, an overview of existing literature and RUL methods are presented. Subsequently, the method for estimating the RUL of grippers is explained. Finally, the results are summarized and discussed before the outlook and further challenges are presented.
The high system flexibility necessary for the full automation of complex and unstructured tasks leads to increased complexity, thus higher costs. On the other hand, the effectiveness and performance of such systems decrease, explaining the unfulfilled potential of robotcs in sectors such as intralogistics, where the benefits of a robotic solution rarely justify its costs. Taking the distance from the false idea that a task should be either fully automated, or fully manual, this aper presents a method for design of a lean human-robot interaction (HRI) withe the objective of the "right level of automation", where functions are divided among human and automated agends, so that the overall process gains in performances and/or costs. ... The 10 progressive steps of the method are presented and discussed with reference to their graphical tool: the House of Quality Interaction.
In recent years, machine learning algorithms have made a huge development in performance and applicability in industry and especially maintenance. Their application enables predictive maintenance and thus offers efficiency increases. However, a successful implementation of such solutions still requires high effort in data preparation to obtain the right information, interdisciplinarity in teams as well as a good communication to employees. Here, small and medium sized enterprises (SME) often lack in experience, competence and capacity. This paper presents a systematic and practice-oriented method for an implementation of machine learning solutions for predictive maintenance in SME, which has already been validated.
The members of the European TRIZ Campus (ETC) have been learning from and working together with many honorable members of MATRIZ Official for many years and feel very connected to the official International TRIZ Association.
To further spread the TRIZ methodology and TRIZ teaching in the European area in the past 12 months the ETC has put a lot of thought in how making TRIZ accessible to a broader audi-ence and getting more professionals in touch with the methodology was one of the focal points.
To this end, we have developed new formats such as the "Trainer Day" to support trainers on their way into practice. We have drawn up detailed quality guidelines for the teaching of the TRIZ methodology, which are intended to provide orientation for the design of training classes and docu-mentation. We strive for exchange with representatives of "neighbouring" methods such as Six sigma, Lean, DFMA and Design Thinking to indicate synergies and added value among methods and approaches of different kinds. We are testing formats for community building, in order to connect users of all places more strongly with the TRIZ methodology through communication and information of-fers. If TRIZ users feel alone in their organizations, the exchange outside their organi-zation helps them to keep up with the TRIZ methodology. Moreover, the ETC strives to increase the ability to communicate the benefits of TRIZ-usage inside organizations. We discuss, how to reach teachers and students of all age, to make them the unique way of inventive thinking accessible.
In our paper we want to give other MATRIZ Official members insights and share our experi-ences and best practices with our fellow MO members.
Condition monitoring supported with artificial intelligence, cloud computing, and industrial internet of things (IIoT) technologies increases the feasibility of predictive maintenance. However, the cost of traditional sensors, data acquisition systems, and the required information technology expert-knowledge challenge the industry. This paper presents a hybrid condition monitoring system (CMS) architecture consisting of a distributed, low-cost IIoT-sensor solution. The CMS uses micro-electro-mechanical system (MEMS) microphones for data acquisition, edge computing for signal preprocessing, and cloud computing, including artificial neural networks (ANN) for higher-level information processing. The system's feasibility is validated using a testbed for reciprocating linear-motion axes.
Rapidly growing population and increasing amount of shipments induced by the e-commerce are two of the main reasons for the constantly rising urban freight traffic. Cities are therefore overwhelmed by a growing stream of goods and the available infrastructure, shared between people and goods traffic, often reached its maximum capacity. Phenomena such as traffic congestion, pollution and lack of space are direct consequences of this trend and their impact on the quality of life in the city is not negligible. City administrations are keen to evaluate innovative city logistics concepts and adopt alternative solutions, to overcome the challenges posed by such a dynamic environment, constrained in existing infrastructure. In this paper, a heuristic method based on the utility analysis is presented. Thanks to a modular approach accounting for stakeholders´ requirements, possible different scenarios and available technologies, the development of new city logistic concepts is supported. The proposed method is then applied to a case study concerning the city of Reutlingen (Germany). Results are presented and a brief discussion leads to the conclusion.
Maintenance is an increasingly complex and knowledge-intensive field. In order to address these challenges, assistance systems based on augmented, mixed, or virtual reality can be applied. Therefore, the objective of this paper is to present a framework that can be used to identify, select, and implement an assistance system based on reality technology in the maintenance environment. The development of the framework is based on a systematic literature review and subject matter expert interviews. The framework provides the best technological and economic solution in several steps. The validation of the framework is carried out through a case study.
Intralogistics operations in automotive OEMs increasingly confront problems of overcomplexity caused by a customer-centred production that requires customisation and, thus, high product variability, short-notice changes in orders and the handling of an overwhelming number of parts. To alleviate the pressure on intralogistics without sacrificing performance objectives, the speed and flexibility of logistical operations have to be increased. One approach to this is to utilise three-dimensional space through drone technology. This doctoral thesis aims at establishing a framework for implementing aerial drones in automotive OEM logistic operations.
As of yet, there is no research on implementing drones in automotive OEM logistic operations. To contribute to filling this gap, this thesis develops a framework for Drone Implementation in Automotive Logistics Operations (DIALOOP) that allows for a close interaction between the strategic and the operative level and can lead automotive companies through a decision and selection process regarding drone technology.
A preliminary version of the framework was developed on a theoretical basis and was then revised using qualitative-empirical data from semi-structured interviews with two groups of experts, i.e. drone experts and automotive experts. The drone expert interviews contributed a current overview of drone capabilities. The automotive experts interview were used to identify intralogistics operations in which drones can be implemented along with the performance measures that can be improved by drone usage.
Furthermore, all interviews explored developments and changes with a foreseeable influence on drone implementation.
The revised framework was then validated using participant validation interviews with automotive experts.
The finalised framework defines a step-by-step process leading from strategic decisions and considerations over the identification of logistics processes suitable for drone implementation and the relevant performance measures to the choice of appropriate drone types based on a drone classification specifically developed in this thesis for an automotive context.
The maintenance of railway infrastructure remains a challenge. Data acquisition technologies have evolved because of Industry 4.0, expanding the capabilities of predictive maintenance. Despite the advances, the potential of these emerging technologies has not been fully realised. This paper presents a technology selection framework in support of railway infrastructure predictive maintenance, which is based on qualitative methods. It consists of three stages, including the mapping of the infrastructure characteristics with the identified technologies, the evaluation of the most appropriate technologies, and the sourcing thereof. This presents the collective decision support output of the framework.
This paper presents the concept of the system architecture of a flexible cyber-physical factory control system. The system allows the automation of process structures using cyber-physical fractal nodes. These nodes have a functional and independent form and can be clustered to larger structures. This makes it possible to equip the factory with a flexible, freely scalable, modular system. The description of this system architecture and the associated rules and conditions is outlined in the concept.
In smart factories, maintenance is still an important aspect to safeguard the performance of their production. Especially in case of failures of machine components diagnosis is a time-consuming task. This paper presents an approach for a cyber-physical failure management system, which uses information from machines such as programmable logic controller or sensor data and IT systems to support the diagnosis and repairing process. Key element is a model combining the different information sources to detect deviations and to determine a probable failed component. Furthermore, the approach is prototypically implemented for leakage detection in compressed air networks.
Towards a sustainable future, looking beyond the system boundaries of a single manufacturing company is necessary to promote meaningful collaborations in terms of circular economy principles. In this context digital data processing technologies to connect the potential collaborators are seen as enablers to make use of proven collaborative circular business models (CCBMs). Since most of such data processing technologies rely on features to describe the entities involved, it is essential to provide guidance for identifying and selecting the relevant and most appropriate ones. Defining critical success factors (CSFs) is considered a suitable instrument to describe the decisive factors. A systematic literature review (SLR), followed by a qualitative synthesis is investigating two scientific fields of work, namely (1) the general relevant features of CCBMs and, (2) methodologies for determining CSFs. This results in the development of a conceptual framework which provides guidance for digital applications that perform further digital processing based on the relevant CSFs relating to the specific CCBM.
A closed-loop control for a cooperative innovation culture in interorganizational R&D projects
(2022)
Since project managers only have a limited authority in interorganizational R&D projects a cooperative innovation culture is essential for team cohesion and thus for achieving project scope in time and cost. For its development different factors depending on underlying values are essential. These factors must be learned iteratively by the project members so that they are living the values of a cooperative innovation culture. Hence, this paper raises the following research question: “How to control living the values of a cooperative innovation culture in interorganizational R&D projects?” To answer this question, a closed-loop control for a cooperative innovation culture is developed. The developed closed-loop control system includes several different functional units which show essential roles and several different variables which show what to consider and design in the control system. In addition, the developed closed-loop control system is generalized for other types of projects such as intraorganizational projects.
This article analyses and compares the performance of regulators in the fields of finance and sport, especially cycling. I hypothesize that the courses of crises or scandals is the best time to study the lessons of regulatory response. First, I take into account the differences in both finance and cycling by looking at the nature of the rules and institutions governing the field. Second, I estimate the attention effect on new regulation in response to crises or scandals. The interest of the paper is in the alignment of incentives to prevent regulatory capture and to ensure accountability and enforceability. The paper concludes that the differences hold important lessons that call for the reform of rules and institutions governing finance and cycling alike.
Academic research is vital for innovation and industrial growth. However, a potential burden of processing ever more knowledge could be affecting research output and researchers’ careers. We look at a dataset of researchers who have published in journals in the field of economics during a period of 45 years. For a subset of these researchers, we amass data from journals listed in the EconLit database, supplemented with years of birth from public sources. Our results show an increase in the age of researchers at their first publication, in the number of articles referenced in debut articles, and in the number of co-authors. Simultaneously, we observe a decline in the probability of researchers changing research fields. Our findings extend earlier findings on patents and hint at a burden of knowledge pervading different areas of human progress. Moreover, our results indicate that researchers develop strategies of specialisation to deal with this challenge.
The 21st century: an era where emojis and hashtags find their way into every sentence, where taking selfies, live tweeting and mining bitcoin are the norm, and where Insta-culture dictates what we say and do. This is the era into which the digital native was born. With so many changes in every aspect of our lives, how is it that one of the most influential aspects, our education, has remained unchanged? Our education system not only fails to appeal to today’s students, but more importantly, it fails to equip them with the skills required in the 21st Century. It is thus of no surprise that industries feel graduates entering the workplace lack skills in critical thinking, problem solving and self-directed learning. AI, machine learning and big data: Tools and mechanisms we so eagerly incorporate to create smart factories yet are hesitant to use elsewhere. Gamification and games have shown great results in education and training; with most research suggesting a stronger focus on personalization and adaptation. When combined with analytics and machine learning, the potential of games is yet to be realized. A real-time adaptive game would not only always present an appropriate degree of challenge for the individual but would allow for a shift in focus from the recitation of facts, to the application of information filtered to solve the particular problem at hand. South Africa, a country faced with a severe skills gap, could benefit greatly from games. If used correctly, they may just offer a desperately needed contribution toward equipping both current and future employees with the skills needed to survive in the 21st century. This paper explores the feasibility of using such games for enhanced knowledge dissemination and the upskilling of the workforce.
Today 40 Gbps is in development at IEEE 802.3bq over four pair balanced cabling. In this paper, we describe a transmission experiment of 25 Gbps enabling either a single pair transmission of 25 Gbps over a 30 meter balanced cabling channel, or a 100 Gbps transmission via a four-pair balanced channel. A scalable matrix modeling tool is introduced which allows the prediction of transmission characteristics of a channel taking mode conversion into account . We applied this tool to characterize PCB-channels including the magnetics and PCB for a four-pair 100 Gbps transmission. We evaluated prototype cables and connecting hardware for frequencies up to 2 GHz and beyond. Finally we investigated possible line encoding schemes and provide measurement results of a transmission over 30 m with a data rate of 25 Gbps per twisted pair.