Applying Platform Design to Improve Product-Service Systems Collaborative Development

Part 3: Product-Service Systems

Reducing fuel consumption through modular vehicle architectures

By identifying energy waste streams in vehicles fuel consumption and introducing the concept of lean driving systems, a technological gap for reducing fuel consumption was identified. This paper proposes a solution to overcome this gap, through a modular vehicle architecture aligned with driving patterns. It does not address detailed technological solutions; instead it models the potential effects in fuel consumption through a modular concept of a vehicle and quantifies their dependence on vehicle design parameters (manifesting as the vehicle mass) and user behavior parameters (driving patterns manifesting as the use of a modular car in lighter and heavier mode, in urban and highway cycles). Modularity has been functionally applied in automotive industry as manufacture and assembly management strategies; here it is thought as a product development strategy for flexibility in use, driven by environmental concerns and enabled by social behaviors. The authors argue this concept is a step forward in combining technological solutions and social behavior, of which eco-driving is a vivid example, and potentially evolutionary to a lean, more sustainable, driving culture.

Engineering modular viral scaffolds for targeted bacterial population editing

Bacteria are central to human health and disease, but existing tools to edit microbial consortia are limited. For example, broad-spectrum antibiotics are unable to precisely manipulate bacterial communities. Bacteriophages can provide highly specific targeting of bacteria, but assembling well-defined phage cocktails solely with natural phages can be a time-, labor- and cost-intensive process. Here, we present a synthetic biology strategy to modulate phage host ranges by engineering phage genomes in Saccharomyces cerevisiae. We used this technology to redirect Escherichia coli phage scaffolds to target pathogenic Yersinia and Klebsiella bacteria, and conversely, Klebsiella phage scaffolds to target E. coli by modular swapping of phage tail components. The synthetic phages achieved efficient killing of their new target bacteria and were used to selectively remove bacteria from multi-species bacterial communities with cocktails based on common viral scaffolds. We envision this approach accelerating phage biology studies and enabling new technologies for bacterial population editing.

Modular support for developing mobile ad hoc applications

Abstract This PhD thesis addresses the issue of alleviating the burden of developing ad hoc applications. Such applications have the particularity of running on mobile devices, communicating in a peer-to-peer manner and implement some proximity-based semantics. A typical example of such application can be a radar application where users see their avatar as well as the avatars of their friends on a map on their mobile phone. Such application become increasingly popular with the advent of the latest generation of mobile smart phones with their impressive computational power, their peer-to-peer communication capabilities and their location detection technology. Unfortunately, the existing programming support for such applications is limited, hence the need to address this issue in order to alleviate their development burden. This thesis specifically tackles this problem by providing several tools for application development support. First, it provides the location-based publish/subscribe service (LPSS), a communication abstraction, which elegantly captures recurrent communication issues and thus allows to dramatically reduce the code complexity. LPSS is implemented in a modular manner in order to be able to target two different network architectures. One pragmatic implementation is aimed at mainstream infrastructure-based mobile networks, where mobile devices can communicate through fixed antennas. The other fully decentralized implementation targets emerging mobile ad hoc networks (MANETs), where no fixed infrastructure is available and communication can only occur in a peer-to-peer fashion. For each of these architectures, various implementation strategies tailored for different application scenarios that can be parametrized at deployment time. Second, this thesis provides two location-based message diffusion protocols, namely 6Shot broadcast and 6Shot multicast, specifically aimed at MANETs and fine tuned to be used as building blocks for LPSS. Finally this thesis proposes Phomo, a phone motion testing tool that allows to test proximity semantics of ad hoc applications without having to move around with mobile devices. These different developing support tools have been packaged in a coherent middleware framework called Pervaho.

Licensing Model Development for Small Modular Reactors (SMRs) - Focusing on the Finnish Regulatory Framework

Recently, Small Modular Reactors (SMRs) have attracted increased public discussion. While large nuclear power plant new build projects are facing challenges, the focus of attention is turning to small modular reactors. One particular project challenge arises in the area of nuclear licensing, which plays a significant role in new build projects affecting their quality as well as costs and schedules. This dissertation - positioned in the field of nuclear engineering but also with a significant section in the field of systems engineering - examines the nuclear licensing processes and their suitability for the characteristics of SMRs. The study investigates the licensing processes in selected countries, as well as other safety critical industry fields. Viewing the licensing processes and their separate licensing steps in terms of SMRs, the study adopts two different analysis theories for review and comparison. The primary data consists of a literature review, semi-structured interviews, and questionnaire responses concerning licensing processes and practices. The result of the study is a recommendation for a new, optimized licensing process for SMRs. The most important SMR-specific feature, in terms of licensing, is the modularity of the design. Here the modularity indicates multi-module SMR designs, which creates new challenges in the licensing process. As this study focuses on Finland, the main features of the new licensing process are adapted to the current Finnish licensing process, aiming to achieve the main benefits with minimal modifications to the current process. The application of the new licensing process is developed using Systems Engineering, Requirements Management, and Project Management practices and tools. Nuclear licensing includes a large amount of data and documentation which needs to be managed in a suitable manner throughout the new build project and then during the whole life cycle of the nuclear power plant. To enable a smooth licensing process and therefore ensure the success of the new build nuclear power plant project, management processes and practices play a significant role. This study contributes to the theoretical understanding of how licensing processes are structured and how they are put into action in practice. The findings clarify the suitability of different licensing processes and their selected licensing steps for SMR licensing. The results combine the most suitable licensing steps into a new licensing process for SMRs. The results are also extended to the concept of licensing management practices and tools.

Modular Double-Cascade Converter

Medium-voltage motor drives extend the power rating of AC motor drives in industrial applications. Multilevel converters are gaining an ever-stronger foothold in this field. This doctoral dissertation introduces a new topology to the family of modular multilevel converters: the modular double-cascade converter. The modularity of the converter is enabled by the application of multiwinding mediumfrequency isolation transformers. Owing to the innovative transformer link, the converter presents many advantageous properties at a concept level: modularity, high input and output power quality, small footprint, and wide variety of applications, among others. Further, the research demonstrates that the transformer link also plays a key role in the disadvantages of the topology. An extensive simulation study on the new converter is performed. The focus of the simulation study is on the development of control algorithms and the feasibility of the topology. In particular, the circuit and control concepts used in the grid interface, the coupling configurations of the load inverter, and the transformer link operation are thoroughly investigated. Experimental results provide proof-of-concept results on the operation principle of the converter. This work concludes a research collaboration project on multilevel converters between LUT and Vacon Plc. The project was active from 2009 until 2014.

Design and Development of 3-DOF Modular Micro Parallel Kinematic Manipulator

This paper presents the research and development of a 3-legged micro Parallel Kinematic Manipulator (PKM) for positioning in micro-machining and assembly operations. The structural characteristics associated with parallel manipulators are evaluated and the PKMs with translational and rotational movements are identified. Based on these identifications, a hybrid 3-UPU (Universal Joint-Prismatic Joint-Universal Joint) parallel manipulator is designed and fabricated. The principles of the operation and modeling of this micro PKM is largely similar to a normal size Stewart Platform (SP). A modular design methodology is introduced for the construction of this micro PKM. Calibration results of this hybrid 3-UPU PKM are discussed in this paper.

PMCRI: a parallel modular classification rule induction framework

In a world where massive amounts of data are recorded on a large scale we need data mining technologies to gain knowledge from the data in a reasonable time. The Top Down Induction of Decision Trees (TDIDT) algorithm is a very widely used technology to predict the classification of newly recorded data. However alternative technologies have been derived that often produce better rules but do not scale well on large datasets. Such an alternative to TDIDT is the PrismTCS algorithm. PrismTCS performs particularly well on noisy data but does not scale well on large datasets. In this paper we introduce Prism and investigate its scaling behaviour. We describe how we improved the scalability of the serial version of Prism and investigate its limitations. We then describe our work to overcome these limitations by developing a framework to parallelise algorithms of the Prism family and similar algorithms. We also present the scale up results of a first prototype implementation.

J-PMCRI: a methodology for inducing pre-pruned modular classification rules

Inducing rules from very large datasets is one of the most challenging areas in data mining. Several approaches exist to scaling up classification rule induction to large datasets, namely data reduction and the parallelisation of classification rule induction algorithms. In the area of parallelisation of classification rule induction algorithms most of the work has been concentrated on the Top Down Induction of Decision Trees (TDIDT), also known as the ‘divide and conquer’ approach. However powerful alternative algorithms exist that induce modular rules. Most of these alternative algorithms follow the ‘separate and conquer’ approach of inducing rules, but very little work has been done to make the ‘separate and conquer’ approach scale better on large training data. This paper examines the potential of the recently developed blackboard based J-PMCRI methodology for parallelising modular classification rule induction algorithms that follow the ‘separate and conquer’ approach. A concrete implementation of the methodology is evaluated empirically on very large datasets.

The NutriChip project--translating technology into nutritional knowledge

Advances in food transformation have dramatically increased the diversity of products on the market and, consequently, exposed consumers to a complex spectrum of bioactive nutrients whose potential risks and benefits have mostly not been confidently demonstrated. Therefore, tools are needed to efficiently screen products for selected physiological properties before they enter the market. NutriChip is an interdisciplinary modular project funded by the Swiss programme Nano-Tera, which groups scientists from several areas of research with the aim of developing analytical strategies that will enable functional screening of foods. The project focuses on postprandial inflammatory stress, which potentially contributes to the development of chronic inflammatory diseases. The first module of the NutriChip project is composed of three in vitro biochemical steps that mimic the digestion process, intestinal absorption, and subsequent modulation of immune cells by the bioavailable nutrients. The second module is a miniaturised form of the first module (gut-on-a-chip) that integrates a microfluidic-based cell co-culture system and super-resolution imaging technologies to provide a physiologically relevant fluid flow environment and allows sensitive real-time analysis of the products screened in vitro. The third module aims at validating the in vitro screening model by assessing the nutritional properties of selected food products in humans. Because of the immunomodulatory properties of milk as well as its amenability to technological transformation, dairy products have been selected as model foods. The NutriChip project reflects the opening of food and nutrition sciences to state-of-the-art technologies, a key step in the translation of transdisciplinary knowledge into nutritional advice.

The ciao modular, standalone compiler and its generic program processing library

Ciao Prolog incorporates a module system which allows sepárate compilation and sensible creation of standalone executables. We describe some of the main aspects of the Ciao modular compiler, ciaoc, which takes advantage of the characteristics of the Ciao Prolog module system to automatically perform sepárate and incremental compilation and efficiently build small, standalone executables with competitive run-time performance, ciaoc can also detect statically a larger number of programming errors. We also present a generic code processing library for handling modular programs, which provides an important part of the functionality of ciaoc. This library allows the development of program analysis and transformation tools in a way that is to some extent orthogonal to the details of module system design, and has been used in the implementation of ciaoc and other Ciao system tools. We also describe the different types of executables which can be generated by the Ciao compiler, which offer different tradeoffs between executable size, startup time, and portability, depending, among other factors, on the linking regime used (static, dynamic, lazy, etc.). Finally, we provide experimental data which illustrate these tradeoffs.

TELMA: Technology enhanced learning environment for minimally invasive surgery

Background: Cognitive skills training for minimally invasive surgery has traditionally relied upon diverse tools, such as seminars or lectures. Web technologies for e-learning have been adopted to provide ubiquitous training and serve as structured repositories for the vast amount of laparoscopic video sources available. However, these technologies fail to offer such features as formative and summative evaluation, guided learning, or collaborative interaction between users. Methodology: The "TELMA" environment is presented as a new technology-enhanced learning platform that increases the user's experience using a four-pillared architecture: (1) an authoring tool for the creation of didactic contents; (2) a learning content and knowledge management system that incorporates a modular and scalable system to capture, catalogue, search, and retrieve multimedia content; (3) an evaluation module that provides learning feedback to users; and (4) a professional network for collaborative learning between users. Face validation of the environment and the authoring tool are presented. Results: Face validation of TELMA reveals the positive perception of surgeons regarding the implementation of TELMA and their willingness to use it as a cognitive skills training tool. Preliminary validation data also reflect the importance of providing an easy-to-use, functional authoring tool to create didactic content. Conclusion: The TELMA environment is currently installed and used at the Jesús Usón Minimally Invasive Surgery Centre and several other Spanish hospitals. Face validation results ascertain the acceptance and usefulness of this new minimally invasive surgery training environment.

Dreams: A tool for the design of dynamically reconfigurable embedded and modular systems

Dynamically Reconfigurable Systems are attracting a growing interest, mainly due to the emergence of novel applications based on this technology. However, commercial tools do not provide enough flexibility to design solutions, while keeping an acceptable design productivity. In this paper, a novel design flow is proposed, targeting dynamically reconfigurable systems. It is fully supported by a tool called Dreams, which is able to implement flexible systems, starting from a set of netlists corresponding to the modules, as well as a system description provided by the user. The tool automatically post-processes the nets, implementing a solution for the communications between reconfigurable regions, as well as the handling of routing conflicts, by means of a custom router. Since the design process of every module and the static system are independent, the proposed flow is compatible with system upgrade at run-time. In this paper, a use case corresponding to the design of a highly regular and parallel mesh-type architecture is described, in order to show the architectural flexibility offered by the tool.