Linking design and manufacturing domains via web-based and enterprise integration technologies

The manufacturing industry faces many challenges such as reducing time-to-market and cutting costs. In order to meet these increasing demands, effective methods are need to support the early product development stages by bridging the gap of communicating early design ideas and the evaluation of manufacturing performance. This paper introduces methods of linking design and manufacturing domains using disparate technologies. The combined technologies include knowledge management supporting for product lifecycle management (PLM) systems, enterprise resource planning (ERP) systems, aggregate process planning systems, workflow management and data exchange formats. A case study has been used to demonstrate the use of these technologies, illustrated by adding manufacturing knowledge to generate alternative early process plan which are in turn used by an ERP system to obtain and optimise a rough-cut capacity plan

Patching task-level robot controllers based on a local µ-calculus formula

We present a method for mending strategies for GR(1) specifications. Given the addition or removal of edges from the game graph describing a problem (essentially transition rules in a GR(1) specification), we apply a µ-calculus formula to a neighborhood of states to obtain a “local strategy” that navigates around the invalidated parts of an original synthesized strategy. Our method may thus avoid global resynthesis while recovering correctness with respect to the new specification. We illustrate the results both in simulation and on physical hardware for a planar robot surveillance task

A standardization approach to Virtual Commissioning strategies in complex production environments

The ongoing industrial revolution puts high demands on the component manufacturers and suppliers to meet the tough requirements set by the development industries to follow the technological advancement of highly digitalized factories with more future-oriented applications as Virtual Commissioning for cyber-physical systems. This paper provides a production system lifecycle assessment regarding the technical specification strategies using Virtual Commissioning for implementation and integration of new systems or plants and its predicted future challenges. With the use of standards and a common language practice between a purchaser/contractor procurement situation and across the different technical disciplines internally and externally, the implementation strategies is reiterated to achieve a new sustainable business model. The paper investigates different types of production systems and how a defined classification framework of different levels of Virtual Commissioning can connect the implementation requirements to a desired solution. This strategy includes aspects of standardization, communication, process lifecycle, and predicted cost parameters

Selective targeting of proteins by hybrid polyoxometalates: Interaction between a bis-biotinylated hybrid conjugate and avidin

The Keggin-type polyoxometalate [\u3b3-SiW10O36]8 12 was covalently modified to obtain a bis-biotinylated conjugate able to bind avidin. Spectroscopic studies such as UV-vis, fluorimetry, circular dichroism, coupled to surface plasmon resonance technique were used to highlight the unique interplay of supramolecular interactions between the homotetrameric protein and the bis-functionalized polyanion. In particular, the dual recognition mechanism of the avidin encompasses (i) a complementary electrostatic association between the anionic surface of the polyoxotungstate and each positively charged avidin subunit and (ii) specific host-guest interactions between each biotinylated arm and a corresponding pocket on the tetramer subunits. The assembly exhibits peroxidase-like reactivity and it was used in aqueous solution for L-methionine methyl ester oxidation by H2O2. The recognition phenomenon was then exploited for the preparation of layer-by-layer films, whose structural evolution was monitored in situ by ATR-FTIR spectroscopy. Finally, cell tracking studies were performed by exploiting the specific interactions with a labeled streptavidin

Tools for Assessing Climate Impacts on Fish and Wildlife

Climate change is already affecting many fish and wildlife populations. Managing these populations requires an understanding of the nature, magnitude, and distribution of current and future climate impacts. Scientists and managers have at their disposal a wide array of models for projecting climate impacts that can be used to build such an understanding. Here, we provide a broad overview of the types of models available for forecasting the effects of climate change on key processes that affect fish and wildlife habitat (hydrology, fire, and vegetation), as well as on individual species distributions and populations. We present a framework for how climate-impacts modeling can be used to address management concerns, providing examples of model-based assessments of climate impacts on salmon populations in the Pacific Northwest, fire regimes in the boreal region of Canada, prairies and savannas in the Willamette Valley-Puget Sound Trough-Georgia Basin ecoregion, and marten Martes americana populations in the northeastern United States and southeastern Canada. We also highlight some key limitations of these models and discuss how such limitations should be managed. We conclude with a general discussion of how these models can be integrated into fish and wildlife management

Location-Based Service and Location-Contextualizing Service: Conceptualizing the Co-creation of Value with Location Information

Location-Based Service (LBS) is an established concept and enables providers and customers to co-create value-in-use, building on location information on humans or mobile objects. LBS, however, is not the only way to co-create value by using location information, as LBS does not target immovable objects, such as infrastructure. Informed by a literature review, we set out to conceptualize Location-Contextualizing Service (LCS) as a class of service complementing LBS. LCS focuses on improving existing service, based on enabling users with static positions to contextualize and analyze data on immovable objects. We describe the conceptual properties of LCS vis- ́a-vis LBS and outline why we see Geographic Information System (GIS) as a crucial class of systems to enable LCS. We discuss why LCS highlights new aspects and shifts research priorities that constitute the LBS and GIS fields today

Bridging Vision and Dynamic Legged Locomotion

Legged robots have demonstrated remarkable advances regarding robustness and versatility in the past decades. The questions that need to be addressed in this field are increasingly focusing on reasoning about the environment and autonomy rather than locomotion only. To answer some of these questions visual information is essential. If a robot has information about the terrain it can plan and take preventive actions against potential risks. However, building a model of the terrain is often computationally costly, mainly because of the dense nature of visual data. On top of the mapping problem, robots need feasible body trajectories and contact sequences to traverse the terrain safely, which may also require heavy computations. This computational cost has limited the use of visual feedback to contexts that guarantee (quasi-) static stability, or resort to planning schemes where contact sequences and body trajectories are computed before starting to execute motions. In this thesis we propose a set of algorithms that reduces the gap between visual processing and dynamic locomotion. We use machine learning to speed up visual data processing and model predictive control to achieve locomotion robustness. In particular, we devise a novel foothold adaptation strategy that uses a map of the terrain built from on-board vision sensors. This map is sent to a foothold classifier based on a convolutional neural network that allows the robot to adjust the landing position of the feet in a fast and continuous fashion. We then use the convolutional neural network-based classifier to provide safe future contact sequences to a model predictive controller that optimizes target ground reaction forces in order to track a desired center of mass trajectory. We perform simulations and experiments on the hydraulic quadruped robots HyQ and HyQReal. For all experiments the contact sequences, the foothold adaptations, the control inputs and the map are computed and processed entirely on-board. The various tests show that the robot is able to leverage the visual terrain information to handle complex scenarios in a safe, robust and reliable manner