Model-based evaluation environment for sustainability

Nowadays, many companies are using enterprise models within an enterprise planning system to develop their business strategy. In order to follow a holistic sustainability approach, environmental, economic and social aspects have to be integrated into these models on a strategic, tactical and operational level. This results in an increased model complexity and requires mechanisms to ensure consistency and efficient model management. Furthermore, the user is confronted with a variety of data and is not able to perform model validation and verification as well as using the enterprise model as a tool for operational support. This paper presents an approach of a model-based evaluation environment by extending enterprise models with sustainability artefacts, to empower the users within their decision-making towards a sustainable enterprise orientation. A framework for contextual enterprise modelling is applied to provide configurable individual model evaluation and application views

Model-based evaluation environment for sustainability

Nowadays, many companies are using enterprise models within an enterprise planning system to develop their business strategy. In order to follow a holistic sustainability approach, environmental, economic and social aspects have to be integrated into these models on a strategic, tactical and operational level. This results in an increased model complexity and requires mechanisms to ensure consistency and efficient model management. Furthermore, the user is confronted with a variety of data and is not able to perform model validation and verification as well as using the enterprise model as a tool for operational support. This paper presents an approach of a model-based evaluation environment by extending enterprise models with sustainability artefacts, to empower the users within their decision-making towards a sustainable enterprise orientation. A framework for contextual enterprise modelling is applied to provide configurable individual model evaluation and application views

Sustainability in Model-based Planning and Control of Global Value Creation Networks

Manufacturing companies are affected by an increasing complexity driven thru fast changing requirements in the global market. To meet the large catalogue of requirements, enterprises are forming global value creation networks and provide services jointly. The existing time pressure and the involvement of many stakeholders results in a demand of methods and tools for a quick configuration of such networks. Beside the management of material, information and money flows the quest of a sustainable corporate development poses a further challenge for the decision makers. The consideration of sustainability in business process management is one approach to take also social, economic and environmental aspects within global value creation networks into account. Reviewing existing modelling techniques shows that the requirements for a fast configuration and an adequate management of sustainability are just insufficiently addressed or are raising the complexity further. This paper will explore capabilities of an enterprise modelling technique which supports an integrated handling of network configuration and sustainability management in a fast and efficient manner.DFG, 199828953, SFB 1026: Sustainable Manufacturing - Globale Wertschöpfung nachhaltig gestalte

Development of a Quality Gate Reference Model for FDM Processes

Additive manufacturing (AM) enables industries to accomplish mass customization by creating complex products in small batches. For this purpose, fused deposition modeling (FDM) is widely used in 3D printing where the material is applied layer-by-layer from a digital model to form a three-dimensional object. There still exist problems in FDM processes regarding the failure rate of printed parts. Failures vary from deformed geometry, clogged nozzles, and dimensional inaccuracies to small parts not being printed that may be attributed to various process steps (e.g., poor quality CAD models, converting issues, overheating, poor quality filament, etc.). The majority of these defects are preventable and are caused by imprudent try-and-error print processes and troubleshooting quality control. The aim of this chapter is to propose a quality gate reference process with defined requirement criteria to prevent the occurrence of defects. The framework shall be applied in quality control and in-situ process monitoring to enhance overall manufacturing quality

Proceedings of the First Karlsruhe Service Summit Workshop - Advances in Service Research, Karlsruhe, Germany, February 2015 (KIT Scientific Reports ; 7692)

Since April 2008 KSRI fosters interdisciplinary research in order to support and advance the progress in the service domain. KSRI brings together academia and industry while serving as a European research hub with respect to service science. For KSS2015 Research Workshop, we invited submissions of theoretical and empirical research dealing with the relevant topics in the context of services including energy, mobility, health care, social collaboration, and web technologies

Theorie und Praxis in der Open-Source-Produktentwicklung

Within the last decade numerous open source product development (OSPD) projects have emerged extending the concept of open source software in the world of tangible products. These projects are characterized by the free revealing of their product development information with the intention of stimulating community feedback, product replications and collaborative development. Based on empirical data acquired from 76 projects, this contribution characterizes how OSPD projects use the public space offered by the internet and the existing online sharing platforms to stimulate attention and contributions from product development communities. It particularly focusses on the identification of gaps between actual practices and generally acknowledged best practices. On the one hand, the identified gaps allow deriving conclusions on the current state of development of OSPD. On the other hand, this indicates a general heterogeneity in the approaches followed by OSPD projects which is discussed

Does adherence to a quality indicator regarding early weaning from invasive ventilation improve economic outcome? A single-centre retrospective study

ObjectivesTo measure and assess the economic impact of adherence to a single quality indicator (QI) regarding weaning from invasive ventilation.DesignRetrospective observational single-centre study, based on electronic medical and administrative records.SettingIntensive care unit (ICU) of a German university hospital, reference centre for acute respiratory distress syndrome.ParticipantsRecords of 3063 consecutive mechanically ventilated patients admitted to the ICU between 2012 and 2017 were extracted, of whom 583 were eligible adults for further analysis. Patients’ weaning protocols were evaluated for daily adherence to quality standards until ICU discharge. Patients with <65% compliance were assigned to the low adherence group (LAG), patients with ≥65% to the high adherence group (HAG).Primary and secondary outcome measuresEconomic healthcare costs, clinical outcomes and patients’ characteristics.ResultsThe LAG consisted of 378 patients with a median negative economic results of −€3969, HAG of 205 (−€1030), respectively (p<0.001). Median duration of ventilation was 476 (248; 769) hours in the LAG and 389 (247; 608) hours in the HAG (p<0.001). Length of stay (LOS) in the LAG on ICU was 21 (12; 35) days and 16 (11; 25) days in the HAG (p<0.001). LOS in the hospital was 36 (22; 61) days in the LAG, and within the HAG, respectively, 26 (18; 48) days (p=0.001).ConclusionsHigh adherence to this single QI is associated with better clinical outcome and improved economic returns. Therefore, the results support the adherence to QI. However, the examined QI does not influence economic outcome as the decisive factor

Harmonized and Open Energy Dataset for Modeling a Highly Renewable Brazilian Power System

Improvements in modeling energy systems of populous emerging economies are highly decisive for a successful global energy transition. The models used – increasingly published open source – still suffer from the lack of appropriate open data. As an illustrative example, we take the Brazilian energy system, which has great potential for renewable energy resources but still relies heavily on fossil fuels. We provide a comprehensive open dataset for scenario analyses, which can be directly used with the popular open energy system model PyPSA and other modeling frameworks. It includes three categories: 1) time series data of variable renewable potentials, electricity load profiles, inflows for the hydropower plants, and cross-border electricity exchanges, 2) geo-referenced data for 27 defined regions, and 3) tabular data, which contains power plant data with installed and planned generation capacities, aggregated grid network topology, biomass thermal plant potential, as well as scenarios of energy demand. This data fosters global or country-specific energy system studies based on open data relevant to decarbonizing Brazil’s energy system

Bringing the margin to the focus: 10 challenges for riparian vegetation science and management

Riparian zones are the paragon of transitional ecosystems, providing critical habitat and ecosystem services that are especially threatened by global change. Following consultation with experts, 10 key challenges were identified to be addressed for riparian vegetation science and management improvement: (1) Create a distinct scientific community by establishing stronger bridges between disciplines; (2) Make riparian vegetation more visible and appreciated in society and policies; (3) Improve knowledge regarding biodiversity—ecosystem functioning links; (4) Manage spatial scale and context-based issues; (5) Improve knowledge on social dimensions of riparian vegetation; (6) Anticipate responses to emergent issues and future trajectories; (7) Enhance tools to quantify and prioritize ecosystem services; (8) Improve numerical modeling and simulation tools; (9) Calibrate methods and increase data availability for better indicators and monitoring practices and transferability; and (10) Undertake scientific validation of best management practices. These challenges are discussed and critiqued here, to guide future research into riparian vegetation

Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review

Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to provide an overview of the main spectral technologies and retrieval approaches for detecting crop stress in agriculture. Firstly, we present integrated views on: i) biotic and abiotic stress factors, the phases of stress, and respective plant responses, and ii) the affected traits, appropriate spectral domains and corresponding methods for measuring traits remotely. Secondly, representative results of a systematic literature analysis are highlighted, identifying the current status and possible future trends in stress detection and monitoring. Distinct plant responses occurring under short-term, medium-term or severe chronic stress exposure can be captured with remote sensing due to specific light interaction processes, such as absorption and scattering manifested in the reflected radiance, i.e. visible (VIS), near infrared (NIR), shortwave infrared, and emitted radiance, i.e. solar-induced fluorescence and thermal infrared (TIR). From the analysis of 96 research papers, the following trends can be observed: increasing usage of satellite and unmanned aerial vehicle data in parallel with a shift in methods from simpler parametric approaches towards more advanced physically-based and hybrid models. Most study designs were largely driven by sensor availability and practical economic reasons, leading to the common usage of VIS-NIR-TIR sensor combinations. The majority of reviewed studies compared stress proxies calculated from single-source sensor domains rather than using data in a synergistic way. We identified new ways forward as guidance for improved synergistic usage of spectral domains for stress detection: (1) combined acquisition of data from multiple sensors for analysing multiple stress responses simultaneously (holistic view); (2) simultaneous retrieval of plant traits combining multi-domain radiative transfer models and machine learning methods; (3) assimilation of estimated plant traits from distinct spectral domains into integrated crop growth models. As a future outlook, we recommend combining multiple remote sensing data streams into crop model assimilation schemes to build up Digital Twins of agroecosystems, which may provide the most efficient way to detect the diversity of environmental and biotic stresses and thus enable respective management decisions