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Global vernetzte Supply Chains (SC) führen bei den Unternehmen zu geringeren Kosten, aber zugleich erhöhen diese auch die Abhängigkeit ggü. den Lieferanten und die Störanfälligkeit der SCs wird erhöht. In den vergangenen Jahren haben zudem die Unsicherheiten für die SCs stark zugenommen. Treiber waren hier u.a. der Brexit, Handelskonflikte oder auch die Corona-Pandemie. In diesem Zusammenhang steht verstärkt die Entwicklung neuer SC-Strategien im Fokus der Unternehmen. Dabei wird stark auf die Verbesserung der Resilienz der SCs geachtet, um dadurch u.a. die Risiken für die SCs zu reduzieren. Die Arbeit beschäftigt sich mit den Auswirkungen steigender Unsicherheiten auf das Design sowie die Resilienz von SCs und hat das Ziel zu ermitteln, ob es Änderungen in der SC bedarf, um auf die Auswirkungen steigender Unsicherheiten zu reagieren und wie die Resilienz zukünftig sichergestellt werden kann (Trade-off zwischen Resilienz und Kosteneffizienz). Im Rahmen der Untersuchung erfolgte eine qualitative Forschung in Form von Experteninterviews, da so u.a. spezifische Meinungen oder auch Begründungen und Einstellungen von bestimmten Personen zu den vorliegenden Thematiken ermittelt werden können. Die Ergebnisse zeigen, dass die Kosten weiterhin meist der entscheidende Aspekt sind und es mehr Transparenz, Flexibilität sowie ein besseres Risikomanagement nötig ist. Des Weiteren bedarf es zukünftig u.a. einer größeren Berücksichtigung von Unsicherheiten, eine Erhöhung von Sicherheitsbeständen sowie eine Verringerung der Komplexität der SCs und u.U. mehr Local Sourcing. Es empfiehlt sich eine weitere Untersuchung hinsichtlich der Kosten, die durch Resilienz-Instrumente sowie durch fehlende Resilienz entstehen können, durchzuführen.
Companies have made considerable progress in assessing the sustainability of their processes and products, including the information and communication technology (ICT) sector. However, it is surprising that little attention has been given to the sustainability performance of software products. For this article, we chose a case study approach to explore the extent, to which software manufacturers have considered sustainability criteria for their products. We selected a manufacturer of sustainability management software on the assumption that they would be more likely to integrate elements of sustainability performance in their products. In the case study, we applied a previously developed set of criteria for sustainable software (SCSS) using a questionnaire and experiments, to assess a web-based sustainability management software product regarding its sustainability performance. The assessment finds that despite a sustainability conscious manufacturer, a systematic assessment of sustainability regarding software products is missing in the case study. This implies that sustainability assessment for software products is still novel, corresponding knowledge is missing and suitable tools are not yet being widely applied in the industry. The SCSS presents a suitable approach to close this gap, but it does require further refinement, for example regarding its applicability to web-based software on external servers.
Sustainable software products - Towards assessment criteria for resource and energy efficiency
(2018)
Many authors have proposed criteria to assess the “environmental friendliness” or “sustainability” of software products. However, a causal model that links observable properties of a software product to conditions of it being green or (more general) sustainable is still missing. Such a causal model is necessary because software products are intangible goods and, as such, only have indirect effects on the physical world. In particular, software products are not subject to any wear and tear, they can be copied without great effort, and generate no waste or emissions when being disposed of. Viewed in isolation, software seems to be a perfectly sustainable type of product. In real life, however, software products with the same or similar functionality can differ substantially in the burden they place on natural resources, especially if the sequence of released versions and resulting hardware obsolescence is taken into account. In this article, we present a model describing the causal chains from software products to their impacts on natural resources, including energy sources, from a life-cycle perspective. We focus on (i) the demands of software for hardware capacities (local, remote, and in the connecting network) and the resulting hardware energy demand, (ii) the expectations of users regarding such demands and how these affect hardware operating life, and (iii) the autonomy of users in managing their software use with regard to resource efficiency. We propose a hierarchical set of criteria and indicators to assess these impacts. We demonstrate the application of this set of criteria, including the definition of standard usage scenarios for chosen categories of software products. We further discuss the practicability of this type of assessment, its acceptability for several stakeholders and potential consequences for the eco-labeling of software products and sustainable software design.
The number of additive manufacturing methods and materials is growing rapidly, leaving gaps in the knowledge of specific material properties. A relatively recent addition is the metal-filled filament to be printed similarly to the fused filament fabrication (FFF) technology used for plastic materials, but with additional debinding and sintering steps. While tensile, bending, and shear properties of metals manufactured this way have been studied thoroughly, their fatigue properties remain unexplored. Thus, the paper aims to determine the tensile, fatigue, and impact strengths of Markforged 17-4 PH and BASF Ultrafuse 316L stainless steel to answer whether the metal FFF can be used for structural parts safely with the current state of technology. They are compared to two 316L variants manufactured via selective laser melting (SLM) and literature results. For extrusion-based additive manufacturing methods, a significant decrease in tensile and fatigue strength is observed compared to specimens manufactured via SLM. Defects created during the extrusion and by the pathing scheme, causing a rough surface and internal voids to act as local stress risers, handle the strength decrease. The findings cast doubt on whether the metal FFF technique can be safely used for structural components; therefore, further developments are needed to reduce internal material defects.
Railroads, roads, rivers, and airways are the most common modes of transportation for people and commodities. The cost of different ways of transportation varies according to distance, luxury, size, fragility, and other factors. When the following factors are accounted for, the vehicle might become prohibitively expensive for many individuals. A new means of conveyance has been developed. Elon Musk initially proposed it as the fifth mode of transportation in 2012. For commuters and goods, Hyperloop offers a quick and cost-effective way of transportation. The Hyperloop is essentially a vacuum tube train that transports people or products at incredible speeds while efficiently. Compared to traditional forms of transportation, the Hyperloop is ideal since it is highly energy-efficient, quiet, and self-contained. Increased cargo delivery speeds will be the most evident benefit of this idea to the industry. Hyperloop also has the potential to make a significant contribution to green supply chains. It is a carbon-free form of transportation that has changed inland freight transportation and maritime and air freight transit. It can move freight below, above ground, and under-water. The aim of this paper is to explain this new innovative technology as a development for logistic concepts.
Background: The STarT-MSK-Tool is an adaptation of the well established STarT-Back-Tool, used to risk-stratify patients with a wider range of musculoskeletal presentations.
Objective: To formally translate and cross-culturally adapt the Keele STarT-MSK risk stratification tool into German (STarT-MSKG) and to establish its reliability and validity.
Methods: A formal, multi-step, forward and backward translation approach was used. To assess validity patients aged ≥18 years, with acute, subacute or chronic musculoskeletal presentations in the lumbar spine, hip, knee, shoulder, or neck were included. The prospective cohort was used with initial data collected electronically at the point-of-consultation. Retest and 6-month follow-up questionnaires were sent by email. Test-retest reliability, construct validity, discriminative ability, predictive ability and floor or ceiling effects were analysed using intraclass correlation coefficient, and comparisons with a reference standard (Orebro-Musculoskeletal-Pain-Questionnaire: OMPQ) using correlations, ROC-curves and regression models.
Results: The participants’ (n = 287) mean age was 47 (SD = 15.8) years, 51% were female, with 48.8% at low, 43.6% at medium, and 7.7% at high risk. With ICC = 0.75 (95% CI 0.69; 0.81) test-retest-reliability was good. Construct validity was good with correlations for the STarT-MSKG-Tool against the OMPQ-Tool of rs = 0.74 (95% CI 0.68, 0.79). The ability of the tool [comparison OMPQ] to predict 6-month pain and disability was acceptable with AUC = 0.77 (95% CI 0.71, 0.83) [OMPQ = 0.74] and 0.76 (95% CI 0.69, 0.82) [OMPQ = 0.72] respectively. However, the explained variance (linear/logistic regression) for predicting 6-month pain (21% [OMPQ = 17%]/logistic = 29%) and disability (linear = 20%:[OMPQ = 19%]/logistic = 26%), whilst being comparable to the existing OMPQ reference standard, fell short of the a priori target of ≥30%.
Conclusions: The German version of the STarT-MSK-Tool is a valid instrument for use across multiple musculoskeletal conditions and is availabe for use in clinical practice. Comparison with the OMPQ suggests it is a good alternative.
Stratified care for low back pain (LBP) has been shown to be clinically- and cost-effective in the UK, but its transferability to the German healthcare system is unknown. This study explores LBP patients’ perspectives regarding future implementation of stratified care, through in-depth interviews (n = 12). The STarT-Back-Tool was completed by participants prior to interviews. Interview data were analysed using Grounded Theory. The overarching theme identified from the data was ‘treatment-success’, with subthemes of ‘assessment and treatment planning’, ‘acceptance of the questionnaire’ and ‘contextual factors’. Patients identified the underlying cause of pain as being of great importance (whereas STarT-Back allocates treatment based on prognosis). The integration of the STarT-Back-Tool in consultations was considered helpful as long as it does not disrupt the therapeutic relationship, and was acceptable if tool results are handled confidentially. Results indicate that for patients to find STarT-Back acceptable, the shift from a focus on identifying a cause of pain and subsequent diagnosis, to prediction-orientated treatment planning, must be made clear. Patient ‘buy in’ is important for successful uptake of clinical interventions, and findings can help to inform future strategies for implementing STarT-Back in the Germany, as well as having potential implications for transferability to other similar healthcare systems.
Background: The STarT-Back-Approach (STarT: Subgroups for Targeted Treatment) was developed in the UK and has demonstrated clinical and cost effectiveness. Based on the results of a brief questionnaire, patients with low back pain are stratified into three treatment groups. Since the organisation of physiotherapy differs between Germany and the UK, the aim of this study is to explore German physiotherapists’ views and perceptions about implementing the STarT-Back-Approach.
Methods: Three two-hour think-tank workshops with physiotherapists were conducted. Focus groups, using a semi-structured interview guideline, followed a presentation of the STarT-Back-Approach, with discussions audio recorded, transcribed and qualitatively analysed using content analysis.
Results: Nineteen physiotherapists participated (15 female, mean age 41.2 (SD 8.6) years). Three main themes emerged, each with multiple subthemes: 1) the intervention (15 subthemes), 2) the healthcare context (26 subthemes) and 3) individual characteristics (8 subthemes). Therapists’ perceptions of the extent to which the STarT-Back intervention would require changes to their normal clinical practice varied considerably. They felt that within their current healthcare context, there were significant financial disincentives that would discourage German physiotherapists from providing the STarT-Back treatment pathways, such as the early discharge of low-risk patients with supported self-management materials. They also discussed the need for appropriate standardised graduate and post-graduate skills training for German physiotherapists to treat high-risk patients with a combined physical and psychological approach (e.g., communication skills).
Conclusions: Whilst many German physiotherapists are positive about the STarT-Back-Approach, there are a number of substantial barriers to implementing the matched treatment pathways in Germany. These include financial disincentives within the healthcare system to early discharge of low-risk patients. Therapists also highlighted the need for solutions in respect of scalable physiotherapy training to gain skills in combined physical and psychological approaches.
Background: Stratified care is an up-to-date treatment approach suggested for patients with back pain in several guidelines. A comprehensively studied stratification instrument is the STarT Back Tool (SBT). It was developed to stratify patients with back pain into three subgroups, according to their risk of persistent disabling symptoms. The primary aim was to analyse the disability differences in patients with back pain 12 months after inclusion according to the subgroups determined at baseline using the German version of the SBT (STarT-G). Moreover, the potential to improve prognosis for disability by adding further predictor variables, an analysis for differences in pain intensity according to the STarT-Classification, and discriminative ability were investigated.
Methods: Data from the control group of a randomized controlled trial were analysed. Trial participants were members of a private medical insurance with a minimum age of 18 and indicated as having persistent back pain. Measurements were made for the risk of back pain chronification using the STarT-G, disability (as primary outcome) and back pain intensity with the Chronic Pain Grade Scale (CPGS), health-related quality of life with the SF-12, psychological distress with the Patient Health Questionnaire-4 (PHQ-4) and physical activity. Analysis of variance (ANOVA), multiple linear regression, and area under the curve (AUC) analysis were conducted.
Results: The mean age of the 294 participants was 53.5 (SD 8.7) years, and 38% were female. The ANOVA for disability and pain showed significant differences (p < 0.01) among the risk groups at 12 months. Post hoc Tukey tests revealed significant differences among all three risk groups for every comparison for both outcomes. AUC for STarT-G’s ability to discriminate reference standard ‘cases’ for chronic pain status at 12 months was 0.79. A prognostic model including the STarT-Classification, the variables global health, and disability at baseline explained 45% of the variance in disability at 12 months.
Conclusions: Disability differences in patients with back pain after a period of 12 months are in accordance with the subgroups determined using the STarT-G at baseline. Results should be confirmed in a study developed with the primary aim to investigate those differences.
The integration of genetic algorithms to optimize the networks of value chains could enormously improve the performance of supply chains. For this reason, this paper describes in more detail the application of genetic algorithms in the value chains of the automotive industry. For this purpose, a theoretical model is built up to evaluate whether the application of the model can optimize the value chain. This option is described, analyzed and its restrictions are shown. Instead of looking at the entire network, individual finished goods and their bill of material are used as a basis for optimization, which greatly reduces the complexity of the original problem. The original complexity of the supply chain networks can thus be reduced and considered based on the bill of material.
Fuzzy system based on two-step cascade genetic optimization strategy for tobacco tar prediction
(2019)
There are many challenges in accurately measuring cigarette tar constituents. These include the need for standardized smoke generation methods related to unstable mixtures. In this research were developed algorithms using fusion of artificial intelligence methods to predict tar concentration. Outputs of development are three fuzzy structures optimized with genetic algorithms resulting in genetic algorithm (GA)-FUZZY, GA-adaptive neuro fuzzy inference system (ANFIS), GA-GA-FUZZY algorithms. Proposed algorithms are used for the tar prediction in the cigarette production process. The results of prediction are compared with gas chromatograph (high-performance liquid chromatography (HPLC)) readings.
One key for successful and fluent human-robot-collaboration in disassembly processes is equipping the robot system with higher autonomy and intelligence. In this paper, we present an informed software agent that controls the robot behavior to form an intelligent robot assistant for disassembly purposes. While the disassembly process first depends on the product structure, we inform the agent using a generic approach through product models. The product model is then transformed to a directed graph and used to build, share and define a coarse disassembly plan. To refine the workflow, we formulate "the problem of loosening a connection and the distribution of the work" as a search problem. The created detailed plan consists of a sequence of actions that are used to call, parametrize and execute robot programs for the fulfillment of the assistance. The aim of this research is to equip robot systems with knowledge and skills to allow them to be autonomous in the performance of their assistance to finally improve the ergonomics of disassembly workstations.
Irrigated paddy rice agriculture accounts for a major share of Asia Pacific’s total water withdrawal. Furthermore, climate change induced water scarcity in the Asia-Pacific region is projected to intensify in the near future. Therefore, methods to reduce water consumption through efficiency measures are needed to ensure the long-term (water) sustainability. The irrigation systems, subak of Karangasem, Indonesia, and the tameike of Kunisaki, Japan, are two examples of sustainable paddy rice irrigation. This research, through interviews and an extensive survey, comparatively assessed the socio-environmental sustainability of the two irrigation management systems with special reference to the intensity and nature of social capital, equity of water distribution, water demand, water footprint, and water quality, etc. The prevailing social capital paradigm of each system was also compared to its overall managerial outcomes to analyze how cooperative action contributes to sustainable irrigation management. Both systems show a comparable degree of sustainable irrigation management, ensuring an equitable use of water, and maintain relatively fair water quality due to the land-use practices adapted. However, the systems differ in water demand and water efficiency principally because of the differences in the irrigation management strategies: human and structural. These findings could help devise mechanisms for transitioning to sustainable irrigation management in the commercially-oriented paddy rice agricultural systems across the Asia-Pacific region.
This study will describe how the robotics industry evolved increasingly and a new phase of advanced robotics has emerged, and the relation between humans and robots in the same workplace. Problems of designing safer robots in human-machine interaction systems are urgent research topics in the field of industrial robotics. Many of the problems in industrial robotics are related not just to technological issues, but also to human-robot collaboration also will be discussed as an effective method to tackle this issue is the invention of Collaborative robots.
Background: To facilitate access to evidence-based care for back pain, a German private medical insurance offered a health program proactively to their members. Feasibility and long-term efficacy of this approach were evaluated.
Methods: Using Zelen’s design, adult members of the health insurance with chronic back pain according to billing data were randomized to the intervention (IG) or the control group (CG). Participants allocated to the IG were invited to participate in the comprehensive health program comprising medical exercise therapy and life style coaching, and those allocated to the CG to a longitudinal back pain survey. Primary outcomes were back pain severity (Korff’s Chronic Pain Grade Questionnaire) as well as health-related quality of life (SF-12) assessed by identical online questionnaires at baseline and 2-year follow-up in both study arms. In addition to analyses of covariance, a subgroup analysis explored the heterogeneity of treatment effects among different risks of back pain chronification (STarT Back Tool).
Results: Out of 3462 persons selected, randomized and thereafter contacted, 552 agreed to participate. At the 24-month follow-up, data on 189 of 258 (73.3%) of the IG were available, in the CG on 255 of 294 (86.7%). Significant, small beneficial effects were seen in primary outcomes: Compared to the CG, the IG reported less disability (1.6 vs 2.0; p = 0.025; d = 0.24) and scored better at the SF-12 physical health scale (43.3 vs 41.0; p < 0.007; d = 0.26). No effect was seen in back pain intensity and in the SF-12 mental health scale. Persons with medium or high risk of back pain chronification at baseline responded better to the health program in all primary outcomes than the subgroup with low risk at baseline.
Conclusions: After 2 years, the proactive health program resulted in small positive long-term improvements. Using risk screening prior to inclusion in the health program might increase the percentage of participants deriving benefits from it.
The data presented here contain information on cheating behavior from experiments and general self-reported attitudes related to honesty-related social norms and trust, together with individual-level demographic variables. Our sample included 493 university students in five countries, namely, Germany, Vietnam, Taiwan, China, and Japan. The experiment was monetarily incentivized based on the performance on a matrix task. The participants also answered a survey questionnaire. The dataset is valuable for academic researchers in sociology, psychology, and economics who are interested in honesty, norms, and cultural differences.
Deep brain stimulation (DBS) is a neurosurgical intervention where electrodes are permanently implanted into the brain in order to modulate pathologic neural activity. The post-operative reconstruction of the DBS electrodes is important for an efficient stimulation parameter tuning. A major limitation of existing approaches for electrode reconstruction from post-operative imaging that prevents the clinical routine use is that they are manual or semi-automatic, and thus both time-consuming and subjective. Moreover, the existing methods rely on a simplified model of a straight line electrode trajectory, rather than the more realistic curved trajectory. The main contribution of this paper is that for the first time we present a highly accurate and fully automated method for electrode reconstruction that considers curved trajectories. The robustness of our proposed method is demonstrated using a multi-center clinical dataset consisting of N = 44 electrodes. In all cases the electrode trajectories were successfully identified and reconstructed. In addition, the accuracy is demonstrated quantitatively using a high-accuracy phantom with known ground truth. In the phantom experiment, the method could detect individual electrode contacts with high accuracy and the trajectory reconstruction reached an error level below 100 μm (0.046 ± 0.025 mm). An implementation of the method is made publicly available such that it can directly be used by researchers or clinicians. This constitutes an important step towards future integration of lead reconstruction into standard clinical care.
Agility and digital trends go hand in hand, but the advantages of digitalization perform a high pressure on the established automotive companies. For years now, automotive groups have no longer been innovation drivers in the industry. This status is reserved for radical companies like Tesla. But is there any chance that conservative companies will reinvent themselves, establish leaner structures and thus regain market dominance and innovation?
Concerns over climate change, air pollution, and oil supply have stimulated the market for battery electric vehicles (BEVs). The environmental impacts of BEVs are typically evaluated through a standardized life-cycle assessment (LCA) methodology. Here, the LCA literature was surveyed with the objective to sketch the major trends and challenges in the impact assessment of BEVs. It was found that BEVs tend to be more energy efficient and less polluting than conventional cars. BEVs decrease exposure to air pollution as their impacts largely result from vehicle production and electricity generation outside of urban areas. The carbon footprint of BEVs, being highly sensitive to the carbon intensity of the electricity mix, may decrease in the nearby future through a shift to renewable energies and technology improvements in general. A minority of LCAs covers impact categories other than carbon footprint, revealing a mixed picture. Up to date little attention is paid so far in LCA to the efficiency advantage of BEVs in urban traffic, the gap between on-road and certified energy consumption, the local exposure to air pollutants and noise and the aging of emissions control technologies in conventional cars. Improvements of BEV components, directed charging, second-life reuse of vehicle batteries, as well as vehicle-to-home and vehicle-to-grid applications will significantly reduce the environmental impacts of BEVs in the future.
Background: Electric vehicles have been identified as being a key technology in reducing future emissions and energy consumption in the mobility sector. The focus of this article is to review and assess the energy efficiency and the environmental impact of battery electric cars (BEV), which is the only technical alternative on the market available today to vehicles with internal combustion engine (ICEV). Electricity onboard a car can be provided either by a battery or a fuel cell (FCV). The technical structure of BEV is described, clarifying that it is relatively simple compared to ICEV. Following that, ICEV can be ‘e-converted’ by experienced personnel. Such an e-conversion project generated reality-close data reported here.
Results: Practicability of today's BEV is discussed, revealing that particularly small-size BEVs are useful. This article reports on an e-conversion of a used Smart. Measurements on this car, prior and after conversion, confirmed a fourfold energy efficiency advantage of BEV over ICEV, as supposed in literature. Preliminary energy efficiency data of FCV are reviewed being only slightly lower compared to BEV. However, well-to-wheel efficiency suffers from 47% to 63% energy loss during hydrogen production. With respect to energy efficiency, BEVs are found to represent the only alternative to ICEV. This, however, is only true if the electricity is provided by very efficient power plants or better by renewable energy production. Literature data on energy consumption and greenhouse gas (GHG) emission by ICEV compared to BEV suffer from a 25% underestimation of ICEV-standardized driving cycle numbers in relation to street conditions so far. Literature data available for BEV, on the other hand, were mostly modeled and based on relatively heavy BEV as well as driving conditions, which do not represent the most useful field of BEV operation. Literature data have been compared with measurements based on the converted Smart, revealing a distinct GHG emissions advantage due to the German electricity net conditions, which can be considerably extended by charging electricity from renewable sources. Life cycle carbon footprint of BEV is reviewed based on literature data with emphasis on lithium-ion batteries. Battery life cycle assessment (LCA) data available in literature, so far, vary significantly by a factor of up to 5.6 depending on LCA methodology approach, but also with respect to the battery chemistry. Carbon footprint over 100,000 km calculated for the converted 10-year-old Smart exhibits a possible reduction of over 80% in comparison to the Smart with internal combustion engine.
Conclusion: Findings of the article confirm that the electric car can serve as a suitable instrument towards a much more sustainable future in mobility. This is particularly true for small-size BEV, which is underrepresented in LCA literature data so far. While CO2-LCA of BEV seems to be relatively well known apart from the battery, life cycle impact of BEV in categories other than the global warming potential reveals a complex and still incomplete picture. Since technology of the electric car is of limited complexity with the exception of the battery, used cars can also be converted from combustion to electric. This way, it seems possible to reduce CO2-equivalent emissions by 80% (factor 5 efficiency improvement).