Predictive model-based quality inspection using Machine Learning and Edge Cloud Computing

© 2020 The Authors The supply of defect-free, high-quality products is an important success factor for the long-term competitiveness of manufacturing companies. Despite the increasing challenges of rising product variety and complexity and the necessity of economic manufacturing, a comprehensive and reliable quality inspection is often indispensable. In consequence, high inspection volumes turn inspection processes into manufacturing bottlenecks. In this contribution, we investigate a new integrated solution of predictive model-based quality inspection in industrial manufacturing by utilizing Machine Learning techniques and Edge Cloud Computing technology. In contrast to state-of-the-art contributions, we propose a holistic approach comprising the target-oriented data acquisition and processing, modelling and model deployment as well as the technological implementation in the existing IT plant infrastructure. A real industrial use case in SMT manufacturing is presented to underline the procedure and benefits of the proposed method. The results show that by employing the proposed method, inspection volumes can be reduced significantly and thus economic advantages can be generated

Scalable anomaly detection in manufacturing systems using an interpretable deep learning approach

Anomaly detection in manufacturing systems has great potential for the prevention of critical quality faults. In recent years, unsupervised deep learning has shown to frequently outperform conventional methods for anomaly detection. However, tuning, deploying and debugging deep learning models is a time-consuming task, limiting their practical applicability in manufacturing systems. We approach this problem by developing a deep learning model that learns interpretable shapes that can be used for anomaly detection in temporal process data. Application of the model to assembly tightening processes in the automotive industry shows a significant improvement in model interpretability and scalability

Systematic combination of Lean Management with digitalization to improve production systems on the example of Jidoka 4.0

© The Author(s) 2020. Lean Management builds the basis for efficient production systems for many industrial companies. However, lots of potentials of Lean Management have been lifted and information and communication technologies in the context of digitalization and cyber-physical production systems (CPPS) offer new possibilities to enhance the performance of companies. Even though surveys indicate that companies recognize these potentials, especially small and medium-sized companies still face challenges in selection and implementation of suitable solutions. Thus, the research project GaProSys 4.0 aims at supporting companies with a systematic approach to combine existing structures of Lean Management with potentials of digitalization in development of a new set of methods to enhance production systems. This paper presents the approach of the research project to develop a structured set of methods and provides an example to illustrate the potentials

On the integration of manufacturing strategy:Deconstructing Hoshin Kanri

Purpose The purpose of this paper is to show that Hoshin Kanri has the potential to integrate the operations strategy literature into a coherent structure. Hoshin Kanri’s planning process is typically described as a top-down cascading of goals, starting with the senior management’s goals and moving to the lowest organizational level. The authors argue that this misrepresents a firm’s actual cognitive processes in practice because it implies reasoning from the effects to the cause, and assumes a direct causal relationship between what the customer wants and what is realizable by the system. Design/methodology/approach This study is conceptual, based on abductive reasoning and the literature. Findings The actual strategic thought process executed in an organization consists of three iterative processes: (i) a translation process that derives the desired customer attributes from customer/stakeholder data, (ii) a process of causal inference that predicts realizable customer attributes from a possible system design and (iii) an integrative process of strategic choices whereby (i) and (ii) are aligned. Each element relies on different cognitive processes (logical relation, causal relation and choice). Research limitations/implications By aligning the thought and planning processes, the competing concepts of manufacturing strategy are integrated into a coherent structure. Practical implications Different techniques have to be applied for each of the three elements. As each element relies on different cognitive processes (logical relation, causal relation and choice), the use of unifying tools (e.g. in the form of matrices, as often presented in the literature) is inappropriate. Originality/value This is the first study to focus on the thought processes underpinning manufacturing strategy

Angioscopic Evaluation of Neointimal Coverage of Coronary Stents

Drug-eluting stents (DES) reduce coronary restenosis significantly; however, late stent thrombosis (LST) occurs, which requires long-term antiplatelet therapy. Angioscopic grading of neointimal coverage of coronary stent struts was established, and it was revealed that neointimal formation is incomplete and prevalence of LST is higher in DES when compared to bare-metal stents. It was also observed that the neointima is thicker and LST is less frequent in paclitaxel-eluting and zotarolimus-eluting stents than in sirolimus-eluting stents. Many new stents were devised and they are now under experimental or clinical investigations to overcome the shortcomings of the stents that have been employed clinically. Endothelial cells are highly anti-thrombotic. Neo-endothelial cell damage is considered to be caused by friction between the cells and stent struts due to the thin neointima between them which might act as a cushion. Therefore, development of a DES that causes an appropriate thickness (around 100 μm) of the neointima is a potential option with which to prevent neo-endothelial cell damage and consequent LST while preventing restenosis

Exceptional LAS Requests in Eurotransplant:Analysis of an 8-year Effort to Improve Lung Allocation for Precarious Patients

PURPOSE: Following introduction of the lung allocation score (LAS) in 2011, Eurotransplant member centers can apply for an exceptional LAS (eLAS) if the calculated LAS insufficiently reflects the perceived transplant benefit for a patient, specifically in case of primary pulmonary hypertension group 1 and 4; combined lung+non-renal transplantation; rare diseases; or extracorporeal support. Each eLAS proposal is evaluated by a LAS Review Board, consisting of ≥3 lung transplant experts, which subsequently declines or approves the eLAS request in consensus of ≥3 votes. In case of a lower than accepted score, predefined business rules to assign LAS percentiles are used. METHODS: A retrospective analysis of all eLAS requests in Eurotransplant from December 2011 until September 2019. RESULTS: Overall, 5183 lung transplants (deceased donors) were performed and 420 eLAS requests were made (Germany 52%, Netherlands 18%, Austria 18%, Belgium 13%), of which 116 (28%) were approved. Most eLAS requests concerned group B/Pulmonary vascular disease (44%), followed by group C/Cystic fibrosis or immunodeficiency disorder (28%), then group D/Restrictive lung disease (15%) and finally group A/Obstructive lung disease (11%); whereas 10 patients (2%) were not classified. The proportion of accepted eLAS requests significantly differed between countries (Germany 25%, Netherlands 37%, Austria 20%, Belgium 36%) (p=0.042). eLAS requests decreased in the Netherlands following its LAS introduction in 2014 (2011-2014 mean 13/yr vs. 2015-2019 mean 4.6/yr; p=0.060). However, since 2015 an overall annual increasing number of eLAS requests is seen, with doubling of the eLAS requests in 2018 vs. 2015, but no difference in acceptance rate (2015-2018: 22.4%) (Figure). Acceptance rates were 38% for Group B, 21% for Group C, 20% for Group D and 11% for Group A. CONCLUSION: The observed variations require further investigation to optimize lung allocation for specific patient populations in Eurotransplant

Hypoimmunogenic derivatives of induced pluripotent stem cells evade immune rejection in fully immunocompetent allogeneic recipients

Autologous induced pluripotent stem cells (iPSCs) constitute an unlimited cell source for patient-specific cell-based organ repair strategies. However, their generation and subsequent differentiation into specific cells or tissues entail cell line-specific manufacturing challenges and form a lengthy process that precludes acute treatment modalities. These shortcomings could be overcome by using prefabricated allogeneic cell or tissue products, but the vigorous immune response against histo-incompatible cells has prevented the successful implementation of this approach. Here we show that both mouse and human iPSCs lose their immunogenicity when major histocompatibility complex (MHC) class I and II genes are inactivated and CD47 is over-expressed. These hypoimmunogenic iPSCs retain their pluripotent stem cell potential and differentiation capacity. Endothelial cells, smooth muscle cells, and cardiomyocytes derived from hypoimmunogenic mouse or human iPSCs reliably evade immune rejection in fully MHC-mismatched allogeneic recipients and survive long-term without the use of immunosuppression. These findings suggest that hypoimmunogenic cell grafts can be engineered for universal transplantation

Impact of donor lung quality on post-transplant recipient outcome in the Lung Allocation Score era in Eurotransplant – a historical prospective study

The aim of this study was to investigate whether there is an impact of donation rates on the quality of lungs used for transplantation and whether donor lung quality affects post-transplant outcome in the current Lung Allocation Score era. All consecutive adult LTx performed in Eurotransplant (ET) between January 2012 and December 2016 were included (N = 3053). Donors used for LTx in countries with high donation rate were younger (42% vs. 33% ≤45 years, P < 0.0001), were less often smokers (35% vs. 46%, P < 0.0001), had more often clear chest X-rays (82% vs. 72%, P < 0.0001), had better donor oxygenation ratios (20% vs. 26% with PaO2/FiO2 ≤ 300 mmHg, P < 0.0001), and had better lung donor score values (LDS; 28% vs. 17% with LDS = 6, P < 0.0001) compared with donors used for LTx in countries with low donation rate. Survival rates for the groups LDS = 6 and ≥7 at 5 years were 69.7% and 60.9% (P = 0.007). Lung donor quality significantly impacts on long-term patient survival. Countries with a low donation rate are more oriented to using donor lungs with a lesser quality compared to countries with a high donation rate. Instead of further stretching donor eligibility criteria, the full potential of the donor pool should be realized

Kinase inhibitors for the treatment of inflammatory and autoimmune disorders

Drugs targeting inhibition of kinases for the treatment of inflammation and autoimmune disorders have become a major focus in the pharmaceutical and biotech industry. Multiple kinases from different pathways have been the targets of interest in this endeavor. This review describes some of the recent developments in the search for inhibitors of IKK2, Syk, Lck, and JAK3 kinases. It is anticipated that some of these compounds or newer inhibitors of these kinases will be approved for the treatment of rheumatoid arthritis, psoriasis, organ transplantation, and other autoimmune diseases