SelSus: Towards a reference architecture for diagnostics and predictive maintenance using smart manufacturing devices

© 2015 IEEE. We propose a reference architecture, SelSus (SELf-SUStaining Manufacturing Systems) that aims to enable the provisioning of diagnostic and prognostic capabilities in manufacturing systems that utilize the notions of 'smart' automation devices

A methodology for developing local smart diagnostic models using expert knowledge

© 2015 IEEE. This paper describes an innovative modular component-based modelling approach for diagnostics and condition-monitoring of manufacturing equipment. The approach is based on the use of object-oriented Bayesian networks, which supports a natural decomposition of a large and complex system into a set of less complex components. The methodology consists of six steps supporting the development process: Begin, Design, Implement, Test, Analyse, and Deploy. The process is iterative and the steps should be repeated until a satisfactory model has been achieved. The paper describes the details of the methodology as well as illustrates the use of the component-based modelling approach on a linear axis used in manufacturing. This application demonstrates the power and flexibility of the approach for diagnostics and condition-monitoring and shows a significant potential of the approach for modular component-based modelling in manufacturing and other domains

Impact of smoking and preoperative electrophysiology on outcome after open carpal tunnel release

Background: The aim was to evaluate the influence of smoking and preoperative electrophysiology on the outcome of open carpal tunnel release. Methods: This retrospective observational study evaluated the outcome in 493 patients (531 hands) primary operated for carpal tunnel syndrome. Data were collected from medical records, health evaluations, and QuickDASH questionnaires before surgery and 1 year after. Results: Smokers had a higher QuickDASH score preoperatively as well as postoperatively, but the change in total score did not differ. The odds of having a postoperative QuickDASH score >10 were 2.5 times higher in smoking patients than in non-smoking patients. In 124/493 patients (25%), no clinically significant improvement was seen. Normal and extreme preoperative electrophysiology values were associated with higher postoperative scores. No correlation was found between preoperative QuickDASH scores and preoperative electrophysiology values. Conclusions: Smokers with carpal tunnel syndrome experience more symptoms preoperatively. Smokers have remaining symptoms after surgery. There is no correlation between preoperative QuickDASH scores and preoperative electrophysiology values. Patients with normal or near to normal preoperative electrophysiology results have limited improvement after surgery

Outcome after carpal tunnel release : impact of factors related to metabolic syndrome

Objective: The standard surgical treatment of carpal tunnel syndrome (CTS), with an open carpal tunnel release, is reported to relieve symptoms in most patients. In a retrospective observational study, outcome after open carpal tunnel release was evaluated, focusing on factors related to the metabolic syndrome: diabetes, hypertension, obesity (BMI ≥30) and statin treatment. Methods: Results from 493 out of 962 patients (531/1044 hands) operated for CTS during 18 months that had filled in QuickDASH questionnaires before and 1-year after surgery were included in the study. Results: Patients with diabetes (n = 76) had higher QuickDASH scores pre- (56 [36–77]; i.e. median [interquartile range]) and postoperatively (31 [9–61]) compared to patients without diabetes (48 [32–66]; p 10 (74% vs 61%;

Parameter learning algorithms for continuous model improvement using operational data

In this paper, we consider the application of object-oriented Bayesian networks to failure diagnostics in manufacturing systems and continuous model improvement based on operational data. The analysis is based on an object-oriented Bayesian network developed for failure diagnostics of a one-dimensional pick-and-place industrial robot developed by IEF-Werner GmbH.We consider four learning algorithms (batch Expectation-Maximization (EM), incremental EM, Online EM and fractional updating) for parameter updating in the object-oriented Bayesian network using a real operational dataset. Also, we evaluate the performance of the considered algorithms on a dataset generated from the model to determine which algorithm is best suited for recovering the underlying generating distribution. The object-oriented Bayesian network has been integrated into both the control software of the robot as well as into a software architecture that supports diagnostic and prognostic capabilities of devices in manufacturing systems. We evaluate the time performance of the architecture to determine the feasibility of online learning from operational data using each of the four algorithms. © Springer International Publishing AG 2017

Breakdown of the classical description of a local system

We provide a straightforward demonstration of a fundamental difference between classical and quantum mechanics for a single local system; namely the absence of a joint probability distribution of the position $x$ and momentum $p$. Elaborating on a recently reported criterion by Bednorz and Belzig [Phys. Rev. A {\bf 83}, 52113] we derive a simple criterion that must be fulfilled for any joint probability distribution in classical physics. We demonstrate the violation of this criterion using homodyne measurement of a single photon state, thus proving a straightforward signature of the breakdown of a classical description of the underlying state. Most importantly, the criterion used does not rely on quantum mechanics and can thus be used to demonstrate non-classicality of systems not immediately apparent to exhibit quantum behavior. The criterion is directly applicable any system described by the continuous canonical variables x and p, such as a mechanical or an electrical oscillator and a collective spin of a large ensemble.Comment: 5 pages, 2 figure

Chronic granulomatous disease: the European experience.

CGD is an immunodeficiency caused by deletions or mutations in genes that encode subunits of the leukocyte NADPH oxidase complex. Normally, assembly of the NADPH oxidase complex in phagosomes of certain phagocytic cells leads to a "respiratory burst", essential for the clearance of phagocytosed micro-organisms. CGD patients lack this mechanism, which leads to life-threatening infections and granuloma formation. However, a clear picture of the clinical course of CGD is hampered by its low prevalence (approximately 1:250,000). Therefore, extensive clinical data from 429 European patients were collected and analyzed. Of these patients 351 were males and 78 were females. X-linked (XL) CGD (gp91(phox) deficient) accounted for 67% of the cases, autosomal recessive (AR) inheritance for 33%. AR-CGD was diagnosed later in life, and the mean survival time was significantly better in AR patients (49.6 years) than in XL CGD (37.8 years), suggesting a milder disease course in AR patients. The disease manifested itself most frequently in the lungs (66% of patients), skin (53%), lymph nodes (50%), gastrointestinal tract (48%) and liver (32%). The most frequently cultured micro-organisms per episode were Staphylococcus aureus (30%), Aspergillus spp. (26%), and Salmonella spp. (16%). Surprisingly, Pseudomonas spp. (2%) and Burkholderia cepacia (<1%) were found only sporadically. Lesions induced by inoculation with BCG occurred in 8% of the patients. Only 71% of the patients received antibiotic maintenance therapy, and 53% antifungal prophylaxis. 33% were treated with gamma-interferon. 24 patients (6%) had received a stem cell transplantation. The most prominent reason of death was pneumonia and pulmonary abscess (18/84 cases), septicemia (16/84) and brain abscess (4/84). These data provide further insight in the clinical course of CGD in Europe and hopefully can help to increase awareness and optimize the treatment of these patients