Change-point visualization and variation analysis in a simple production line: a process mining application in manufacturing

In production systems, digital twins must be always aligned with the real system to guarantee an effective decision making process in a continuously changing environment. To allow the alignment, digital models can be updated with process mining techniques through data collected by sensors. This paper addresses the issue of detecting changes in the production system by analyzing data collected from sensors. Using raw collected data, a procedure is proposed to compute and plot relevant system measures that could help change identification. Simulation is used to test the effectiveness of the procedure in a realistic medium size production line

Variability propagation in manufacturing systems: the impact of the processing time distribution

In manufacturing and service systems, the negative effects of variability propagation are usually addressed through approximation models and other tools, such as simulation and optimization algorithms. This paper investigates the conditions in which these approaches are ineffective, and considering only the mean and variance of the processing time distribution is misleading. A scenario analysis deepens the impacts of considering the entire processing time distribution (beyond its mean and variance) on the inter-departure times in balanced and unpaced lines modeled through Discrete Event Simulation. The results correlate the impacts on variability propagation of approximating the processing time distribution with system characteristics such as utilization levels, line sizes, and inter-arrival and processing time variability. Production planning approaches can benefit from these results to reduce variability propagation, particularly in flexible and reconfigurable manufacturing systems, largely adopted in Industry 4.0, that can highly influence processing time distributions by varying product mix and line configuration

Circular economy strategies at the manufacturing system scheduling level: the impacts on Makespan

The use of end-of-life and end-of-use products to recover parts and raw materials can mitigate the severity of the increasing price of raw materials, the disruption of global supply chains for critical raw materials (e.g., chips and rare earth elements), and reduce the environmental impacts. Furthermore, circular economy strategies can improve scheduling by shortening the completion times of the components. This paper investigates the effects of implementing circular economy strategies (repair, reuse, and re-manufacturing) at the scheduling level in a manufacturing system involving disassembly, re-manufacturing, and assembly operations. A set of eight priority rules modify the job priority and the strategy implementation. The results show that including circular economy strategies through disassembly can reduce the makespan, but scheduling is pivotal to managing the frequent changes in the quality of end-of-life products and their volumes and the current production order mix

A Discrete Event Simulation Based Approach for Digital Twin Implementation

Nowadays, manufacturing companies need to improve their production monitoring and prediction to be more flexible and re-configurable. To do so, the digitization of the manufacturing environment is a very critical issue. This paper proposes an approach to develop digital twins in this environment. Digital twins are virtual systems, real time connected with their physical counterpart, which replicate exactly their behaviour. Discrete event simulation models, connected in real-time with their real system counterparts, are developed in this work. Two industrial use cases are analysed, to show the benefits that this promising technology can bring to the manufacturing industry

Serious Adverse Events Associated with Anti-Tumor Necrosis Factor Alpha Agents in Pediatric-Onset Inflammatory Bowel Disease and Juvenile Idiopathic Arthritis in A Real-Life Setting

7noOBJECTIVES: Anti-tumor necrosis factor alpha (anti-TNF-α) agents are generally well tolerated, yet they can be associated with serious adverse events (SAEs) in a minority of patients. We examined the incidence of SAEs in a pediatric referral center for chronic rheumatologic and gastroenterological inflammatory disorders. METHODS: Retrospective analysis of SAEs occurring during treatment with anti-TNF-α agents in patients with juvenile idiopathic arthritis (JIA) (n = 78) or pediatric-onset inflammatory bowel disease (IBD) (n = 105) seen at the Institute for Maternal and Child Health IRCCS "Burlo Garofolo" in Trieste, Italy, between June 2001 and February 2016. Only SAEs grade 3-5 according to the Common Terminology Criteria for Adverse Events version 4.03 and/or requiring definitive therapy discontinuation were reported. RESULTS: Total anti-TNF-α exposure was 390.5 patient-years (PYs). The overall incidence rate of SAEs for etanercept was 4.14/100 PYs. Four patients developed uveitis, two had anxiety disorders, one had a serious zoster infection, and one developed TNF-α antagonist-induced lupus-like syndrome (TAILS). The overall incidence rate of SAEs for infliximab was 22.49/100 PYs. The most common SAEs were anaphylactoid reactions (n = 18), followed by infectious events (n = 9) and TAILS (n = 3). The overall incidence rate of SAEs for adalimumab was 4.71/100 PYs (two infectious SAEs). No malignancies or deaths were observed. A greater incidence rate of infectious SAEs was observed in IBD patients receiving infliximab compared to JIA patients receiving etanercept (8.11 vs 0.52 per 100 PYs). CONCLUSIONS: Anti-TNF-α therapy was generally well tolerated. SAEs leading to anti-TNF-α discontinuation were rare and non-fatal. Infliximab was associated with the highest incidence of SAEs. Infectious SAEs were more frequently observed in IBD patients treated with infliximab than in JIA patients receiving etanercept.partially_openembargoed_20181213Pastore, Serena; Naviglio, Samuele; Canuto, Arianna; Lepore, Loredana; Martelossi, Stefano; Ventura, Alessandro; Taddio, AndreaPastore, Serena; Naviglio, Samuele; Canuto, Arianna; Lepore, Loredana; Martelossi, Stefano; Ventura, Alessandro; Taddio, Andre

Oleanolic acid: A promising antidiabetic metabolite detected in Aglianico grape pomace

Grape pomace, a bulky component of winery waste, is a source of healthy compounds. So far, scientific research has mainly focused on its polyphenol content, but given the impressive number of bioactivities shown by grape pomace, it is not unlikely that, besides polyphenols, additional metabolites, so far undetected, may be involved. In order to verify such hypothesis, an in-depth chemical analysis of Aglianico (Vitis vinifera) grape pomace was conducted by NMR and LC-MS/MS. In addition to a number of polyphenols, a remarkable concentration of oleanolic acid (0.45 mg/g - fresh weight) was determined in the analyzed material. Oleanolic acid is a natural triterpenoid showing many bioactivities including antitumor, anti-inflammatory, antibiotic and antiviral properties. Also, it was proven a potential antidiabetic molecule in Type1 Diabetes rats. Hence, its influence on the mitochondrial and glucose uptake activities of C2C12 myoblast was here assessed, thus supporting oleanolic acid as a promising antidiabetic metabolite

Trajectory of Spike-Specific B Cells Elicited by Two Doses of BNT162b2 mRNA Vaccine

: The mRNA vaccines for SARS-CoV-2 have demonstrated efficacy and immunogenicity in the real-world setting. However, most of the research on vaccine immunogenicity has been centered on characterizing the antibody response, with limited exploration into the persistence of spike-specific memory B cells. Here we monitored the durability of the memory B cell response up to 9 months post-vaccination, and characterized the trajectory of spike-specific B cell phenotypes in healthy individuals who received two doses of the BNT162b2 vaccine. To profile the spike-specific B cell response, we applied the tSNE and Cytotree automated approaches. Spike-specific IgA+ and IgG+ plasmablasts and IgA+ activated cells were observed 7 days after the second dose and disappeared 3 months later, while subsets of spike-specific IgG+ resting memory B cells became predominant 9 months after vaccination, and they were capable of differentiating into spike-specific IgG secreting cells when restimulated in vitro. Other subsets of spike-specific B cells, such as IgM+ or unswitched IgM+IgD+ or IgG+ double negative/atypical cells, were also elicited by the BNT162b2 vaccine and persisted up to month 9. The analysis of circulating spike-specific IgG, IgA, and IgM was in line with the plasmablasts observed. The longitudinal analysis of the antigen-specific B cell response elicited by mRNA-based vaccines provides valuable insights into our understanding of the immunogenicity of this novel vaccine platform destined for future widespread use, and it can help in guiding future decisions and vaccination schedules

Radiomics and Magnetic Resonance Imaging of Rectal Cancer: From Engineering to Clinical Practice

While cross-sectional imaging has seen continuous progress and plays an undiscussedpivotal role in the diagnostic management and treatment planning of patients with rectal cancer, alargely unmet need remains for improved staging accuracy, assessment of treatment response andprediction of individual patient outcome. Moreover, the increasing availability of target therapies hascalled for developing reliable diagnostic tools for identifying potential responders and optimizingoverall treatment strategy on a personalized basis. Radiomics has emerged as a promising, still fullyevolving research topic, which could harness the power of modern computer technology to generatequantitative information from imaging datasets based on advanced data-driven biomathematicalmodels, potentially providing an added value to conventional imaging for improved patient manage-ment. The present study aimed to illustrate the contribution that current radiomics methods appliedto magnetic resonance imaging can offer to managing patients with rectal cancer