Tire inspection spreading machine

The aim of the project was to design in Solidworks and improve an existing Tire inspection machine. The project was developed in Gislotica - Mechanical Solutions, guided by ing. Rui Manuel Fazenda Silva who is a professor in ISEP. The designed device relates to the inspection of automobile tires for holes and weak places caused by punctures and usage. Such inspection includes careful examination of the inside surface of the tire which is difficult because of its cylindrical shape, stiff and resistant nature of the material out of which the tire is made. The whole idea is to provide a machine by which the walls of the tire may be spread and hold apart, presenting the inner surface for the worker to control. The device must also perform rotational and vertical movement of the tire. It is meant to provide inspection in hich there is no need for the controller to use force. It makes his work easier and more efficient.

Scheduling of track inspection and maintenance activities in railroad networks

The U.S. railroad companies spend billions of dollars every year on railroad track maintenance in order to ensure safety and operational efficiency of their railroad networks. Besides maintenance costs, other costs such as train accident costs, train and shipment delay costs and rolling stock maintenance costs are also closely related to track maintenance activities. Optimizing the track maintenance process on the extensive railroad networks is a very complex problem with major cost implications. Currently, the decision making process for track maintenance planning is largely manual and primarily relies on the knowledge and judgment of experts. There is considerable potential to improve the process by using operations research techniques to develop solutions to the optimization problems on track maintenance. In this dissertation study, we propose a range of mathematical models and solution algorithms for three network-level scheduling problems on track maintenance: track inspection scheduling problem (TISP), production team scheduling problem (PTSP) and job-to-project clustering problem (JTPCP). TISP involves a set of inspection teams which travel over the railroad network to identify track defects. It is a large-scale routing and scheduling problem where thousands of tasks are to be scheduled subject to many difficult side constraints such as periodicity constraints and discrete working time constraints. A vehicle routing problem formulation was proposed for TISP, and a customized heuristic algorithm was developed to solve the model. The algorithm iteratively applies a constructive heuristic and a local search algorithm in an incremental scheduling horizon framework. The proposed model and algorithm have been adopted by a Class I railroad in its decision making process. Real-world case studies show the proposed approach outperforms the manual approach in short-term scheduling and can be used to conduct long-term what-if analyses to yield managerial insights. PTSP schedules capital track maintenance projects, which are the largest track maintenance activities and account for the majority of railroad capital spending. A time-space network model was proposed to formulate PTSP. More than ten types of side constraints were considered in the model, including very complex constraints such as mutual exclusion constraints and consecution constraints. A multiple neighborhood search algorithm, including a decomposition and restriction search and a block-interchange search, was developed to solve the model. Various performance enhancement techniques, such as data reduction, augmented cost function and subproblem prioritization, were developed to improve the algorithm. The proposed approach has been adopted by a Class I railroad for two years. Our numerical results show the model solutions are able to satisfy all hard constraints and most soft constraints. Compared with the existing manual procedure, the proposed approach is able to bring significant cost savings and operational efficiency improvement. JTPCP is an intermediate problem between TISP and PTSP. It focuses on clustering thousands of capital track maintenance jobs (based on the defects identified in track inspection) into projects so that the projects can be scheduled in PTSP. A vehicle routing problem based model and a multiple-step heuristic algorithm were developed to solve this problem. Various side constraints such as mutual exclusion constraints and rounding constraints were considered. The proposed approach has been applied in practice and has shown good performance in both solution quality and efficiency.

A comprehensive study of multiplicative attribute graph model

Graphs are powerful tools to describe social, technological and biological networks, with nodes representing agents (people, websites, gene, etc.) and edges (or links) representing relations (or interactions) between agents. Examples of real-world networks include social networks, the World Wide Web, collaboration networks, protein networks, etc. Researchers often model these networks as random graphs. In this dissertation, we study a recently introduced social network model, named the Multiplicative Attribute Graph model (MAG), which takes into account the randomness of nodal attributes in the process of link formation (i.e., the probability of a link existing between two nodes depends on their attributes). Kim and Lesckovec, who defined the model, have claimed that this model exhibit some of the properties a real world social network is expected to have. Focusing on a homogeneous version of this model, we investigate the existence of zero-one laws for graph properties, e.g., the absence of isolated nodes, graph connectivity and the emergence of triangles. We obtain conditions on the parameters of the model, so that these properties occur with high or vanishingly probability as the number of nodes becomes unboundedly large. In that regime, we also investigate the property of triadic closure and the nodal degree distribution.

Early investigation towards defining and measuring sustainability as a quality attribute in software systems

Sustainability in software system is still a new practice that most software developers and companies are trying to incorporate into their software development lifecycle and has been largely discussed in academia. Sustainability is a complex concept viewed from economic, environment and social dimensions with several definitions proposed making sometimes the concept of sustainability very fuzzy and difficult to apply and assess in software systems. This has hindered the adoption of sustainability in the software industry. A little research explores sustainability as a quality property of software products and services to answer questions such as; How to quantify sustainability as a quality construct in the same way as other quality attributes such as security, usability and reliability? How can it be applied to software systems? What are the measures and measurement scale of sustainability? The Goal of this research is to investigate the definitions, perceptions and measurement of sustainability from the quality perspective. Grounded in the general theory of software measurement, the aim is to develop a method that decomposes sustainability in factors, criteria and metrics. The Result is a method to quantify and access sustainability of software systems while incorporating management and users concern. Conclusion: The method will empower the ability of companies to easily adopt sustainability while facilitating its integration to the software development process and tools. It will also help companies to measure sustainability of their software products from economic, environmental, social, individual and technological dimension.

Removing redundancy for attribute implications in data with grades

Reasoning with if-then rules –in particular, with those taking from of implications between conjunctions of attributes– is crucial in many disciplines ranging from theoretical computer science to applications. One of the most important problems regarding the rules is to remove redundancies in order to obtain equivalent implicational sets with lower size.

ARL1 of the Attribute c Control Chart with Estimated Parameter

International audience

CAISL: Simplification Logic for Conditional Attribute Implications

In this work, we present a sound and complete axiomatic system for conditional attribute implications (CAIs) in Triadic Concept Analysis (TCA). Our approach is strongly based on the Simplification paradigm which offers a more suitable way for automated reasoning than the one based on Armstrong’s Axioms. We also present an automated method to prove the derivability of a CAI from a set of CAI s.

Computer vision in aseptic pharmaceutical manufacturing: a deep learning-based approach to vial inspection and pack formation during a lyophilizer loading cycle

Vision systems are powerful tools playing an increasingly important role in modern industry, to detect errors and maintain product standards. With the enlarged availability of affordable industrial cameras, computer vision algorithms have been increasingly applied in industrial manufacturing processes monitoring. Until a few years ago, industrial computer vision applications relied only on ad-hoc algorithms designed for the specific object and acquisition setup being monitored, with a strong focus on co-designing the acquisition and processing pipeline. Deep learning has overcome these limits providing greater flexibility and faster re-configuration. In this work, the process to be inspected consists in vials’ pack formation entering a freeze-dryer, which is a common scenario in pharmaceutical active ingredient packaging lines. To ensure that the machine produces proper packs, a vision system is installed at the entrance of the freeze-dryer to detect eventual anomalies with execution times compatible with the production specifications. Other constraints come from sterility and safety standards required in pharmaceutical manufacturing. This work presents an overview about the production line, with particular focus on the vision system designed, and about all trials conducted to obtain the final performance. Transfer learning, alleviating the requirement for a large number of training data, combined with data augmentation methods, consisting in the generation of synthetic images, were used to effectively increase the performances while reducing the cost of data acquisition and annotation. The proposed vision algorithm is composed by two main subtasks, designed respectively to vials counting and discrepancy detection. The first one was trained on more than 23k vials (about 300 images) and tested on 5k more (about 75 images), whereas 60 training images and 52 testing images were used for the second one.

[lean Production And Psychosocial Risks: The Case Of A Multinational Merger In A Metallurgical Company In Brazil].

This study focused on the method known as lean production as a work-related psychosocial risk factor in a Brazilian multinational auto parts company after its merger with other multinational companies. The authors conducted a qualitative analysis of two time points: the first using on-site observation and key interviews with managers and workers during implementation of lean production in 1996; the second, 16 years later, comparing data from a document search in labor inspection records from the Ministry of Labor and Employment and legal proceedings initiated by the Office of the Public Prosecutor for Labor Affairs. The merger led to layoffs, replacements, and an increase in the workday. A class action suit was filed on grounds of aggravated working conditions. The new production model led to psychosocial risks that increased the need for workers' health precautions when changes in the production process introduced new and increased risks of physical and mental illnesses.

Measurement Of The Hydrodynamic Radius Of Quantum Dots By Fluorescence Correlation Spectroscopy Excluding Blinking.

One of the most important properties of quantum dots (QDs) is their size. Their size will determine optical properties and in a colloidal medium their range of interaction. The most common techniques used to measure QD size are transmission electron microscopy (TEM) and X-ray diffraction. However, these techniques demand the sample to be dried and under a vacuum. This way any hydrodynamic information is excluded and the preparation process may alter even the size of the QDs. Fluorescence correlation spectroscopy (FCS) is an optical technique with single molecule sensitivity capable of extracting the hydrodynamic radius (HR) of the QDs. The main drawback of FCS is the blinking phenomenon that alters the correlation function implicating in a QD apparent size smaller than it really is. In this work, we developed a method to exclude blinking of the FCS and measured the HR of colloidal QDs. We compared our results with TEM images, and the HR obtained by FCS is higher than the radius measured by TEM. We attribute this difference to the cap layer of the QD that cannot be seen in the TEM images.

Avaliação do teor e da estabilidade de vitaminas do complexo B e vitamina C em bebidas isotônicas e energéticas

Vitamin C stability and concentration was evaluated in isotonic beverages and B group vitamins (B1, B2, B3, B5 and B6) in power beverages. The amount of vitamins was found to be above of that declared on the labels, even after the shelf life had been exceeded. A small decrease in the amount of B group vitamins was observed during the shelf life of the products. In the case of vitamin C this decrease was slightly higher. The present research shows the need of increased quality control and inspection.

Mapeamento de semeaduras de soja (Glycine max (L.)Merr.) mediante dados MODIS/Terra E TM/Landsat 5: um comparativo

The objective of this work was to compare the soybean crop mapping in the western of Parana State by MODIS/Terra and TM/Landsat 5 images. Firstly, it was generated a soybean crop mask using six TM images covering the crop season, which was used as a reference. The images were submitted to Parallelepiped and Maximum Likelihood digital classification algorithms, followed by visual inspection. Four MODIS images, covering the vegetative peak, were classified using the Parallelepiped method. The quality assessment of MODIS and TM classification was carried out through an Error Matrix, considering 100 sample points between soybean or not soybean, randomly allocated in each of the eight municipalities within the study area. The results showed that both the Overall Classification (OC) and the Kappa Index (KI) have produced values ranging from 0.55 to 0.80, considered good to very good performances, either in TM or MODIS images. When OC and KI, from both sensors were compared, it wasn't found no statistical difference between them. The soybean mapping, using MODIS, has produced 70% of reliance in terms of users. The main conclusion is that the mapping of soybean by MODIS is feasible, with the advantage to have better temporal resolution than Landsat, and to be available on the internet, free of charge.

CARACTERÍSTICAS DE QUALIDADE DO CONTRAFILÉ (m. L. dorsi) DE TOUROS JOVENS DA RAÇA NELORE

Quality traits of boneless rib cut (L. dorsi muscle) from Nelore young bulls. To study the meat quality traits of Nelore breed young bulls, and the effect of age (690-780 days) on them, 113 animals were slaughtered after 109 days of intensive feeding with 20% concentrate and 80% roughage. All the carcasses were graded at the slaughter floor by the Federal Inspection and chilled for 24 hours (Tinitial=5°C, Tfinal=2°C). Fifty one half carcasses (right side), type B - B R A S I L `s grading system - from animals of 23 to 26 months were boned and separated into commercial cuts. Two steaks (2.5cm thick) were removed from each boneless rib cut (m. L. dorsi), vacuum packaged and aged for 7 days (0-2°C). The pH varied from 5.44 to 5.83 and only two samples had pH ³ 5.70. The L* (brightness) average value was 34.85. The water and fat content were 75.65% and 1.71%, respectively. The average WB shear force was 6.70kg, and it was not affected by age (690-734 days), but presented a trend (t test, p=0.22) for increasing values between 735 and 780 days. Animal age did not affect other quality traits (t test, p>0.20). It was concluded that the rib cut from Nelore young bulls may not have a good acceptability in exigent markets, and that carcasses graded B, presumed to be the best grade, do not necessarily present the best meat quality characteristics.