Virtual Learning Factory on VR-Supported Factory Planning

Part 13: Virtual Reality and Simulation

Oppimistehtaan toimintamallin kehittäminen

Educaworks Oy on toiminut viisi vuotta oppimistehtaana, jonka omistajia ovat olleet yritykset ja oppilaitokset. Yrityksen pääasiallisia työntekijöitä ovat tähän mennessä olleet ammattiopiston työssäoppijat ja parina viimeisenä vuotena on yrityksellä ollut palkkalistoillaan omia työntekijöitä. Tässä työssä luotiin vaihtoehtoja Educaworks Oy:n tulevalle toiminnalle lähtien siitä, että tämä nykyinen toimintamalli on tullut tiensä päähän ja tarvitaan uusi malli toiminnan jatkamiselle.Työssä haettiin hyviä käytäntöjä Suomesta benchmarkingin avulla. Näiden mallienvahvuuksia hyödyntämällä pystyttiin kehittämään vaihtoehto Educaworks Oy:n tulevalle toiminnalle. Tämä malli, oppimistehdas osana osaamiskeskittymää, valittiin toteutettavaksi kolmesta eri vaihtoehdosta, joista kaksi muuta olivat oppimistehdas yrityksenä ja oppimistehdas osana koulutusorganisaatiota. Valitussa vaihtoehdossa hyödynnetään Savonia-ammattikorkeakoulun suunnitteilla olevaa EducaTech Center-hanketta, jossa on tarkoitus luoda Iisalmeen teknologiateollisuuden osaamiskeskittymä seuraavan EU-kauden 2007-2013 aikana. Valitussa mallissa Educaworks Oy hyödyntää tulevassa toiminnassaan tämän osaamiskeskittymän uutta kone- ja laitekantaa sekä tekee yhteistyötä keskittymän tutkimus- ja tuotekehityshenkilökunnan kanssa. Yritykset pääsevät parhaiten osallisiksi Educa Tech Center osaamiskeskittymän tuottamista palveluista hankkimalla Educaworks Oy:n osakkeita ja pääsemällä täten keskittymän ytimeen sen tuotannollisen toimijan, Educaworks Oy:n, avulla. Educaworks Oy toimii tässä keskittymässä komponenttitoimittajan roolissa ollen malli komponenttitoimittajasta muillealueella oleville vastaaville verkostoissa toimiville yrityksille. Educaworks Oy:n toiminnan toisena periaatteena tulee olemaan työssäoppiminen. Työssäoppiminen on tänä päivänä osa ammatillista koulutusta ja sen merkityskorostuu yhä enemmän, koska oppilaat tulevat opiskelemaan tänä päivänä monesti lähtökohdista, joissa heillä ei ole ollut mahdollisuutta harjoittaa käytännön taitojaan ennen ammatillisten opiskelujen aloittamista. Työpaikoilla ei ole vielä kovin hyvää valmiutta toteuttaa sitä opetushallituksen tavoitetta, että oppilaatoppisivat työssäoppimisjaksoilla uusia asioita ohjatusti. Työpaikoilta puuttuu työssäoppimisen ohjaajat ja oppilaiden tekemät harjoitteet ovat liian monta kertaa ammatillisesti kovin vaatimattomia jäysteenpoisto- tai kappaleenvaihtotöitä koneistuksesta puhuttaessa. Tässä työssä luodaan mallia oppilaiden ohjatulle työssäoppimiselle tehtyjen tieteellisten tutkimusten pohjalta. Tavoitteena on, että Educaworks Oy:ssä pystyttäisiin jatkossa kouluttamaan myös muiden alueen teknologiateollisuuden yritysten työntekijöitä toimimaan työssäoppimisen ohjaajina.

The HOSHIN KANRI TREE. Cross-Plant Lean Shopfloor Management

Shopfloor Management (SM) empowerment methodologies have traditionally focused on two aspects: goal achievement following rigid structures, such as SQDCME, or evolutional aspects of empowerment factors away from strategic goal achievement. Furthermore, SM Methodologies have been organized almost solely around the hierarchical structure of the organization, failing systematically to cope with the challenges that Industry 4.0 is facing. The latter include the growing complexity of value-stream networks, sustainable empowerment of the workforce (Learning Factory), an autonomous and intelligent process management (Smart Factory), the need to cope with the increasing complexity of value-stream networks (VSN) and the leadership paradigm shift to strategic alignment. This paper presents a novel Lean SM Method (LSM) called ?HOSHIN KANRI Tree? (HKT), which is based on standardization of the communication patterns among process owners (POs) by PDCA. The standardization of communication patterns by HKT technology should bring enormous benefits in value stream (VS) performance, speed of standardization and learning rates to the Industry 4.0 generation of organizations. These potential advantages of HKT are being tested at present in worldwide research.

Yritysvalmennuksen onnistumiset ja kehittämiskohteet Case: Start-up & Spin-off Factory -projekti

Tässä työssä tarkastellaan Start-up & Spin-off Factory -projektissa, pääsääntöisesti Kymenlaaksossa toimiville, yrittäjille suunnattua ja toteutettua yritysvalmennusohjelmaa. Työssä selvitetään ja käsitellään Start-up & Spin-off -projektin yritysvalmennuksen onnistumisia ja kehittämiskohteita sähköisen kyselyn sekä teemahaastatteluiden pohjalta. Start-up & Spin-off Factory -projektissa tuettiin innovatiivisten yritysten (21 yritystä) kasvua kiihdytysohjelmalla, jossa kokeneet sarjayrittäjät valmensivat uutta yritystä perustavia tai jo yritystoiminnan aloittaneita yrittäjiä, joiden tuotteille/palveluille haluttiin saada kasvua. Projektin tavoitteena oli edistää erityisesti kiihdytettävien yritysten nopeaa kansainvälistymistä auttamalla yrittäjiä pilottien, asiakkaiden, partnerien ja rahoituksen hankinnassa. Valmennettavat kokivat saaneensa lisäarvoa valmennuksesta omaksumalla uusia näkökulmia. He kokivat koulutuksen tuoneen yrityksen toimintaan lisää nöyrää asennetta ja lujaa uskoa tulevaisuuteen. Vertaistuen osuutta sekä verkostojen lisääntymisen mukana tullutta uusien kontaktien määrää pidettiin myönteisenä asiana. Vastausten perusteella valmennus selkeytti valmennettavien ymmärrystä liiketoiminnan kehittämisestä. Hissipuheen teko ja harjoittelu koettiin tärkeäksi ja jännittäväksi. Valmennus vahvisti luottamusta omaan tuotteeseen ja palveluun. Valmennuksen painottuminen ICT-alan firmoihin merkitsi valmennuksessa sitä, että teoriat ja esimerkit tulivat useasti tältä alalta. Toimialojen eroavaisuus tulisi huomioida valmennuksessa opetussisältöjen ja esimerkkien osalta. Kyselyn ja haastatteluiden mukaan valmentajien asiantuntemukseen oltiin tyytyväisiä. Lisäksi onnistuneena osa-alueena koettiin valmennuksen käytännön järjestelyjä. Kehitettävää puolestaan oli opetusmateriaalien, opetusmenetelmien ja koulutuksen keston suhteen. Kysyttäessä valmennuksen hyvistä ja huonoista puolista olivat vastaajat sitä mieltä, että valmennuksessa oli hyvä ilmapiiri ja valmennus oli käytännönläheistä. Pienryhmävalmennusta pidettiin hyvänä asiana, samoin kuin henkilökohtaistamista.

Predicting the concentration of residual methanol in industrial formalin using machine learning

In this thesis, a machine learning approach was used to develop a predictive model for residual methanol concentration in industrial formalin produced at the Akzo Nobel factory in Kristinehamn, Sweden. The MATLABTM computational environment supplemented with the Statistics and Machine LearningTM toolbox from the MathWorks were used to test various machine learning algorithms on the formalin production data from Akzo Nobel. As a result, the Gaussian Process Regression algorithm was found to provide the best results and was used to create the predictive model. The model was compiled to a stand-alone application with a graphical user interface using the MATLAB CompilerTM.

A deep learning model for controlling the galvanizing process in a production line

In the industry of steelmaking, the process of galvanizing is a treatment which is applied to protect the steel from corrosion. The air knife effect (AKE) occurs when nozzles emit a steam of air on the surfaces of a steel strip to remove excess zinc from it. In our work we formalized the problem to control the AKE and we implemented, with the R&D dept.of MarcegagliaSPA, a DL model able to drive the AKE. We call it controller. It takes as input the tuple : a tuple of the physical conditions of the process line (t,h,s) with the target value of the zinc coating (c); and generates the expected tuple of (pres and dist) to drive the mechanical nozzles towards the (c). According to the requirements we designed the structure of the network. We collected and explored the data set of the historical data of the smart factory. Finally, we designed the loss function as sum of three components: the minimization between the coating addressed by the network and the target value we want to reach; and two weighted minimization components for both pressure and distance. In our solution we construct a second module, named coating net, to predict the coating of zinc resulting from the AKE when the conditions are applied to the prod. line. Its structure is made by a linear and a deep nonlinear “residual” component learned by empirical observations. The predictions made by the coating nets are used as ground truth in the loss function of the controller. By tuning the weights of the different components of the loss function, it is possible to train models with slightly different optimization purposes. In the tests we compared the regularization of different strategies with the standard one in condition of optimal estimation for both; the overall accuracy is ± 3 g/m^2 dal target for all of them. Lastly, we analyze how the controller modeled the current solutions with the new logic: the sub-optimal values of pres and dist can be optimize of 50% and 20%.

Ecological Literacy And Beyond: Problem-based Learning For Future Professionals.

Ecological science contributes to solving a broad range of environmental problems. However, lack of ecological literacy in practice often limits application of this knowledge. In this paper, we highlight a critical but often overlooked demand on ecological literacy: to enable professionals of various careers to apply scientific knowledge when faced with environmental problems. Current university courses on ecology often fail to persuade students that ecological science provides important tools for environmental problem solving. We propose problem-based learning to improve the understanding of ecological science and its usefulness for real-world environmental issues that professionals in careers as diverse as engineering, public health, architecture, social sciences, or management will address. Courses should set clear learning objectives for cognitive skills they expect students to acquire. Thus, professionals in different fields will be enabled to improve environmental decision-making processes and to participate effectively in multidisciplinary work groups charged with tackling environmental issues.

Flicker perimetry in healthy subjects: influence of age and gender, learning effect and short-term fluctuation

PURPOSE: To determine the mean critical fusion frequency and the short-term fluctuation, to analyze the influence of age, gender, and the learning effect in healthy subjects undergoing flicker perimetry. METHODS: Study 1 - 95 healthy subjects underwent flicker perimetry once in one eye. Mean critical fusion frequency values were compared between genders, and the influence of age was evaluated using linear regression analysis. Study 2 - 20 healthy subjects underwent flicker perimetry 5 times in one eye. The first 3 sessions were separated by an interval of 1 to 30 days, whereas the last 3 sessions were performed within the same day. The first 3 sessions were used to investigate the presence of a learning effect, whereas the last 3 tests were used to calculate short-term fluctuation. RESULTS: Study 1 - Linear regression analysis demonstrated that mean global, foveal, central, and critical fusion frequency per quadrant significantly decreased with age (p<0.05).There were no statistically significant differences in mean critical fusion frequency values between males and females (p>0.05), with the exception of the central area and inferonasal quadrant (p=0.049 and p=0.011, respectively), where the values were lower in females. Study 2 - Mean global (p=0.014), central (p=0.008), and peripheral (p=0.03) critical fusion frequency were significantly lower in the first session compared to the second and third sessions. The mean global short-term fluctuation was 5.06±1.13 Hz, the mean interindividual and intraindividual variabilities were 11.2±2.8% and 6.4±1.5%, respectively. CONCLUSION: This study suggests that, in healthy subjects, critical fusion frequency decreases with age, that flicker perimetry is associated with a learning effect, and that a moderately high short-term fluctuation is expected.

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

Pedagogia do esporte : pressupostos para uma teoria da avaliação da aprendizagem = Sport pedagogy: presuppositions for a learning assessment theory

Universidade Estadual de Campinas . Faculdade de Educação Física

Learning processes and the neural analysis of conditioning

Classical and operant conditioning principles, such as the behavioral discrepancy-derived assumption that reinforcement always selects antecedent stimulus and response relations, have been studied at the neural level, mainly by observing the strengthening of neuronal responses or synaptic connections. A review of the literature on the neural basis of behavior provided extensive scientific data that indicate a synthesis between the two conditioning processes based mainly on stimulus control in learning tasks. The resulting analysis revealed the following aspects. Dopamine acts as a behavioral discrepancy signal in the midbrain pathway of positive reinforcement, leading toward the nucleus accumbens. Dopamine modulates both types of conditioning in the Aplysia mollusk and in mammals. In vivo and in vitro mollusk preparations show convergence of both types of conditioning in the same motor neuron. Frontal cortical neurons are involved in behavioral discrimination in reversal and extinction procedures, and these neurons preferentially deliver glutamate through conditioned stimulus or discriminative stimulus pathways. Discriminative neural responses can reliably precede operant movements and can also be common to stimuli that share complex symbolic relations. The present article discusses convergent and divergent points between conditioning paradigms at the neural level of analysis to advance our knowledge on reinforcement.

The Process of Simulation Authoring/Creation by Chemistry Teachers: A Service Learning Experience

Two case studies are presented to describe the process of public school teachers authoring and creating chemistry simulations. They are part of the Virtual Didactic Laboratory for Chemistry, a project developed by the School of the Future of the University of Sao Paulo. the documental analysis of the material produced by two groups of teachers reflects different selection process for both themes and problem-situations when creating simulations. The study demonstrates the potential for chemistry learning with an approach that takes students' everyday lives into account and is based on collaborative work among teachers and researches. Also, from the teachers' perspectives, the possibilities of interaction that a simulation offers for classroom activities are considered.

Students' collective knowledge construction in the virtual learning environment ""ToLigado - your school interactive newspaper""

Introduction. The ToLigado Project - Your School Interactive Newspaper is an interactive virtual learning environment conceived, developed, implemented and supported by researchers at the School of the Future Research Laboratory of the University of Sao Paulo, Brazil. Method. This virtual learning environment aims to motivate trans-disciplinary research among public school students and teachers in 2,931 schools equipped with Internet-access computer rooms. Within this virtual community, students produce collective multimedia research documents that are immediately published in the portal. The project also aims to increase students' autonomy for research, collaborative work and Web authorship. Main sections of the portal are presented and described. Results. Partial results of the first two years' implementation are presented and indicate a strong motivation among students to produce knowledge despite the fragile hardware and software infrastructure at the time. Discussion. In this new environment, students should be seen as 'knowledge architects' and teachers as facilitators, or 'curiosity managers'. The ToLigado portal may constitute a repository for future studies regarding student attitudes in virtual learning environments, students' behaviour as 'authors', Web authorship involving collective knowledge production, teachers' behaviour as facilitators, and virtual learning environments as digital repositories of students' knowledge construction and social capital in virtual learning communities.

Cooperation, interaction and learning in local production systems: Evidence in Brazilian firms

In a local production system (LPS), besides external economies, the interaction, cooperation, and learning are indicated by the literature as complementary ways of enhancing the LPS's competitiveness and gains. In Brazil, the greater part of LPSs, mostly composed by small enterprises, displays incipient relationships and low levels of interaction and cooperation among their actors. The size of the participating enterprises itself for specificities that engender organizational constraints, which, in turn, can have a considerable impact on their relationships and learning dynamics. For that reason, it is the purpose of this article to present an analysis of interaction, cooperation, and learning relationships among several types of actors pertaining to an LPS in the farming equipment and machinery sector, bearing in mind the specificities of small enterprises. To this end, the fieldwork carried out in this study aimed at: (i) investigating external and internal knowledge sources conducive to learning and (ii) identifying and analyzing motivating and inhibiting factors related to specificities of small enterprises in order to bring the LPS members closer together and increase their cooperation and interaction. Empirical evidence shows that internal aspects of the enterprises, related to management and infrastructure, can have a strong bearing on their joint actions, interaction and learning processes.