Training Competences in Industrial Risk Prevention with Lego® Serious Play®: A Case Study

This paper proposes the use of the Lego® Serious Play® (LSP) methodology as a facilitating tool for the introduction of competences for Industrial Risk Prevention by engineering students from the industrial branch (electrical, electronic, mechanical and technological engineering), presenting the results obtained in the Universities of Cadiz and Seville in the academic years 2017–2019. Current Spanish legislation does not reserve any special legal attribution, nor does it require specific competence in occupational risk prevention for the regulated profession of a technical industrial engineer (Order CIN 351:2009), and only does so in a generic way for that of an industrial engineer (Order CIN 311:2009). However, these universities consider the training in occupational health and safety for these future graduates as an essential objective in order to develop them for their careers in the industry. The approach is based on a series of challenges proposed (risk assessments, safety inspections, accident investigations and fire protection measures, among others), thanks to the use of “gamification” dynamics with Lego® Serious Play®. In order to carry the training out, a set of specific variables (industrial sector, legal and regulatory framework, business organization and production system), and transversal ones (leadership, teamwork, critical thinking and communication), are incorporated. Through group models, it is possible to identify dangerous situations, establish causes, share and discuss alternative proposals and analyze the economic, environmental and organizational impact of the technical solutions studied, as well as take the appropriate decisions, in a creative, stimulating, inclusive and innovative context. In this way, the theoretical knowledge which is acquired is applied to improve safety and health at work and foster the prevention of occupational risks, promoting the commitment, effort, motivation and proactive participation of the student teams.Spanish Ministry of Science, Innovation and Universities / European Social Fund: Ramón y Cajal contract (RYC-2017-22222

Training Competences in Industrial Risk Prevention with Lego (R) Serious Play (R): A Case Study

This paper proposes the use of the Lego (R) Serious Play (R) (LSP) methodology as a facilitating tool for the introduction of competences for Industrial Risk Prevention by engineering students from the industrial branch (electrical, electronic, mechanical and technological engineering), presenting the results obtained in the Universities of Cadiz and Seville in the academic years 2017-2019. Current Spanish legislation does not reserve any special legal attribution, nor does it require specific competence in occupational risk prevention for the regulated profession of a technical industrial engineer (Order CIN 351:2009), and only does so in a generic way for that of an industrial engineer (Order CIN 311:2009). However, these universities consider the training in occupational health and safety for these future graduates as an essential objective in order to develop them for their careers in the industry. The approach is based on a series of challenges proposed (risk assessments, safety inspections, accident investigations and fire protection measures, among others), thanks to the use of "gamification" dynamics with Lego (R) Serious Play (R). In order to carry the training out, a set of specific variables (industrial sector, legal and regulatory framework, business organization and production system), and transversal ones (leadership, teamwork, critical thinking and communication), are incorporated. Through group models, it is possible to identify dangerous situations, establish causes, share and discuss alternative proposals and analyze the economic, environmental and organizational impact of the technical solutions studied, as well as take the appropriate decisions, in a creative, stimulating, inclusive and innovative context. In this way, the theoretical knowledge which is acquired is applied to improve safety and health at work and foster the prevention of occupational risks, promoting the commitment, effort, motivation and proactive participation of the student teams

Oscillation-based DFT for Second-order Bandpass OTA-C Filters

This document is the Accepted Manuscript version. Under embargo until 6 September 2018. The final publication is available at Springer via https://doi.org/10.1007/s00034-017-0648-9.This paper describes a design for testability technique for second-order bandpass operational transconductance amplifier and capacitor filters using an oscillation-based test topology. The oscillation-based test structure is a vectorless output test strategy easily extendable to built-in self-test. The proposed methodology converts filter under test into a quadrature oscillator using very simple techniques and measures the output frequency. Using feedback loops with nonlinear block, the filter-to-oscillator conversion techniques easily convert the bandpass OTA-C filter into an oscillator. With a minimum number of extra components, the proposed scheme requires a negligible area overhead. The validity of the proposed method has been verified using comparison between faulty and fault-free simulation results of Tow-Thomas and KHN OTA-C filters. Simulation results in 0.25μm CMOS technology show that the proposed oscillation-based test strategy for OTA-C filters is suitable for catastrophic and parametric faults testing and also effective in detecting single and multiple faults with high fault coverage.Peer reviewedFinal Accepted Versio

Control of Complex Dynamic Systems by Neural Networks

This paper considers the use of neural networks (NN's) in controlling a nonlinear, stochastic system with unknown process equations. The NN is used to model the resulting unknown control law. The approach here is based on using the output error of the system to train the NN controller without the need to construct a separate model (NN or other type) for the unknown process dynamics. To implement such a direct adaptive control approach, it is required that connection weights in the NN be estimated while the system is being controlled. As a result of the feedback of the unknown process dynamics, however, it is not possible to determine the gradient of the loss function for use in standard (back-propagation-type) weight estimation algorithms. Therefore, this paper considers the use of a new stochastic approximation algorithm for this weight estimation, which is based on a 'simultaneous perturbation' gradient approximation that only requires the system output error. It is shown that this algorithm can greatly enhance the efficiency over more standard stochastic approximation algorithms based on finite-difference gradient approximations

On the Selection of Tuning Methodology of FOPID Controllers for the Control of Higher Order Processes

In this paper, a comparative study is done on the time and frequency domain tuning strategies for fractional order (FO) PID controllers to handle higher order processes. A new fractional order template for reduced parameter modeling of stable minimum/non-minimum phase higher order processes is introduced and its advantage in frequency domain tuning of FOPID controllers is also presented. The time domain optimal tuning of FOPID controllers have also been carried out to handle these higher order processes by performing optimization with various integral performance indices. The paper highlights on the practical control system implementation issues like flexibility of online autotuning, reduced control signal and actuator size, capability of measurement noise filtration, load disturbance suppression, robustness against parameter uncertainties etc. in light of the above tuning methodologies.Comment: 27 pages, 10 figure

The Kentucky Noisy Monte Carlo Algorithm for Wilson Dynamical Fermions

We develop an implementation for a recently proposed Noisy Monte Carlo approach to the simulation of lattice QCD with dynamical fermions by incorporating the full fermion determinant directly. Our algorithm uses a quenched gauge field update with a shifted gauge coupling to minimize fluctuations in the trace log of the Wilson Dirac matrix. The details of tuning the gauge coupling shift as well as results for the distribution of noisy estimators in our implementation are given. We present data for some basic observables from the noisy method, as well as acceptance rate information and discuss potential autocorrelation and sign violation effects. Both the results and the efficiency of the algorithm are compared against those of Hybrid Monte Carlo. PACS Numbers: 12.38.Gc, 11.15.Ha, 02.70.Uu Keywords: Noisy Monte Carlo, Lattice QCD, Determinant, Finite Density, QCDSPComment: 30 pages, 6 figure