Identification and control of occupational risks in a Sao Paulo metropolitan region quarry

Crushed stone mining is the third largest mining economy in Brazil, where almost half is produced in the Sao Paulo metropolitan region. The segment registers the highest number of accidents among the extractive industries, which justifies the concern with workers` health and safety, and the importance of controlling occupational hazards. Since 2002, the NR-22 Standard (NR-22: Occupational Health and Safety in Mining) makes compulsory the elaboration of a Risk Management Program that identifies risks and establishes control measures. Considering the crushed stone mining industry importance to the state, this paper evaluates and discusses the risks identified in unit operations during the production process of crushed stone in an open pit mine in order to propose control measures for the development of the Risk Management Program. Although this study refers to a specific quarry, it can be applied to other mines from the same sector since some considerations are made regarding differences in manufacturing processes. The research was based on the identification of the main risks associated with drilling, blasting, load & haulage, crushing and screening through field measurements of some hazardous agents, together with company reports. The results contributed to the choice of the appropriate control measures for the improvement Of workers` health and safety conditions.

Suspension of apatite particles in a self-aerated Denver laboratory flotation cell

Effective solids suspension is a necessary precondition for particle collection, and solids suspension is largely dependent on the hydrodynamics of the flotation cell. This study attempted to correlate the status of the suspension of apatite particles of different sizes in a Denver laboratory flotation cell versus the impeller rotational speed (N) adopted to operate the machine. The latter variable (N) influences the impeller capacity to lift the particles from the bottom of the tank and also to disperse them throughout the volume of the vessel. Such an impeller capacity can be characterized by the critical impeller speed for the accomplishment of solids off-bottom suspension (N(z)) and also by the velocity of the radial water flow discharged by the impeller (U) divided by the particle terminal settling velocity (U(s)). This way, the status of the suspension of apatite particles inside the flotation cell can be characterized by one of three categories: ""segregation"" (N/N(2) < 0.60 and U(s)/U > 0.08); ""suspension"" (0.60 <= N/N(2) < 1 and 0.06 < U(s)/U < 0.10); and ""dragging"" (N/N(2) >= 1 and U(s)/U <= 0.03). The range of impeller rotational speed (N), which was able to suspend the finest particles (D(p) = 90,mu m), was unable to suspend the coarsest particles (D(P) = 254 mu m). Conversely, the high value of N (N > 1,300 rpm), which is adequate to suspend the coarsest particles, may promote the entrainment of the finest particles to the froth layer.

A simple and effective inverse projection scheme for void distribution control in topology optimization

The ability to control both the minimum size of holes and the minimum size of structural members are essential requirements in the topology optimization design process for manufacturing. This paper addresses both requirements by means of a unified approach involving mesh-independent projection techniques. An inverse projection is developed to control the minimum hole size while a standard direct projection scheme is used to control the minimum length of structural members. In addition, a heuristic scheme combining both contrasting requirements simultaneously is discussed. Two topology optimization implementations are contributed: one in which the projection (either inverse or direct) is used at each iteration; and the other in which a two-phase scheme is explored. In the first phase, the compliance minimization is carried out without any projection until convergence. In the second phase, the chosen projection scheme is applied iteratively until a solution is obtained while satisfying either the minimum member size or minimum hole size. Examples demonstrate the various features of the projection-based techniques presented.

Modeling, control and experimental validation of a novel actuator based on shape memory alloys

The paper presents the development of a mechanical actuator using a shape memory alloy with a cooling system based on the thermoelectric effect (Seebeck-Peltier effect). Such a method has the advantage of reduced weight and requires a simpler control strategy as compared to other forced cooling systems. A complete mathematical model of the actuator was derived, and an experimental prototype was implemented. Several experiments are used to validate the model and to identify all parameters. A robust and nonlinear controller, based on sliding-mode theory, was derived and implemented. Experiments were used to evaluate the actuator closed-loop performance, stability, and robustness properties. The results showed that the proposed cooling system and controller are able to improve the dynamic response of the actuator. (C) 2009 Elsevier Ltd. All rights reserved.

Development of Control Systems for Safety Instrumented Systems

Safety Instrumented Systems (SIS) are designed to prevent and / or mitigate accidents, avoiding undesirable high potential risk scenarios, assuring protection of people`s health, protecting the environment and saving costs of industrial equipment. The design of these systems require formal methods for ensuring the safety requirements, but according material published in this area, has not identified a consolidated procedure to match the task. This sense, this article introduces a formal method for diagnosis and treatment of critical faults based on Bayesian network (BN) and Petri net (PN). This approach considers diagnosis and treatment for each safety instrumented function (SIF) including hazard and operability (HAZOP) study in the equipment or system under control. It also uses BN and Behavioral Petri net (BPN) for diagnoses and decision-making and the PN for the synthesis, modeling and control to be implemented by Safety Programmable Logic Controller (PLC). An application example considering the diagnosis and treatment of critical faults is presented and illustrates the methodology proposed.

MODELLING AND CONTROL OF ERSW PROCESSES BY NEURONAL NETWORK

A study on the use of artificial intelligence (AI) techniques for the modelling and subsequent control of an electric resistance spot welding process (ERSW) is presented. The ERSW process is characterized by the coupling of thermal, electrical, mechanical, and metallurgical phenomena. For this reason, early attempts to model it using computational methods established as the methods of finite differences, finite element, and finite volumes, ask for simplifications that lead the model obtained far from reality or very costly in terms of computational costs, to be used in a real-time control system. In this sense, the authors have developed an ERSW controller that uses fuzzy logic to adjust the energy transferred to the weld nugget. The proposed control strategies differ in the speed with which it reaches convergence. Moreover, their application for a quality control of spot weld through artificial neural networks (ANN) is discussed.

High Carbon Ferro-chromium Production by Self-reducing Process: Effects of Fe-Si and Fluxing Agent Additions

The technology of self-reducing pellets for ferro-alloys production is becoming an emerging process due to the lower electric energy consumption and the improvement of metal recovery in comparison with the traditional process. This paper presents the effects of reduction temperature, addition of ferro-silicon and addition of slag forming agents for the production of high carbon ferro-chromium by utilization of self-reducing pellets. These pellets were composed of Brazilian chromium ore (chromite) concentrate, petroleum coke, Portland cement, ferro-silicon and slag forming components (silica and hydrated lime). The pellets were processed at 1 773 K, 1 823 K and 1 873 K using an induction furnace. The products obtained, containing slag and metallic phases, were analyzed by scanning electron microscopy and chemical analyses (XEDS). A large effect on the reduction time was observed by increasing the temperature from 1 773 K to 1 823 K for pellets without Fe-Si addition: around 4 times faster at 1 823 K than at 1 773 K for reaction fraction close to one. However, when the temperature was further increased from 1 823 K to 1 873 K the kinetics improved by double. At 1 773 K, the addition of 2% of ferro-silicon in the pellet resulted in an increasing reaction rate of around 6 times, in comparison with agglomerate without it. The addition of fluxing agents (silica and lime), which form initial slag before the reduction is completed, impaired the full reduction. These pellets became less porous after the reduction process.

High Carbon Ferro-Chromium by Self-Reducing Process

This paper discusses the effects of temperature, addition of ferro-silicon and fluxing agents for the production of high carbon ferro-chromium by self-reducing process. The use of self-reducing agglomerates for ferro-alloys production is becoming an emerging processing technology due to lowering the electric energy consumption and improving the metal recovery in comparison with traditional ones. The self-reducing pellets were composed by chromite, petroleum coke, cement and small (0.1% - 2%) addition of ferro-silicon. The slag composition was adjusted by addition of fluxing agents. The reduction of pellets was carried out at 1773K (1500 degrees C), 1823K (1550 degrees C) and 1873K (1600 degrees C) by using induction furnace. The products obtained, containing slag and metallic phases, were analyzed by scanning electron microscopy and chemical analyses (XEDS). By increasing temperature from 1773K to 1823K large effect on the reduction time was observed. It decreased from 30 minutes to 10 minutes, for reaching around 0.98 reduction fraction. No significant effect on reduction time was observed when the reduction temperature was increased from 1823K to 1873K. At 1773K, the addition of 2% of ferro-silicon in the pellet resulted in an increasing reaction rate of around 6 times, in comparison with agglomerate without this addition. The addition of fluxing agents (silica and hydrated lime) has effect on reduction time (inverse relationship) and the pellets become less porous after reduction.

Thermodynamic self-consistency issues related to the Cluster Variation Method: The case of the BCC Cr-Fe (Chromium-Iron) system

The Cluster Variation Method (CVM), introduced over 50 years ago by Prof. Dr. Ryoichi Kikuchi, is applied to the thermodynamic modeling of the BCC Cr-Fe system in the irregular tetrahedron approximation, using experimental thermochemical data as initial input for accessing the model parameters. The results are checked against independent data on the low-temperature miscibility gap, using increasingly accurate thermodynamic models, first by the inclusion of the magnetic degrees of freedom of iron and then also by the inclusion of the magnetic degrees of freedom of chromium. It is shown that a reasonably accurate description of the phase diagram at the iron-rich side (i.e. the miscibility gap borders and the Curie line) is obtained, but only at expense of the agreement with the above mentioned thermochemical data. Reasons for these inconsistencies are discussed, especially with regard to the need of introducing vibrational degrees of freedom in the CVM model. (C) 2008 Elsevier Ltd. All rights reserved.

Robust integration of real time optimization with linear model predictive control

Here, we study the stable integration of real time optimization (RTO) with model predictive control (MPC) in a three layer structure. The intermediate layer is a quadratic programming whose objective is to compute reachable targets to the MPC layer that lie at the minimum distance to the optimum set points that are produced by the RTO layer. The lower layer is an infinite horizon MPC with guaranteed stability with additional constraints that force the feasibility and convergence of the target calculation layer. It is also considered the case in which there is polytopic uncertainty in the steady state model considered in the target calculation. The dynamic part of the MPC model is also considered unknown but it is assumed to be represented by one of the models of a discrete set of models. The efficiency of the methods presented here is illustrated with the simulation of a low order system. (C) 2010 Elsevier Ltd. All rights reserved.

Real time optimization (RTO) with model predictive control (MPC)

This paper studies a simplified methodology to integrate the real time optimization (RTO) of a continuous system into the model predictive controller in the one layer strategy. The gradient of the economic objective function is included in the cost function of the controller. Optimal conditions of the process at steady state are searched through the use of a rigorous non-linear process model, while the trajectory to be followed is predicted with the use of a linear dynamic model, obtained through a plant step test. The main advantage of the proposed strategy is that the resulting control/optimization problem can still be solved with a quadratic programming routine at each sampling step. Simulation results show that the approach proposed may be comparable to the strategy that solves the full economic optimization problem inside the MPC controller where the resulting control problem becomes a non-linear programming problem with a much higher computer load. (C) 2010 Elsevier Ltd. All rights reserved.

Optimizing model predictive control of an industrial distillation column

The main scope of this work is the implementation of an MPC that integrates the control and the economic optimization of the system. The two problems are solved simultaneously through the modification of the control cost function that includes an additional term related to the economic objective. The optimizing MPC is based on a quadratic program (QP) as the conventional MPC and can be solved with the available QP solvers. The method was implemented in an industrial distillation system, and the results show that the approach is efficient and can be used, in several practical cases. (C) 2011 Elsevier Ltd. All rights reserved.