Purpose This paper aims to propose a process optimization approach showing how organizations are able to achieve sustainable and efficient process optimization, based on integrated process-risk analysis using several criteria to a better decision-making. Design/methodology/approach Several approaches are used (functional/dysfunctional) to analyze how processes work and how to deal with risks forming multi-criteria decision-making. In addition, a risk factor is integrated into the structured analysis and design techniques (SADT) method forming a novel graphical view SADT-RISK; it identifies process’s failures using the traditional failure modes, effects and criticality analysis (FMECA) and economic consideration “failure mode and effect, criticality analysis-cost FMECA-C” making a multi-criterion matrix for better decision-making. Subsequently, some recommendations are proposed to overcome the failure. Findings This paper illustrates a methodology with a case study in a company, which has a leading brand in the market in Algeria. The authors are integrating a varied portfolio of approaches linking with each other to analyze, improve and optimize the processes in terms of reliability and safety to deal with risks; reduce the complexity of the systems; increase the performance; and achieve a safer process. However, the proposed method can be readily used in practice. Originality/value The paper provides a new approach based on integrated management using new elements as an innovative contribution, forming a novel graphical view SADT-RISK; it identifies process’s failures using the traditional FMECA and economic consideration “a new multi-criterion matrix for better decision-making and using the SWOT analysis – Strengths, Weaknesses, Opportunities, Threats – as a balance to decide about the process improvement”. The authors conclude that this methodology is oriented and applicable to different types of companies such as financial, health and industrial as illustrated by this case study.

Renewable power generation facilities are constantly expanding due to the expected depletion of fossil fuels and the increasingly demanding policy of pollution control. Having said that, hydrogen is one of the promising energy sources. That said, hydrogen chain safety is an unescapable parameter that should continuously coexist with the development of hydrogen domain. In this context, this article presents a contribution to the risk analysis and evaluation of a complex hydrogen production system ’EGA-9000' at CIEMAT (Centre for Research on Energy, Environment and Technology - Madrid, Spain). The methodology followed in this study revolves around the risk analysis process through a FAST (Functional Analysis System Technique) functional analysis method and a HAZOP (HAZard and Operability) dysfunctional analysis method. The evaluation of the thirty-three scenarios identified by the risk analysis shows that the studied system is insecure. Indeed, five scenarios at an unacceptable level of risk. And it is noted that the risk of fire and explosion is the major risk for all scenarios studied. To this end, safety measures (recommendation) have been proposed based on the weaknesses detected by the risk analysis carried out.

The industrial risk mapping is a topical problem in the field of risk management that attracts many researchers to develop risk matrices to ensure consultation between their actors. In this context, this paper aims to propose the principal component analysis (PCA) method as support for this consultation. Indeed, the use of PCA method is justified by its robustness for aggregate initial data associated with industrial risks as principal factors and ranking of this risk in terms of their criticalities in risk matrices. However, the aggregation of initial data on industrial risks by the main factors, in some cases, leads to inaccuracies which make it difficult to classify certain risks. This paper proposes two variants of PCA method to solve this inaccuracy and succeeds in classifying risks according to their respective criticalities, namely PCA-Improved (PCA-I) and PCA-I-Fuzzy (PCA-IF). The results come from the PCA application and its proposed variants (PCA-I and PCA-IF) on an example of accident scenarios ranking. We have established a scientific basis for the capitalization of mapping tool for consultation and decision support to industrial risk managers.

This paper presents a hybrid scheme for the control of active and reactive powers using the direct vector control with stator flux orientation (SFO) of the DFIG. The hybrid scheme consists of Fuzzy logic, Reference Signal Tracking (F-RST) controllers. The proposed (F-RST) controller is compared with the classical Proportional-Integral (PI) and the Polynomial (RST) based on the pole placement theory. The various strategies are analyzed and compared in terms of tracking, robustness, and sensitivity to the speed variation. Simulations are done using MATLAB software. The simulation results prove that the proposed approach leads to good performances such as the tracking test, the rejection of disturbances and the robustness concerning the parameter variations. The hybrid controller is much more efficient compared to those of PI and RST controller, it also improves the performance of the powers and ensures some important strength despite the parameter variation of the DFIG.

This paper presents a hybrid scheme for the control of active and reactive powers using the direct vector control with stator flux orientation (SFO) of the DFIG. The hybrid scheme consists of Fuzzy logic, Reference Signal Tracking (F-RST) controllers. The proposed (F-RST) controller is compared with the classical Proportional-Integral (PI) and the Polynomial (RST) based on the pole placement theory. The various strategies are analyzed and compared in terms of tracking, robustness, and sensitivity to the speed variation. Simulations are done using MATLAB software. The simulation results prove that the proposed approach leads to good performances such as the tracking test, the rejection of disturbances and the robustness concerning the parameter variations. The hybrid controller is much more efficient compared to those of PI and RST controller, it also improves the performance of the powers and ensures some important strength despite the parameter variation of the DFIG.

The combination of neural networks and fuzzy controllers is considered as the most efficient approach for different functions approximation, and indicates their ability to control nonlinear dynamical systems. This paper presents a hybrid control strategy called Neuro-Fuzzy Sliding Mode Control (NFSMC) based on the Brushless Doubly fed Induction Generator (BDFIG). This replaces the sliding surface of the control to exclude chattering phenomenon caused by the discontinuous control action. This technique offers attractive features, such as robustness to parameter variations. Simulations results of 2.5 KW BDFIG have been presented to validate the effectiveness and robustness of the proposed approach in the presence of uncertainties with respect to vector control (VC) and sliding mode control (SMC). We compare the static and dynamic characteristics of the three control techniques under the same operating conditions and in the same simulation configuration. The proposed controller schemes (NFSMC) are effective in reducing the ripple of active and reactive powers, effectively suppress sliding-mode chattering and the effects of parametric uncertainties not affecting system performance.

Anti-lock Braking System (ABS) is used in automobiles to prevent slipping and locking of wheels after the brakes are applied. Its control is a rather complicated problem due to its strongly nonlinear and uncertain characteristics. The aim of this paper is to investigate the wheel slip control of the ground vehicle, comprising two new strategies. The first strategy is the Sliding Mode Controller (SMC) and the second one is the Fuzzy Sliding Mode Controller (FSMC), which is a combination of fuzzy logic and sliding mode, to ensure the stability of the closed-loop system and remove the chattering phenomenon introduced by classical sliding mode control. The obtained simulation results reveal the efficiency of the proposed technique for various initial road conditions.

Unified power flow controller is a power electronics-based device utilised to improve transmission line capacity and control power flow transmitted by power transmission systems. This paper presents the application of the decoupled control strategy to control independently active and reactive power in the event of changes in the step points of the powers. Two types of controllers are used to handle the control strategy proposed: conventional PI regulator and fuzzy logic PI regulator. The fuzzy logic controller must have high performance to handle the problem of adjustment of power decoupling. Also, a three level neutral point controller inverter is used in both series and shunt parts of the UPFC to get multistep voltage wave and improve the power quality.

The paper presents two fuzzy logic control algorithms: type-1 and type-2. These two nonlinear techniques are used for adjust the speed control with a direct stator flux orientation control of a doubly fed induction motor. The effectiveness of the proposed control strategy is evaluated under different operating conditions such as of reference speed and for load torque step changes at nominal parameters and in the presence of parameter variation (stator resistance, rotor resistance and moment of inertia). The results of the simulation of the doubly fed induction motor velocity control have shown that fuzzy type-2 ensures better dynamic performances with respect to fuzzy type-1 control, even by parametric variations and external disturbances.

Electrochemical methods, weight loss and surface analysis technique were used to study the effect of glutamic acid on the corrosion of Fe-19Cr stainless steel in 1 M hydrochloric acid solution. Results revealed that the corrosion inhibition of glutamic acid of Fe-19Cr in 1 M HCl was enhanced in the presence of the iodide ions due to synergistic effect. In the absence of KI, the inhibition of Fe-19Cr corrosion by glutamic acid was glutamic acid concentration dependent. Potentiodynamic polarization curves demonstrated that glutamic acid acts as a mixed type inhibitor. Self-Assembled Monolayers of glutamic acid were able to protect stainless steel from corrosion effectively. The adsorption of the inhibitor onto the stainless steel surface follows Langmuir adsorption isotherm. The value of free energy of the adsorption indicated that there is a physical interaction between the glutamic acid and the stainless steel surface.

During turning operations, tool-part-chip contact causes wear to the cutting tool. The objective of this work is to study the wear of the clearance faces of tungsten carbide cutting tools during turning operations. Experimental tests on tool life for dry turning operations were carried out at four different cutting speeds, where the feed rate and the depth of cut are kept at constant values: 0.08 mm/rev for feed rate and 0.5 mm for depth of cut. An analysis of the influence of cutting parameters on the tools wear and consequently tool life (Τ) was presented, then the roughness of the machined surface Ra and the morphology of the chips produced were studied. This study makes it possible to identify that the wear mechanisms and the tool life are strongly linked to the roughness of the machined surfaces and to the morphology of the chips produced during the turning operations.

Today, and to quickly meet the high demands of variability, supply chain efficiency and energy optimization, business markets are looking for modern manufacturing technologies and as a solution, industry 4.0 is using the benefits of integrating modern manufacturing technologies and information systems to promote production capabilities. In this context, intelligent industry represents a new generation of automatic production systems based on the concepts of intelligent industry, intelligent manufacturing, control and intelligent inspection, such as inspection on coordinate measuring machines (CMMs). This technology allows many machines to be integrated into a plant and controlled online using the MBD (Model Based Design) quality system. The problem of conformity of parts with complex geometry is becoming more and more important. The objective of this work is to present a 3D inspection technique on a virtual model (MBD: Model Based Design), using a coordinate measuring machine equipped with a “POWER INSPECT” measurement and inspection software. The interest of this technique is to show the impact of the dimensional inspection and geometric tolerance process of the CAD model for the CAI (Computer aided Inspection) approach on the fidelity of the finished product for additive manufacturing (AM) including intelligent industry.