Skill management is a key factor in improving effectiveness of industrial companies, notably their maintenance services. The problem considered in this paper concerns scheduling of maintenance tasks under resource (maintenance teams) constraints. This problem is generally known as unrelated parallel machine scheduling. We consider the problem with a both objectives of minimizing total weighted tardiness (TWT) and number of tardiness tasks. Our interest is focused particularly on solving this problem under skill constraints, which each resource has a skill level. So, we propose a new efficient heuristic to obtain an approximate solution for this NP-hard problem and demonstrate his effectiveness through computational experiments. This heuristic is designed for implementation in a static maintenance scheduling problem (with unequal release dates, processing times and resource skills), while minimizing objective functions aforementioned.

This paper focuses on the exploitation of the response surface methodology (RSM) to determine optimum cutting conditions leading to minimum surface roughness and cutting force components. The technique of RSM helps to create an efficient statistical model for studying the evolution of surface roughness and cutting forces according to cutting parameters: cutting speed, feed rate and depth of cut. For this purpose, turning tests of hardened steel alloy (AISI 4140) (56 HRC) were carried out using PVD – coated ceramic insert under different cutting conditions. The equations of surface roughness and cutting forces were achieved by using the experimental data and the technique of the analysis of variance (ANOVA). The obtained results are presented in terms of mean values and confidence levels. It is shown that feed rate and depth of cut are the most influential factors on surface roughness and cutting forces, respectively. In addition, it is underlined that the surface roughness is mainly related to the cutting speed, whereas depth of cut has the greatest effect on the evolution of cutting forces. The optimal machining parameters obtained in this study represent reductions about 6.88%, 3.65%, 19.05% in cutting force components (Fa, Fr, Ft), respectively. The latters are compared with the results of initial cutting parameters for machining AISI 4140 steel in the hard turning process.

In this paper, a method for severity fault diagnosis of ball bearings is presented. The method is based on wavelet packet transform (WPT), statistical parameters, principal component analysis (PCA) and support vector machine (SVM). The key to bearing faults diagnosis is features extraction. Hence, the proposed technique consists of preprocessing the bearing fault vibration signal using statistical parameters and energy obtained through the application of Db8- WPT at the third level of decomposition. After feature extraction from vibration signal, PCA is employed for dimensionality reduction. Finally, particle swarm optimization with passive congregation-based support vector machine is used to classify seven kinds of bearing faults. The classification results indicate the effectiveness of the proposed method for severity faults diagnosis in ball bearings.

This work illustrates the manufacturing of the honeycomb hexagonal topology structures by the kirigami technical, and the compressive testing of this specimen. The cellular configuration is simulated using a series of finite element models representing fullscale. The models are benchmarked against experimental results from pure compression tests. Finite element models of the honeycomb assemblies under compressive loading have been developed using nonlinear shell elements from an ANSYS code. Good agreement is observed between numerical nonlinear simulations and the experimental results.

The bulk room-temperature polymerization of styrene initiated by environmentally friendly catalysts Maghnite-Na+ is investigated. The catalyst removed from the reaction mixture simply by filtration could be regenerated and reused. The effect of the Maghnite-Na+ catalyst loading on degree of polymerization had been studied and state their inverse relation. The catalyst was characterized by X-ray diffraction and FTIR spectroscopy.

This paper presents a novel composite material produced by a natural reinforcement subjected to tensile test. The used reinforcement is made of Diss fibers. The Diss (Ampelodesma mauritanica) is a Mediterranean wild plant. This fiber is characterized in tensile according to ASTM standard. The results obtained show that the fiber Young’s modulus and the stress at break were very interesting and were similar to those obtained for some natural fibers such as sisal fiber. The composite was developed to study by three differing volume fractions of 20%, 30 % and 40 %.

Serviceable engineering components not only rely on their bulk material properties but also on the design and the characteristics of their surface. These characteristics influence directly the surface quality of the machined products. In terms of surface roughness, the influence of the tool material can be also caused by its tribological properties, i.e. a contact behavior between cutting tool and workpiece. This study presents a formulation of the nominal’s coefficient and friction forces generated in machining between workpiece and cutting tool using cutting force profiles. The obtained equations led to the evaluation of coefficient, frictional forces and cutting inserts characterization in terms of better surface finish and lowest frictional forces. Indeed, results show that the contact between cutting tool and workpiece depends on the materials cutting tool nature, and that the cutting tool type can influences the surface roughness of the machined surface.