Search results for: Mohieddine Ksantini
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5

Search results for: Mohieddine Ksantini

5 Insecticidal Effect of a Botanical Plant Extracts (Ultra Act®) on Bactrocera oleae (Diptera:Tephritidae) Preimaginal Development and Pupa Survival

Authors: Imen Blibech, Mohieddine Ksantini, Manohar Shete

Abstract:

Bactrocera oleae is one of the most economically damaging insects of olive in Tunisia and other producing countries of olive trees. As a reliable alternative to synthetic chemical insecticides, botanical insecticides are considered natural control methods safe for the environment and human health. The certified botanical insecticide ULTRA-ACT® effectively on large scale of insects is approved per Indian and International organic standards certified organic pesticides. Olives with signs of olive fly infestation were collected from productive olive trees in three Sahel localities of Tunisia. Infested fruits were separated daily for larval stage control purposes, into new rearing boxes under microclimatic conditions at 75% R.H, 25 ± 3°C and 8 L-16D. Treatment with ULTRA-ACT® extract solutions was made by dipping methods; each fruit was pipetted in 5 mL of extract for 10 seconds then air- dried. Five doses of ULTRA-ACT® were used for a bioassay, plus a water-only control. A total of 200 infested olive fruits were treated in separate dishes with a proportion of 10 olives per dish. A total of 20 dishes were used for each concentration treatment as well as 20 dished utilized as control. The bioassay was conducted with 3 replicates. The development of the larval and pupal stages was recorded since the egg hatching until emergence of adults. It was determined that ULTRA-ACT® extracts on succeeding concentrations; 0.25, 0.5, 1 and 2% show significant effect on the biology of the pest. Increased concentration decreased significantly adult emergence from pupae and affect the egg hatchability percentage. Therefore, larval mortality increased insignificantly with the increase of the product concentration. The 2nd instar larvae were more susceptible to the product and after 72 hours the maximum mortality (75%) was observed with ULTRA-ACT® 2%. The present work aimed to give a possible and efficient alternative solution for B. oleae biological control with a promising botanical insecticide.

Keywords: Bactrocera oleae, olive insect pest, Ultra Act®, larval mortality, pupal emergency, biological control

Procedia PDF Downloads 114
4 Surface Roughness Modeling in Dry Face Milling of Annealed and Hardened AISI 52100 Steel

Authors: Mohieddine Benghersallah, Mohamed Zakaria Zahaf, Ali Medjber, Idriss Tibakh

Abstract:

The objective of this study is to analyse the effects of cutting parameters on surface roughness in dry face milling using statistical techniques. We studied the effect of the microstructure of AISI 52100 steel on machinability before and after hardening. The machining tests were carried out on a high rigidity vertical milling machine with a 25 mm diameter face milling cutter equipped with micro-grain bicarbide inserts with PVD (Ti, AlN) coating in GC1030 grade. A Taguchi L9 experiment plan is adopted. Analysis of variance (ANOVA) was used to determine the effects of cutting parameters (Vc, fz, ap) on the roughness (Ra) of the machined surface. Regression analysis to assess the machinability of steel presented mathematical models of roughness and the combination of parameters to minimize it. The recorded results show that feed per tooth has the most significant effect on the surface condition for both steel treatment conditions. The best roughnesses were obtained for the hardened AISI 52100 steel.

Keywords: machinability, heat treatment, microstructure, surface roughness, Taguchi method

Procedia PDF Downloads 132
3 Statistical Analysis of Surface Roughness and Tool Life Using (RSM) in Face Milling

Authors: Mohieddine Benghersallah, Lakhdar Boulanouar, Salim Belhadi

Abstract:

Currently, higher production rate with required quality and low cost is the basic principle in the competitive manufacturing industry. This is mainly achieved by using high cutting speed and feed rates. Elevated temperatures in the cutting zone under these conditions shorten tool life and adversely affect the dimensional accuracy and surface integrity of component. Thus it is necessary to find optimum cutting conditions (cutting speed, feed rate, machining environment, tool material and geometry) that can produce components in accordance with the project and having a relatively high production rate. Response surface methodology is a collection of mathematical and statistical techniques that are useful for modelling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. The work presented in this paper examines the effects of cutting parameters (cutting speed, feed rate and depth of cut) on to the surface roughness through the mathematical model developed by using the data gathered from a series of milling experiments performed.

Keywords: Statistical analysis (RSM), Bearing steel, Coating inserts, Tool life, Surface Roughness, End milling.

Procedia PDF Downloads 410
2 Larvicidal Activity of Azadirachtin and Essential Oils from Thymus capitatus against Prays oleae Bern (Lepidoptera, Yponomeutidae)

Authors: Imen Blibech, Mohiedine Ksantini, Mohamed Bouaziz

Abstract:

Prays oleae is a major insect of olive in the Mediterranean Region. In an effort to find effective and affordable ways of controlling this pest, larvicidal activity of essential oils from Tunisian Thymus capitatus were analyzed in comparison to Azadirachtin, a biologically active compound insecticide. The essential oils were extracted by hydrodistillation, and their chemical composition was determined by gas liquid-chromatography coupled with mass spectroscopy. The main components of chemical components were oxygenated monoterpenes (60.24%). The most abundant oxygenated monoterpenes were carvacrol (54.11%). Monoterpenes hydrocarbons were much more abundant and dominated by the o-cymene (16.68%). Both active compounds of Azadirachtin and Thymus capitatus oil extracts exhibited significant larvicidal activity against P. oleae with LC50 values 81.30 ppm and 52.49 ppm respectively. Dose-response relationships were established with almost 100% mortality when using the highest dose 100 ppm of T. capitatus oil extracts and 80 ppm of Azadirachtin. At the lowest dose (10 ppm), T. capitatus oil extracts and Azadirachtin caused 60% and 76% larval mortality in 48 hours respectively. The larval mortality rate greatly decreased with increases of the dilution of both oil extract compounds. Larval development duration appeared to be prolonged to about 12 days for larvae feeding on control diet. The maximum antifeedant activity was shown by both T. capitatus oil extract and Azadirachtin at LC90 values (47.5 and 50.1 ppm respectively). Tunisian T. capitatus oil extract used at low concentrations could be considered as eco-friendly promising insecticide similar to Azadirachtin that has significant potential for the biological control of P. oleae.

Keywords: Thymus capitatus, chemical composition, azadirachtin, larvicidal effects, antifeedant activity, Prays oleae

Procedia PDF Downloads 179
1 Implementation of Correlation-Based Data Analysis as a Preliminary Stage for the Prediction of Geometric Dimensions Using Machine Learning in the Forming of Car Seat Rails

Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali

Abstract:

When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

Procedia PDF Downloads 14