AMIRKABIR
Year:2006 | Volume:16 | Issue:63-B|Papers Count:8

Recently, numerous attempts have been made to obtain intelligent process planning systems and to increase the efficiency of computer aided process planning (CAPP) system using new mathematical methods. Graph theories, Petri nets, and fuzzy logic are powerful tools that are employed in this research to model different feasible states for performing a process and to obtain the best process performance path using exertion of the process designer's criteria. Then with the transformation of obtained model to machine language or other states which are capable for applying on tool machine controller can automatically do main pan of generation procedure and optimal path selection of process performance. The main idea of this research is the automation of assembly of industrial part using robots. In this paper it will be shown that several ideas and approaches which are proposed in the field of robotic assembly are applicable to the planning procedure modeling with minor modifications.

The Two-zone Thermodynamic models commonly used in SI Engines consider Two regions, burned and unburned, with assumptions of equilibrium for products in the burned region; and ignoring nature of the flame. Using these models to predict the NOx emission level, which is very important these days are not very accurate and the error in prediction is about 70%. In this Multi zone investigation, it is assumed that combustion of Natural Gas in the flame region is in equilibrium state, the product resulted from equilibrium combustion is considered by means of chemical kinetic method with 13 species and 24 chemical reactions for non-equilibrium combustion to predict the NOx formation. This has lead to two different temperatures for flame and combustion products. In this method, the error of NOx prediction has reduced to 30%. In this work combustion products recirculation effects on engine performance is also considered. The developed results are compared with existing experimental results. In this way the accuracy is validated.

Tool wear is a purpose in machining process. Dimensional accuracy, surface quality of work, machining forces, vibration, tool life, and machine tools life are influenced by tool wear. In other hand estimating the tool wear without stopping the operation is an essential problem in system automation. In this paper an intelligent approach for tool wear estimation from machining forces is proposed. Many experimental tests have been done in different machining conditions and tool wear amount have been measured directly. With this data, a back propagation (bp) neural network have been designed and trained. This neural network can estimate the tool wear amount with a high accuracy receiving data of depth of cut, feed rate, revolution and machining forces in X, Y and Z coordinates.

The main objective of this paper is to evaluate the impact of variations of demand and control parameters on the performance of a Just-In-Time (JIT) production system. Demand parameters considered in this work include the mean time between customers' order arrivals and the mean demand quantity. The control parameters are the mean and variance of delivery lead time, processing time, order batch size and supply lead time. To simplify the analysis, we consider a single chain of customer-manufacturer-supplier in a typical JIT production environment. This approach provides the capability of linking as many chains as needed to model a real situation. The proposed model has been implemented on Arena 3.0 real time simulation environment. By varying the values of system parameters a large number of simulation experiments have been conducted. The results indicate the sensitivity of the proposed model to the defined system parameters. The model has been extended to include two production cells, which has been analyzed using the same simulation method.

A new computational procedure based on two Spring-Mass-Damper-Dashpot (SMDD) and Spring-Mass- Damper (SMD) models representing contact behavior between the impactor and the plate are presented to study the low velocity impact phenomenon of sandwich plates comprising of a transversely flexible core and laminated composite face-sheets. The interaction between the impactor and the plate is modeled with the help of a new system having three-degree of-freedom, consisting of spring-mass-damper-dashpot or spring mass- damper. The plate may be subjected to initial in-plane biaxial normal and shear stresses along the edges of the plate. Impact is assumed to occur normally over the top or the bottom face-sheets, at arbitrary location. The boundary conditions of the top and the bottom face-sheets are independent. The effects of transverse flexibility of the core and structural damping of the plate are considered in the proposed models. Based on these models, the analytic functions describing the contact force, the transverse deflections of the impactor and the plate are derived. The effects of some parameters such as plate aspect ratio, boundary conditions, initial in-plane biaxial stresses, and impact location are examined in details.

A new control strategy for attitude maneuver of an elastic spacecraft is presented. Adaptive sliding mode control scheme with a synthesized Hybrid Sliding Surface (HSS) is used to overcome the difficulties arising from measurement of flexible dynamics coordinates. The excitation of flexible modes that frequently happens in the conventional sliding mode is minimized by using the synthesized sliding surface. The model of the spacecraft considered as rigid central hub and two flexible appendages. Collocated actuators and sensors are placed on the rigid central hub. Stability proof of the overall closed-loop system is given via Lyapunov analysis. Asymptotical tracking control of the multi-axis attitude motion and suppression of the elastic deformations are accomplished. Numerical simulations show the effectiveness of the proposed control scheme.

Designing of the road map for competitive strategic planning based on changing situations on Iranian day by- day planned companies is the main objective of this study. HCMS 4 model's design presenting a complementary to validated traditional models. Observing new factors, which have effects on preparation of strategic plans and their sequential order in HCMS' model is the platform of presented road map in this paper.Study review shows preparation of strategic planning using SWOTS technique for internal analysis to find strengths and weaknesses requires more factors than introduced in traditional models. Factors needed such as, Critical Success Factors, Key Performance Indicators, Organizational Excellence measures, Corporate Life Cycles' Diagnosis, Balance Score Cards measures, World Class Manufacturing measures and Core Competency findings. On the other hand, Porter Analysis, Industry attractive analysis, Stakeholders' fringe benefits for observing organizational opportunities and threats require additional subjects than introduced in existing matrix's standard elements. To achieve organizational master and main strategies, addition to complex combination of strengths, weaknesses, opportunities and threats need more actions such as, Life Cycle analysis and ADL6 matrix outcomes. It is inevitable, for selection and ranking of introduced strategies, forecast of external and internal factors' trends and evaluating strategies with trends and Evaluation Matrix take place. Description of mentioned requirements, the outcomes and their order is developing and presenting as the HCMS model's road map, in this paper.