Search

The Mechanism of heat generation at the cutting region (tool-workpiece interface) during machining processes is a highly complicated phenomenon and depends on many process parameters. Elevated temperature during the machining process is a root cause of residual stress on the machined part as well as a cause of rapid tool wear. Although several methods have been developed to measure the temperature in machining, the in-situ application of these methods has many technical problems and restrictions. As a result, the utilization of computational methods to predict temperature in machining is very demanding. In this paper, the artificial intelligent models known as Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) were used to model and predict the temperature in machining. Several experiments were conducted to validate these models. These experiments were carried out on thin-walled AL7075 work pieces to investigate the effect of different machining parameters on temperature in turning. A thermal imaging Infrared (IR) camera was used to measure the temperature of the cutting area during machining. With respect to experimental data, the ANN and ANFIS models were developed and the results obtained from those models were then compared to the experimental results to evaluate the performance of the models. According to the results, the ANFIS model is superior to the ANN model in terms the accurate and reliable prediction of temperature in machining.

Purpose: The purpose of this paper is to introduce a solution that can enhance the reconfigurability of special purpose machines (SPMs). This is because SPMs can be used in different configurations and the reconfiguring time for these machines can be crucial. Therefore, it is important to reduce this time in order to enhance the performance of SPMs. Design/methodology/approach: A mechanical adapter is proposed as a solution to achieve the purpose of this paper. The design of the adapter is based on Multi Coupling (MC) type, and its functionality is based on “Plug and Produce”. This adapter is used to modify an SPM element called workpiece transfer in order to accommodate two types of chucks without the need to change the workpiece transfer. The performance criteria are analysed and investigated for this adapter. Findings: The proposed solution will enhance the reconfigurability of SPMs. This is because it will reduce the number of elements that are needed for reconfiguration. As a result, the time and cost for the reconfiguration will be reduced considerably. Research limitations/implications: Because SPMs have several types of elements, adapting the proposed solutions to be used for all elements can be a complex process. Therefore, more investigation and analysis need to be carried out in order to build a complete adapter system for SPMs. Practical implications: SPMs are already used widely in manufacturing. However, they are considered relatively expensive compared to the traditional machines tools because they are applied for special applications. The proposed solution will help to overcome this problem and make SPMs applicable for wider applications. Originality/value: The proposed solution is the first attempt in terms of enhancing the performance of SPMs. This can bring considerable benefits to the end users in manufacturing, who are using SPMs, in order to reduce the reconfiguration time and cost for these machine tools.

Purpose: Improving the productivity of a large manufacturing firm through development and implementation of a group technology model in a real manufacturing environment. This incorporates classification of parts, coding of parts and par families, formation of machine cells, and minimization of machine idle times through machine cell capacity adjustment. Design/methodology/approach: An algorithm has been developed for classification of all the parts into part families on the basis of manufacturing similarities. This formed 144 par families for more than 7500 different parts in production. The algorithm assigned group technology code to each part and a part family code to each part family. The former represents manufacturing characteristics of the part and the latter simplifies determination of part families. A number of machine cells were developed to produce all of the part families. After classification the system automatically directs each part to the appropriate machine cell for manufacturing. A computer software has been developed that automated the functions of classification of parts and assigning a group technology code to each part, determination of part families and assigning part family codes, and directing part families to appropriate machine cells for production. Findings: Introducing part family codes in addition to group technology codes considerably simplified the task of part family determination. Application of the system immediately resulted in an increased productivity of about 50%. This was due to the reduced setup times, less flow of parts in the workshop, production of similar parts due to parts classification, etc. Yet a productivity improvement of 100% or more is anticipated in near future. Research limitations/implications: As the manufacturing firm was producing a wide range of products at the time of implementation of this work, it was difficult to implement the project without affecting the production flow significantly. There has also be

Often, when highly accurate components are to be produced in relatively large volumes, manufacturers may not have a clear idea in utilising widely used CNC machines or less commonly used Special-Purpose Modular (SPM) machine tools. Consequently, the most economical method may not be selected. This paper helps manufacturers in deciding the most economical method by presenting the basic components of SPM machines and how they are used, the necessary steps in configuring these machines, and a detailed economical analysis while presenting a real case study where a comparison of the unit costs per part is made.

This paper presents methodologies for developing an intelligent CAD system assisting in analysis and design of reconfigurable special machines. It describes a procedure for determining feasibility of utilizing these machines for a given part and presents a model for developing an intelligent CAD system. The system analyzes geometrical and topological information of the given part to determine possibility of the part being produced by reconfigurable special machines from a technical point of view. Also feasibility of the process from a economical point of view is analyzed. Then the system determines proper positioning of the part considering details of machining features and operations needed. This involves determination of operation types, cutting tools and the number of working stations needed. Upon completion of this stage the overall layout of the machine and machining equipment required are determined.

This paper investigates mechanical and microstructural behaviour of E110 case hardening steel when subjected to different heat treatment processes includingquenching, normalizing and tempering. After heat treatment samples were subjected to mechanical and metallographic analysisand the properties obtained from applying different processes were analysed. The heat treatment process had certain effects on the resultant properties andmicrostructures obtained for E110 steel which are described in details. Quenching produced a martensitic microstructure characterized by significant increase in material’s hardness and a significant decreased in its impact energy. Annealed specimens produced a coarse pearlitic microstructure with minimal variation in hardness and impact energy. For normalized samples, fine pearlitic microstructure was identified with a moderate increase in hardness and significant reduction in impact energy. Tempering had a significant effect on quenched specimens, with a substantial rise in material ductility and reduction of hardness with increasing tempering temperature. Furthermore, Results provide additional substantiation of temper embrittlement theory for low.carbon alloys, and indicate potential occurrence of temper embrittlement for fine pearlitic microstructures.

Machining sequence planning can be considered as one of the most important functions of manufacturing process planning. However, less attention has been paid to automation of this function in contemporary computer-aided process planning systems. This paper describes an efficient algorithm for automatic machining sequence planning in 2.5D milling operations. It is programmed in LISP and forms the machining sequence planning module of a CIM system. This module is integrated with a feature-based design system that determines required machining operations and parameters for each machining operation. This information is then sent to the machining sequence planning module for determining proper machining sequence plans for producing the part. The algorithm generates feasible machining sequences based on the bilateral precedence between machining operations. The algorithm results in minimized tool changes.

The purpose of this study is to investigate the influence of different quenching media, size and shape of the specimen on the hardened depth of AISI 4140 steel. The paper demonstrates how these parameters can affect the hardness from the surface to the core of the samples. This study represents the relationship between hardened depth and geometry. Findings reveal the fact that high hardening effect was obtained in water-quenched samples by the virtue of the martensitic structure and lower hardened depth achieved in the air-quenched samples. Significant improvement achieved by increasing the velocity of air when quenched by compressed air. It was also concluded that the hardness of the quenched samples at certain depths can be estimated on the basis of heat transfer equations.

This study proposes a vision-based methodology for searching and relocation of target objects using a hexapod mobile robot. Such robot needs enhanced systems for navigation and vision-based object recognition. The navigation system is important for generating a path that covers the entire environment and for locating the position of the robot within that environment. Vision system is also important for undertaking the exploration task; it involves using a vision sensor and employing an optimal object recognition technique. This paper explains the development of such systems and presents a strategy for constructing the sensory platform to enable the robot to navigate and explore its environment. It also explains the challenges that arise from the viewpoint of vision sensor to the objects and suggests some relevant solutions. The experimental results demonstrate that it is possible to implement a navigation system within a minimum number of sensors if they are properly positioned in the robot’s body. The Experiments proved that the methodology used and that the codes developed made the robot capable of performing its task of finding, approaching and relocating objects as planned.

CAD/CAM activities play a crucial role in flexible manufacturing systems (FMSs). These activities have been improved due to the rapid development of computer technology. This improvement results in high productivity as well as the costs and time saving for FMSs which use computer numerical control (CNC) machined as major components. Modular fixtures (MFs) design is one of these activities that need to be developed. Computer aided fixture design (CAFD) systems were solutions for MFs design process. However, the need of automated CAFD systems has become important due to the development of artificial intelligence (AI) technology. In this paper, a methodology of the assembly process of CAFD system is presented by using SolidWorks as a powerful CAD environment. A proposed approach to automate CAFD system is also illustrated by applying the expert system and the knowledge base in SolidWorks.

Industrial robots become useless without end-effectors that for many instances are in the form of friction grippers. Commonly friction grippers apply frictional forces to different objects on the basis of programmers’ experiences. This puts a limitation on the effectiveness of gripping force that may result in damaging the object. This paper describes various stages of design and development of a low cost sensor-based robotic gripper that would facilitate the task of applying right gripping forces to different objects. The gripper is also equipped with range sensors in order to avoid collisions of the gripper with objects. It is a fully functional automated pick and place gripper which can be used in many industrial applications. Yet it can also be altered or further developed in order to suit a larger number of industrial activities. The current design of gripper could lead to designing completely automated robot grippers able to improve the efficiency and productivity of industrial robots.

Mobile robots are used in various application areas including manufacturing, mining, military operations, search and rescue missions and so on. As such there is a need to model robot mobility that tracks robot system modules such as navigation system and visi on based object recognition. For the navigation system it is important to locate the position of the robot in surr ounding environment. Then it has to plan a path towards desired destination. The navigation system of a robot has to identify all potential obstacles in order to find a suitable path. The objective of this research is to develop a simulation system to identify difficulties facing mobile robot navigation in industrial environments, and then tackle these problems effectively. The simulation makes use of information provided by various sensors including vision, range, and force sensors. With the help of battery operated mobile robots it is possible to move objects around in any industry/manufacturing plant and thus minimize environmental impact due to carbon emissions and pollution. The use of such robots in industry also makes it safe to deal with hazardous materials. In industry, a mobile robot deals with many tools and equipment and therefore it has to detect and recognize these objects and then track them. In this paper, the object detection and recognition is based on vision sensors and then image processing techniques. Techniques cove red include Speeded Up Ro bust Features (SURF), template matching, and colour segmentation. If the robot detects the target in its view, it will track the target and then grasp it. However, if the object is not in the current view, the robot continues its search to find it. To make the mobile robot move in its environment, a number of basic path planning strategies have been used. In the navigation system, the robot navigates to the nearest wall (or similar obstacle) and then moves along that obstacle. If an obstacle is detected by the robot using the built-in ultr

Purpose: To investigate the possibility of application of knowledge-based expert systems to facilitate the task of techno-economical feasibility analysis of utilization of special purpose machines for high quantity production tasks. Also, to study the possibility of assisting special purpose machine designers in applying knowledge-based expert systems in the design task in order to reduce required machine design time, improve machine design efficiency, and eliminate possible human errors. Design/methodology/approach: Development of a knowledge-based expert system has been proposed to help decide where to utilize special purpose machines to accomplish the production task. The knowledge-based expert system consists of a rule-base which contains qualitative human knowledge and expertise in the form of if-then rules; and a database which contains qualitative information of machining operations, and characteristics of standardized special purpose machine components. Findings: A case study has been presented where an analysis has been made on the basis of techno-economical considerations for a typical part with three machining operations to be produced in large quantities. It has been concluded that for the given production task, special purpose machines would result in a significant 59% reduction of costs compared to CNC machines, and 95.5% compared to traditional machines. The proposed methodology also reduces the time and effort needed for decision making on utilization of special purpose machines and determination of machine layout. In addition, it minimizes the level of expertise required to perform these functions and eliminates possible human errors. Research limitations/implications: The current system focuses on drilling and drilling-related operations which cover about 60% of all machining operations. More work is needed to cover other machining operations including milling. Also the KBES developed currently works on a standalone basis. Work is in progress to in

Utilization of various sensors has made it possible to extend capabilities of industrial robots. Among these are vision sensors that are used for providing visual information to assist robot controllers. This paper presents a method of integrating a vision system and a simulation program with an industrial robot. The vision system is employed to detect a target object and compute its location in the robot environment. Then, the target object’s information is sent to the robot controller via parallel communication port. The robot controller uses the extracted object information and the simulation program to control the robot arm for approaching, grasping and relocating the object. This paper presents technical details of system components and describes the methodology used for this integration. It also provides a case study to prove the validity of the methodology developed.

Purpose– The purpose of the research is to analyze instability in ED machining of silicon carbide (SiC) due to heat generation in the workpiece body. The results can be used in selecting a convenient machining set up. Design/methodology/approach– Various researches (1978‐2002) have shown the importance of SiC industrial applications in many branches of technology. Instability process in EDM as a very good candidate for SiC machining is still a serious problem. Joule heating generation in SiC body due to its very high electrical resistivity is a very important point, which needs to be considered. From this point of view, the machining set up can be optimized. Findings– The results of this research provide consideration of some factors to prevent against heat loss and voltage drop in SiC body during ED machining process. This leads the process to be more stable. Originality/value – According to the results of this research, Joule heating due to the voltage drop in SiC body is a main factor in ED machining of this material. Therefore, some techniques as voltage injection are recommended.

Rahimi, H., Masoudi, S., & Tolouei-Rad, M. (2021). Experimental investigation of the effect of EDM parameters and dielectric type on the surface integrity and topography. The International Journal of Advanced Manufacturing Technology. Advance online publication. https://doi.org/10.1007/s00170-021-08040-z

Aamir, M., Davis, A., Keeble, W., Koklu, U., Giasin, K., Vafadar, A., & Tolouei-Rad, M. (2021). The effect of TiN-, TiCN-, TiAlN-, and TiSiN coated tools on the surface defects and geometric tolerances of holes in multi-spindle drilling of Al2024 alloy. Metals, 11(7), article 1103. https://doi.org/10.3390/met11071103

Tolouei-Rad, M., & Aamir, M. (2021). Analysis of the performance of drilling operations for improving productivity. In M. Tolouei-Rad (Ed.), Drilling. IntechOpen. https://doi.org/10.5772/intechopen.96497

Aamir, M., Giasin, K., Tolouei-Rad, M., Ud Din, I., Hanif, M. I., Kuklu, U., ... Ikhlaq, M. (2021). Effect of cutting parameters and tool geometry on the performance analysis of one-shot drilling process of AA2024-T3. Metals, 11(6), article 854. https://doi.org/10.3390/met11060854

Aamir, M., Tolouei-Rad, M., & Giasin, K. (2021). Multi-spindle drilling of Al2024 alloy and the effect of TiAlN and TiSiN-coated carbide drills for productivity improvement. The International Journal of Advanced Manufacturing Technology, 114(9-10), 3047-3056. https://doi.org/10.1007/s00170-021-07082-7

Llanto, J. M., Tolouei-Rad, M., Vafadar, A., & Aamir, M. (2021). Impacts of traverse speed and material thickness on abrasive waterjet contour cutting of austenitic stainless steel AISI 304L. Applied Sciences, 11(11), article 4925. https://doi.org/10.3390/app11114925

Aamir, M., Tolouei-Rad, M., Giasin, K., Vafadar, A., Koklu, U., & Keeble, W. (2021). Evaluation of the surface defects and dimensional tolerances in multi-hole drilling of AA5083, AA6061, and AA2024. Applied Sciences, 11(9), article 4285. https://doi.org/10.3390/app11094285

Aamir, M., Giasin, K., Tolouei-Rad, M., & Vafadar, A. (2020). A review: drilling performance and hole quality of aluminium alloys for aerospace applications. Journal of Materials Research and Technology, 9(6), 12484-12500. https://doi.org/10.1016/j.jmrt.2020.09.003

Aamir, M., Tolouei-Rad, M., Vafadar, A., Raja, M. N. A., & Giasin, K. (2020). Performance analysis of multi-spindle drilling of Al2024 with TiN and TiCN coated drills using experimental and artificial neural networks technique. Applied Sciences, 10(23), article 8633. https://doi.org/10.3390/app10238633

Aamir, M., Muhammad, R., Tolouei-Rad, M., Giasin, K., & Silberschmidt, V. V. (2020). A review: microstructure and properties of tin-silver-copper lead-free solder series for the applications of electronics. Soldering & Surface Mount Technology, 32(2), 115-126. https://doi.org/10.1108/SSMT-11-2018-0046

A. Vafadar, M. Tolouei-Rad, and K. Hayward, “Evaluation of the effect of product demand uncertainty on manufacturing system selection," In Procedia Manufacturing, 27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM2017, Italy, 11, pp.1735-1743, 2017. doi:10.1016/j.promfg.2017.07.301. Published version Available here.

Aamir, M., Tolouei-Rad, M., Giasin, K., & Vafadar, A. (2020). Feasibility of tool configuration and the effect of tool material, and tool geometry in multi-hole simultaneous drilling of Al2024. The International Journal of Advanced Manufacturing Technology, 111(3-4), 861-879. https://doi.org/10.1007/s00170-020-06151-7

Farhan, U. H., Tolouei-Rad, M., & Osseiran, A. (2016). Use of AHP in decision-making for machine tool configurations. Journal of Manufacturing Technology Management, 27 (6), 874-888. Available here.

Aamir, M., Tu, S., Giasin, K., & Tolouei-Rad, M. (2020). Multi-hole simultaneous drilling of aluminium alloy: A preliminary study and evaluation against one-shot drilling process. Journal of Materials Research and Technology, 9(3). pp 3994-4006. https://doi.org/10.1016/j.jmrt.2020.02.026

Farhan, U. H., & Tolouei-Rad, M. (2017). Enhancing the reconfigurability of special purpose machine tools using mechanical module interfaces. Journal of Achievements in Materials and Manufacturing Engineering, (2),85, 56-66. doi:10.5604/01.3001.0010.8035 Available here.

Farhan, U. H., Tolouei-Rad, M., & Osseiran, A. (2017). Assembly modelling approach for special purpose machines. Assembly Automation, 38(2), 158-172. doi:here.