An Intelligent Approach to High Quantity Automated Machining

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 integrate it with a 3D CAD modelling system. Upon completion the information could be directly extracted from the CAD system, eliminating the need for manual data input by the user. Originality/value: In spite of a large number of publications on machine tool design in the literature, publications on special purpose machines are very limited. The method of techno-economical analysis presented here for utilization of special purpose machines in comparison with other production alternatives is of great value to manufacturing engineers and specialists. Also the methodology presented for machine design and implementation is highly valued by machine tool designers and manufacturers

Intelligent Analysis of Utilization of Special Purpose Machines for Drilling Operations

Drilling and drilling-related operations constitute more than 60% of all machining processes in manufacturing industries. Consequently, it is important to know how to perform these operations properly. With availability of many machining processes capable of performing drilling operations sometimes it is difficult to decide which process would result in a higher profit or a lower unit cost for a given task. Due to increasing global competition, manufacturing industries are now more concerned with their productivity and are more sensitive than ever to their investments with respect to flexibility and efficiency of production equipment (Boothroyd and Knight, 2005, Wecka and Staimer, 2002). Researchers (Ko et al., 2005) believe that increasing the quality of production and reducing cost and time of production are very important factors in achieving higher productivity. Achieving this goal requires reconsidering current production methods that could lead to introduction of new production techniques and more advanced technologies

The heat treatment analysis of E110 case hardening steel

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

Simulation of a mobile robot navigation system

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 ultrasonic range sensor, the robot will navigate around that obstacle and then continue moving along it. While the robot is self-navigating in its environment, it continues to look for the target. The robot used in this work robot is scalable for industrial applications in mining, search and rescue missions, and so on. This robot is environmentally friendly and does not produce carbon emissions. In this paper the simulation of path planning algorithm for an autonomous robot is presented. Results of modelling the robot in a real-world industrial environment for testing the robot’s navigation are also discussed

An integrated model to use drilling modular machine tools

Modular machine tools provide a platform for drilling-related operations within automotive companies. The use of these machine tools is widespread; however, manufacturers wishing to use this technology frequently face the challenge of selecting the most appropriate manufacturing system. Accordingly, a comprehensive feasibility analysis procedure is required to assist decision-makers before any investment is made on the preparation of detailed machine design or purchase one. This paper presents a model, which collects the previous works of the authors. To do this, an integrated framework for decision-making of using machine tools is developed. The aim of this model is to enable users to make a logical decision by assessing the strengths and limitations of machine tools. To do this, the parameters which have a key influence on the decision-making process and relevant procedures are identified and integrated into a model. A case study is presented to illustrate the application of proposed model, and results are discussed. The results show that the proposed model is useful in assisting manufacturers in evaluating the performance of a modular machine tool in comparison with other alternatives

Evaluation of the effect of product demand uncertainty on manufacturing system selection

The use of advanced manufacturing systems is widespread; however, manufacturers frequently face difficult decisions when it comes to selecting the most appropriate system. Uncertainty regarding product demand makes this process more difficult, as many factors are influencing simultaneously. This paper focuses on analyzing the demand uncertainty on the performance of modular drilling manufacturing systems versus other alternatives and evaluating the uncertainty’s impacts on the final decision. To do so, a model is suggested and the effect of demand uncertainty on the output is investigated. Three automotive components of varying complexity are used to examine the approach for making reliable decision

Drilling reconfigurable machine tool selection and process parameters optimization as a function of product demand

Special purpose machines (SPMs) are customized machine tools that perform specific machining operations in a variety of production contexts, including drilling-related operations. This research investigates the effect of optimal process parameters and SPM configuration on the machine tool selection problem versus product demand changes. A review of previous studies suggests that the application of optimization in the feasibility analysis stage of machine tool selection has received less attention by researchers. In this study, a simulated model using genetic algorithm is proposed to find the optimal process parameters and machine tool configuration. During the decision-making phase of machine tool selection, unit profit is targeted as high as possible and is given by the value of the following variables: SPM configuration selection, machining unit assignment to each operation group, and feed and cutting speed of all operations. The newly developed model generates any random chromosome characterized by feasible values for process parameters. Having shown how the problem is formulated, the research presents a case study which exemplifies the operation of the proposed model. The results show that the optimization results can provide critical information for making logical, accurate, and reliable decisions when selecting SPMs

New cost model for feasibility analysis of utilising special purpose machine tools

Special purpose machine tools (SPMs) have been widely used to perform drilling-related operations in high volume production including within automotive component industries. The first step in designing and manufacturing a SPM is a feasibility analysis. Since SPMs have relatively higher investment cost than other machine tools, this task must be performed before any investment on the preparation of detailed design. The present paper explores an economic feasibility analysis strategy which aims to make logical decision by assessing the strengths and limitations of an SPM in comparison with other machine tools. The mathematical product cost model for SPMs is proposed for estimating important economic factors and then financial indicators are calculated to evaluate the SPM’s economic performance. A case study is used to examine the proposed model and results are compared with other machine tools. The proposed model provides a decision support approach for selecting an SPM for manufacturing a given part from an economic perspective

Sensitivity analysis for justification of utilising special purpose machine tools in the presence of uncertain parameters

Decision-makers in manufacturing area frequently face machine tool selection problem under uncertainty due to competitive market changes. Special purpose machines (SPMs), a relatively new class of reconfigurable machine tools, are used to react quickly to changes. Justification of utilising these machines vs. other machine tools requires a technique to investigate the sources of uncertainties. In this work, sensitivity analysis is utilised to investigate the sources of these uncertainties and errors which may reveal new insights for evaluating a machine tool. An illustrative example is provided to show the sensitivity of parameters on the economic performance of SPMs compared to the other alternatives. The results show that this analysis provides additional information and moves the decision closer to the optimum alternative