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齿轮轴.dwg

镗铣加工中心换刀机械手部件设计【三维PROE】【含全套23张CAD图纸】【答辩毕业资料】

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镗铣加工中心换刀机械手部件设计【三维PROE】【含全套CAD图纸】【答辩毕业资料】.rar

机械手装配图--.dwg---(点击预览)

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任务书-镗铣加工中心换刀机械手.doc---(点击预览)

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3D-PROE

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关键词：: 加工中心机械手部件设计三维 proe 全套 cad 图纸答辩毕业资料

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摘要
机械手是在机械化，自动化生产过程中发展起来的一种新型装置。机械手虽然目前还不如人手那样灵活，但它具有能不断重复工作和劳动，不知疲劳，不怕危险，抓举重物的力量比人手力大的特点，因此，机械手已受到许多部门的重视，并越来越广泛地得到了应用。
在机械加工中，大部分零件都要进行多种工序加工。在一般数控机床的整个加工过程中，真正用于切削的时间只占整个工作时间的30%左右，其余的大部分时间都花在安装、调整刀具、装卸、搬运零件和检查加工精度等辅助工作上。自动换刀装置是数控加工中心在工件的一次装夹中实现多道工序加工不可缺少的装置。为充分发挥机床的作用，数控中心均配有自动换刀装置。
本课题重点在于镗铣加工中心换刀机械手的结构设计。目前工业机械手主要用于机床加工、铸造、热处理等方面，无论数量，品质还是性能方面都不能完全满足工业发展的需要。本课题重点解决的问题：换刀机械手部件的结构设计，对关键零件进行校核以及尺寸的优化选取。
主要设计内容有：
（1）设计镗铣加工中心换刀机械手部件的结构，传动系统以及驱动系统，使其能够满足快速，平稳，准确换刀的功能。
（2）完成重要零件的设计，主要包括齿轮的设计，轴的设计，手指的设计。使用Pro/E对所有换刀机械手零件进行三维建模，并建立总装模型。
（3）用AutoCAD画出换刀机械手重要零部件的二维图纸。
关键词：镗铣加工中心；结构设计；换刀机械手；伸缩回转式单臂双爪机械手。

Abstract
The robot is a new device developed in the mechanization and automation of the production process. Although the robot is not as staffing flexibility, but it has repeated the work and labor, I do not know fatigue, not afraid of danger, the the snatch weight of force than manual force, Therefore, the robot has been subject to many sectors, and increasingly has been applied more widely.
In machining, most of the parts should be carried out a wide range of machining processes. Whole process in general CNC machine tools for cutting real time accounted for only about 30% of the entire working time, most of the rest of the time is spent on installation, adjustment tool, loading and unloading, handling parts and check processing accuracy auxiliary work on Automatic tool changer CNC machining center in one clamping of the workpiece to achieve multi-channel processing indispensable device. In order to give full play to the role of the machine tool, CNC centers are equipped with automatic tool changer.
The focus of this project is boring and milling machining center blade structural design of the robot. Industrial robot is mainly used for machining, casting, heat treatment, regardless of the quantity, quality or performance are not fully meet the needs of industrial development. Focused on solving the problem of the subject: A tool of the structural design of the robot components, select the check key parts and size optimization.
The main design elements:
(1) Design milling centers gripper parts of the structure, the transmission system and drive system to enable it to meet the fast, smooth and accurate tool.
(2) the completion of the important parts of the design, including the choice of gear design, the design of the shaft bearing. Pro / E 3D modeling, and all parts of gripper
assembly model.
(3) AutoCAD to draw the gripper important parts of the two-dimensional drawings.
Keywords: boring and milling machining center; structural design; gripper; retractable rotary arm claw robot.

目录
摘要
Abstract
第1章绪论 1
1.1选题的背景和意义 1
1.2国内外研究现状和发展趋势 1
1.2.1机械手简介 1
1.2.2 机械手的分类 3
1.2.3工业机械手研究趋势 6
1.3 换刀机械手研究意义 7
1.4 设计的内容和思路 7
第2章镗铣加工中心换刀机械手总体设计 8
2.1 换刀机械手的工作原理分析 8
2.2 机械手的平稳性 10
2.3 机械手的运动特性 11
2.4 换刀机械手方案的确定 12
第3章换刀机械手的总体方案设计 12
3.1手爪部分设计 12
3.2 机械手手臂的设计 13
3.3 机械手传动方式的选择 14
3.3.1机械手转过180度的传动机构选择 14
3.3.2 主轴以及机械手上下伸缩的传动机构设计 16
3.4 换刀机械手驱动机构的选择 18
第4章换刀机械手的结构设计及尺寸确定 19
4.1 手指结构设计及计算 19
4.1.1 手指夹紧力的计算 19
4.1.2 手指部分的相关校核 21
4.2手臂的弯曲变形 23
4.3 轴与机械手配合部分的直径的选取 25
4.4 机械手转过180度的驱动机构设计 26
4.5 设计参数 29
第5章总结与展望 30
参考文献 31
致谢 33

第1章绪论
1.1选题的背景和意义
机械制造业是一个国家最基础的行业，为整个国民经济提供技术装备，其发展水平是国家工业化程度的主要指标之一。在机械工业中，应用机械手的意义可以概括如下：

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传动齿轮.gif

传动齿条.gif

大主轴.gif

上端盖.gif

手指.gif

转轴.gif

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字数统计.gif

内容简介：: Beyond intelligent manufacturing: A new generationof flexible intelligent NC machinesS. Mekida,*, P. Pruschekb, J. HernandezcaThe University of Manchester, School of Mechanical, Aerospace and Civil Engineering, Manchester M60 1QD, UKbInstitute for Control Engineering of Machine Tools and Manufacturing Units, University of Stuttgart, GermanycIDEKO Technological Centre, Arriaga Kalea, 2 20870 Elgoibar Gipuzkoa, Spaina r t i c l ei n f oArticle history:Received 30 November 2006Received in revised form 3 March 2008Accepted 4 March 2008Available online 29 April 2008a b s t r a c tNew challenges for intelligent reconfigurable manufacturing systems are on the agenda forthe next generation of machine tool centres. Zero defect workpieces and just-in-time pro-duction are some of the objectives to be reached for better quality and high performanceproduction. Sustainability requires a holistic approach to cover not only flexible intelligentmanufacture but also product and services activities. New routes philosophy of possiblemachine architecture with characteristics such as hybrid processes with in-process inspec-tion and self-healing will be presented with great features as well as challenges related tovarious aspects of the next generation of intelligent machine tool centres.? 2008 Elsevier Ltd. All rights reserved.1. IntroductionComplex component machined with zero defects is a top performance in mass production and it becomes a new chal-lenge required for the new generation of intelligent machine-tools. Increasing the precision and accuracy of machines, prod-ucts and processes offers substantial benefits to a wide range of applications from ultra-precision to mass production withhigher quality and better reliability. The recent development of ultra precision machines is reaching nanometre precisionunder very tight conditions 1,2.The machine-tool industry is responding to a number of requirements, e.g. e_commerce, just-in-time-production andmost importantly zero defect component. This is facilitated by integrating new materials, design concepts, and control mech-anisms which enable machine tools operating at high-speed with accuracies below than 5 lm. However the integration ofhuman experience in manufacturing towards flexible and self-optimising machines is widely missing. This can be achievedby enhancing existing computing technologies and integrating them with human knowledge of design, automation, machin-ing and servicing into e-manufacturing.The next generation will be described as new intelligent reconfigurable manufacturing systems which realises a dynamicfusion of human and machine intelligence, manufacturing knowledge and state-of-the-art design techniques. This may leadto low-cost self-optimising integrated machines. It will encompass fault-tolerant advanced predictive maintenance facilitiesfor producing high-quality error-free workpieces using conventional and advanced manufacturing processes.Machining process monitoring and control is a core concept on which to build up the new generation of flexible self-opti-mising intelligent NC machines. In-process measurement and processing of the information provided by dedicated sensorsinstalled in the machine, enables autonomous decision making based on the on-line diagnosis of the correct machine, work-piece, tool and machining process condition, leading to an increased machine reliability towards zero defects, together withhigher productivity and efficiency. Indeed, the main sensing and processing techniques in the literature 35 focus on0094-114X/$ - see front matter ? 2008 Elsevier Ltd. All rights reserved.doi:10.1016/j.mechmachtheory.2008.03.006* Corresponding author. Tel.: +44 161 2003804.E-mail address: s.mekidmanchester.ac.uk (S. Mekid).Mechanism and Machine Theory 44 (2009) 466476Contents lists available at ScienceDirectMechanism and Machine Theoryjournal homepage: /locate/mechmtmonitoring strategies for part condition monitoring (surface roughness, surface integrity and dimensional accuracy), toolcondition monitoring (the so-called TCM for wear and breakage detection), process condition monitoring (chatter onsetand collision detection) and machine component condition monitoring for predictive maintenance purposes (rotary compo-nents and parts subject to friction such as guideways). Since direct and in-process measurement is not generally possible dueto the aggressive environment in the cutting zone surroundings, the main research effort over the last decades for part andtool monitoring has been focused on indirect measurement techniques (process condition-based), in which cutting processcharacteristics (i.e. cutting forces and power, vibrations, cutting temperature, acoustic emission, etc.) are measured in orderto indirectly infer the part and tool condition 6,7. Sensitivity offered by CNC internal servo signals from open architecturecontrollers is under study as well 8,9, since they enable the development of monitoring and control strategies without theneed of installing additional sensors in the machine.In the same way, based on the data provided by in-process monitoring, autonomous self-optimisation can be performedwith the integration of process control strategies into the machine tool control architecture. Machining process control strat-egies are classified into two main groups 5, namely adaptive control constraint (ACC) and adaptive control optimisation(ACO).In the former ACC control strategies, a process variable (i.e. cutting force) is kept constant and under control through thereal-time in-process regulation of a cutting process parameter (i.e. cutting feed), with the aim of increasing process produc-tivity and repeatability. Main research efforts on ACC strategies focus on cutting force control 1012 and chatter vibrationsuppression 13,14.On the other hand, special attention has to be paid to the latter process control strategies (ACO). Characteristic examplescan be found at 1519. The main functionality provided by such control systems is the post-process self-optimisation ofprocess parameter set-up (i.e. feeds, depths of cut, etc.), with the objective of set-up time minimisation, process knowledgemanagement and process optimisation, towards flexible just-in-time production. With the in-process monitoring of processperformance and the post-process measurement of the resulting part quality, a knowledge based process model is used todetermine the new optimised set of cutting parameters, enabling autonomous self-optimisation. In the same way, as a pre-vious step to optimisation, ACO systems are also applied to select the first process set-up for new part quality and processrequirements. Therefore, if a flexible intelligent NC machine tool is to be developed, process knowledge based models are acomponent of primary importance to be integrated under the machine tool control architecture.In addition to the adaptation of control parameters according to process conditions, control parameters have also to beoptimal during handling (including changing operations of work pieces and tools) and positioning operations as these oper-ations account typically for more than 50% of the overall operating time. Earlier methods for parameter optimisation con-centrated on the reduction of positioning and settling times of the feed axis by tuning only a few basic controlparameters (e.g. gain of the position control loop and gain and reset time of the velocity control loop). With increased com-putational power, optimisation methods as described in 20 can now be reinvestigated for the use with a wider parameterset including the parameters for acceleration and jerk limits which are directly influencing the vibrations of an axis.If the characteristics of a controlled axis are known by means of the vibration behaviour, an adequate generation of theprogrammed trajectories can yield a further optimisation. Methods for input shaping 49 can be used to design trajectoriesthat do not excite resonant frequencies of a given system. Hence, settling times and thus positioning times can be furtherreduced.Concerning parameter optimisation through self-learning particularly, the interest of the so-called machine learning ap-proaches 21 will be introduced as the main research trend in process monitoring and control strategies towards the intel-ligent manufacturing system.2. Expected characteristics of the next generationThe expected characteristics of the next generation of machine centres are described as follows:(a) Integration: development of an integrated machine tool being capable of performing both conventional and non-con-ventional processes in one platform. (b) Bi-directional data flow: definition of a bi-directional process chain for unified datacommunication exchange between CAD, CAM, CNC and Drive systems. (c) Process control loop: development and CNC inte-gration of robust and reliable real-time strategies for the in-process tool, part, and process condition monitoring and control.(d) Predictive maintenance: specification of a load- and situation-dependent condition monitoring for machine componentsas a basis for self-reliant machine operation. This will be followed by the formulation of a self-organising predictive main-tenance schedule that is based on self- and remote diagnostics and covers both short and long term aspects. (e) Autonomousoptimisation: development of a self-configuring self-optimising control system for autonomous manufacturing, based on thein-process monitoring, characterisation and management of process knowledge. To facilitate such characteristics, the follow-ing topics will be necessary to be implemented:(a) To develop an integrated intelligent machine centre dedicated to e-manufacturing.(b) To investigate and develop fast, stable and stiff reconfigurable machines with hybrid machining processes to prepare anew platform for future machine-tools.(c) To investigate implementation of total error compensation and in situ inspection facility.S. Mekid et al./Mechanism and Machine Theory 44 (2009) 466476467(d) To develop and produce new methodologies and concepts of autonomous manufacturing, self-supervision and self-diagnostic/tuning/healing.(e) To develop and integrate real-time process controllers into open CNC and drive system architecture, taking themachine from an axis-controlled system to a machining process-controlled self-reliant system, based on the on-lineinformation provided by robust and reliable sensing techniques for tool, part, and machining process conditionmonitoring.(f) To develop and incorporate an extendible and knowledge based CAM system capable of recognising complex features,performing self-learning based on in-process monitored data provided by machine control loops, and autonomouslydetermining the optimum tools/sets for given requirements of part quality, machine productivity and process effi-ciency. Following the e-manufacturing approach, in a second step, CAM systems capable of sharing self-optimised pro-cess knowledge between networked machines are to be developed.An interdisciplinary approach of machine-tool builders in order to achieve these objectives becomes necessary and in-cludes control manufacturers, research institutions and potential end-users. Such a development will realise a number ofbreakthroughs in the future, e.g. (a) Delay-free cum zero-downtime production: the proposed e-manufacturing approach willsee the use of electronic services based on available data from machined processes, sensor signals, and human experiencethat is integrated in a zero delay-time system to enable machines with near zero-downtime and production that meets userrequirements with zero delay time. (b) Self-reliant production: machines will be enabled to operate widely autonomously. (c)Optimal production: self-configuration and self-optimisation will eliminate production errors down to the limitations of thein-process measurement devices.3. Concepts of intelligent and flexible machinesIn Fig. 2, the authors propose a new integrated concept for the next generation of machine tool centres. Based on theknowledge acquired and the features extracted, the performance of control systems will be extended towards self-controlledmanufacturing with the objectives of cost-effective, high quality, fault-tolerant and more flexible systems with better pro-cess capability. New intelligent control systems have to be developed and integrated with open architecture controllers suchas OpenCNC?or OSACA-based CNCs. In order to allow an automated error-free production with near zero down time, openinterfaces, learning capabilities, self-tuning and self-adjusting mechanisms as well as sophisticated model-based predictioninstruments have to be implemented at these layers. Quality inspection could operate in situ with environmental conditionstaken into account. For the first time, the concept of self-healing with e-maintenance could be operational.3.1. Industrial requirements for machining process monitoring and controlAmong the future requirements that have to be focused on, are the aspects of the just-in-time-production and zero defectcomponents, together with continuously higher part quality and process productivity. Automation level provided bymachining process monitoring and control systems contributes to those requirements. However, taking into account thatthere is a growing need for production of small lot sizes in the market, flexibility lack in such automation systems is the maindrawback to deal with.Indeed, flexible monitoring systems are required under the actual market requirements and thus, reliable process diag-nosis is necessary under different cutting conditions. Nowadays, a common problematic shared by conventional processmonitoring approaches for part and tool condition monitoring is the lack of reliability under changing cutting conditionshence limiting the flexibility of such automation systems 3. As a characteristic example of this problematic for process con-dition based tool condition monitoring (TCM), the process condition is not only influenced by changes in tool condition, butit is also directly affected by cutting conditions. Furthermore, under different cutting conditions, different wear mechanismscan be activated on the tool, each one having its particular impact on process and part condition. Therefore, when setting-upprocess monitoring systems for new cutting conditions, previous trials for process signal database retrieval are required 4.These are combined together with skilled operators with the necessary process knowledge in order to interpret changes inprocess behaviour (i.e. forces, vibrations, etc.) and set-up suited detection limits. Additionally, flexible process monitoringequipments often requires additional sensors that can fail and result in unforeseen downtime. As a result, when high flex-ibility is required, monitoring systems are usually switched-off in industry, and direct post-process measurement is per-formed, with the corresponding reliability lack in the machined part quality.Dealing with such a problematic, model-based process monitoring and sensor fusion approaches are pointed out as thealternative in order to get reliable process condition diagnosis, with a clear research effort over last years for machining pro-cesses such as turning 2224, grinding 4,25,26 and milling 27.On the other hand, the integration of human experience in manufacturing is widely missing concerning machining pro-cess optimisation. Set-up time reduction is critical when flexible just-in-time production is required. Nowadays, set-up-timemainly depends on process knowledge concentrated in skilled operators, and there is a lack of systematic management, re-trieval, sharing and optimisation of that key knowledge. Furthermore, characterisation of process knowledge and develop-ment of models for autonomous process optimisation are required if set-up times are to be drastically reduced.468S. Mekid et al./Mechanism and Machine Theory 44 (2009) 466476Concerning this process knowledge related problematic, intelligent manufacturing systems (IMS) are the key on goingresearch concepts. The main objective of the IMS concepts is the development of an autonomous machine tool control sys-tem able to perform self-tuning and self-learning, provided by the on-line monitoring and retrieval of cutting process relatedknowledge (i.e. forces, part quality, machining time, tool life econometrics, predictive maintenance, etc.), towards flexibleand self-optimising machine tools. With the successful incorporation of IMSs into machine tool control integrated CAM sys-tems, set-up times for new parts and process optimisation needs will be minimised, enabling just-in-time production, inde-pendent from machine operator skills.3.2. New possibilities in knowledge based societyThe core concept of developing a flexible machine operated by a controller that performs process-adaptation on the basisof a bi-directional data exchange between all parts of the process chain will yield a completely new way of manufacturing,Fig. 1. Bi-directional process chain.S. Mekid et al./Mechanism and Machine Theory 44 (2009) 466476469especially small lot sizes, (Fig. 1). Economically speaking, this will have a large impact on end-users of machine tools that willbe able to meet customer requests in shorter time.In addition to adaptiveness, there is a growing need for intelligence in numerical controllers as processes are becomingmore complex and manufacturing time has to be decreased. Much of this intelligence can be realised by introducing e-tech-nologies for self-maintenance supported by remote-maintenance functions. If a machine has the ability to be serviced in partpreparation, load-dependent monitoring, fault diagnosis from internal and external knowledge bases, optimal manufactur-ing can be guaranteed while downtimes and set-up times are minimised, especially when a variety of different parts must bemanufactured in a short time.Consequently, the most important advantage for end-user will be the availability of machines that are able to operate in aself-reliant manner, self-optimising and automatically serviced. Thus, there is no need to employ a number of cost-expensivepersonnel to accomplish a large number of different process types which is not profitable to small companies.At first glance, the advantages for machine tool builders may be less obvious. By taking a closer look, it is obvious thatwith a growing need for production of small lot sizes there is also a growing market for machine tools to fill this gap.Although a number of approaches to build modular machines and controls are known, their application to commercial prod-ucts is missing as these approaches are mostly scientific.Concepts could be created to combine modular machine approaches with modular numerical controllers that integrate e-technologies derived from other disciplines, namely e-business and e-servicing. By generating common knowledge bases ofmachine abilities and possible machine disabilities and faults, not only an automated maintenance can be achieved but alsoan automated machine design optimisation which mainly addresses the machine tool builders, towards a holistic productlife cycle management (Fig. 3).3.3. Research trends in process monitoring and control towards IMSsThe expertise in the machine-tool sector must rapidly converge towards new paradigms of production and new conceptsof product-services and will move to a production industry from resource-based towards knowledge-based approaches, toremotely manufacture on-demand, multi-use, upgradeable product-services. Intelligent manufacturing systems (IMSs) are aFig. 2. A new approach for the future machine centres.470S. Mekid et al./Mechanism and Machine Theory 44 (2009) 466476research area with world-wide interest encompassing all industrialised nations. Progress has already been made in countriessuch as the USA, Japan, Canada and Australia; European countries have also initiated some work in this area. In order to makea significant impact, the next generation of IMS should embody not only the processes but also the associated intelligence,so that they can be used to manufacture high-value components with near-zero faults.Integration of human expertise into machine tool control system has been a key research issue over last years in themachining process monitoring and control field. It can be emphasised that intelligence is strongly connected with learning.Learning ability must be an indispensable feature of future IMSs. In particular, artificial intelligence (AI) modelling ap-proaches under the machine learning concept (knowledge-based systems (KBS), expert systems (ES), artificial neural net-works (ANN), fuzzy logic (FL), etc.) have to be pointed out as a core concept for the new generation of intelligent NCmachines. A comprehensive study in machine learning approaches for machining process monitoring and control can befound at 21.On the other hand, regarding the integration of monitoring and control systems into machine control architecture, mostof the control strategies are single input single output (SISO), as in ACC strategies for force control, where only one processvariable in controlled (i.e. cutting force) through the regulation of one process parameter (i.e. feed). However, in order to dealwith the existing interdependence between different process variables, first proposals in the literature consider MIMO ap-proaches (multiple input multiple output) 28, where multiple inter-related controlled variables and regulating parametersare considered. Following that integration trend, ACC strategies subordinated to ACC controllers are also presented 29.Recently, there has been work focusing on integration of multiple controllers leading to research in supervisory controlsystems 11,30, where the joint processing of the data concerning machining process, part, tool and machine componentconditions is carried for the co-ordinated management and situation-dependant decision making onto the correspondingset of subordinated and inter-dependant process control modules. Several approaches and techniques can be found forsupervisory system development: KBSs 31,32, hierarchic control systems 33,34, Grafcet based decision-making 35,etc. An example of the superior performance of a supervisory control system over independent single controllers in termsof productivity and part quality can be found at 36. Additionally, as a potential advantage of such an integrated approach,networked supervisory systems to machine component suppliers will enable periodical remote machine condition inspec-tions, leading to fault-tolerant advanced predictive maintenance facilities for producing high-quality error-free workpieces.Therefore, a systematic design approach is necessary for the effective construction and implementation of supervisorysystems into an open-architecture machine tool control as inter-dependant and co-ordinated machining process controlmodules.3.4. Aspects of the new generation of machine toolsThe next generation of machine tools will be reconfigurable and self-adaptive as single machine or within a manufactur-ing system. It is designed for a rapid change in structure and components in order to rapidly introduce a new product andadjust production capacity and functionality in response to market changes.Fig. 3. Holistic approach to evolutionary manufacturing.S. Mekid et al./Mechanism and Machine Theory 44 (2009) 466476471The next generation of machines will be characterised by a limp from independent assembled sensor, actuator and con-trols towards mechatronic knowledge based system. The machines could also be modular with embedded intelligence andstandardised interfaces to be able to assemble and reconfigure. To Secure work envelope, high dexterity, high stiffness, etc.,in the new configuration knowing the programmed tasks, a rapid simulation should be computed to check specifications. Theinnovative design of the next generation is heading towards adaptronic modules, i.e. intelligent spindle, haptic cutting toolsand real time reconfiguration interfaces.Hence, the aspects have to be addressed for the next generation of machine tools:? New self-adaptive machine structures based on mechatronic concepts.? Mechatronic knowledge-based intelligent modules.? Integrated process control with in-process product characterisation.? Intelligent manufacturing equipment.? Development of tools for integrated/embedded optimised system.? Embedded simulation capability for current configuration.? Scalability of the machines.4. Virtual design and simulationVirtual machine tool engineering gives the possibility to design, test, optimise, control and machine parts in a computersimulation environment. This saves much time and money in avoiding build the first test-prototype. The rigid and flexiblemachine tools models are analysed under various jerk, acceleration, velocity and control profiles at high speeds. The coupledsimulation of machine structure, drives and CNC control offers not only the chance to study the interactions between thedifferent instance for offline optimisations of a new machine tool. In contrast, real-time simulation models are able to beconnected to a real CNC building a hardware-in-the-loop system which allows for optimisation of control parameters anda completely virtual ramp-up process 37.The digital model of the machine is integrated to the numerical simulation of the cutting process; hence the machine toolcan be tested to machine particular parts under desired cutting conditions. However, the virtual machine tool technologystill requires fundamental research in the area of process simulation, integration of all analysis modules in a user friendlysimulation programme for the users 38. Fundamentals of precision engineering with second and third order errors couldbe taken into account in the design process to drastically reduce most of the errors 39.Simulation of manufacturing processes using multi agent technologies allows testing of various configurations of pro-duction processes and locates bottlenecks and other possible problems 40. To achieve higher accuracy in machining atmicro and macro scale, full virtual simulation including control, manufacturing process and mechanical capabilities arerequired.5. Intelligent open architecture controllersSuccessful development and implementation of supervisory systems concerning process monitoring and control demandshigh flexibility for the machine tool controller architecture 3, both for software and hardware component integration andupgrading. Open architecture control (OAC) is a concept derived from this flexibility requirement. In particular, PC-basedhomogeneous and standardised platforms are pointed out as the best solution for flexibility 41. Although there are avail-able commercial solution in the market under the OAC concept (Delta Tau PMAC-NC, IBH PA 8000, etc.), together with largeinternational consortiums addressing this field (OSACA in Europe, OMAC in United States, JOP in Japan, etc.), the use of OACsystems is still limited to research and development activities, since standardisation still remains unresolved for their wide-spread application in the machine tool industry.Nowadays, most of the available commercial process monitoring and control systems (Prometec, Artis, etc.) remain asadd-on external hardware systems integrated to machine tool CNCs, with various available communication standards(Ethernet, Profibus, CAN, etc.), and with a clear trend towards higher HMI (Human Machine Interface) integration level asadditional and flexible software modules into PC-based CNCs. There are only few systems that allow the integration of pro-cess monitoring routines at a lower level. An example for an open system is the newest generation of servo-drives offered byBosch-Rexroth which has a freely programmable PLC. Bosch-Rexroths own productivity agent is using this PLC to offer mon-itoring and maintenance algorithms based on drive signals (current and scale information). However, processing algorithmsand decision making strategies integrated by commercial systems are relatively simple, and the ability to extend system re-sources in order to upgrade system performance through the integration of process knowledge in terms of complex user-de-fined signal processing algorithms and advanced control strategies is widely missing. Furthermore, standardised interfacesare missing that enable the distribution of monitoring, control and servicing algorithms to different NC and drive platformsat the levels of velocity and current control (i.e. below 1 ms cycle times). On the other hand, last generation of open CNCsavailable in the market (Fanuc, Siemens, etc.) offer the possibility of real-time execution of user-defined control algorithmsin the cycle times of the position controller (usually P1 ms). Again, programming languages for such algorithms are472S. Mekid et al./Mechanism and Machine Theory 44 (2009) 466476proprietary solutions, with a clear lack of a standard in this field. In the same way, complexity of programmable algorithms isstill restricted by the limited processing capability offered nowadays.A core problem that hinders the realisation of flexible interfaces is related to the system design. Both drives and CNC areusually based on digital signal processors or microcontrollers. Both types of processing units feature a serial execution of alltasks. Consequently, a complex task scheduler must be implemented to guarantee a stable real-time processing of data. Con-trol, monitoring and serving tasks can never be performed in a truly parallel way. An alternative to these serial control sys-tems are units that are based on field programmable gate arrays (FPGA). With new FPGA-based control platforms, it ispossible to configure drive controllers and PLCs on one chip using hardware description languages (VHDL). All of these unitscan access the same signals and process data in parallel in hard real-time. As an extension to the set of control and PLC func-tionality, it is possible to instantiate complete DSPs or CPUs as additional units. As these blocks are not simulated but estab-lished as real hardware circuits, they can execute sophisticated code that is programmed in high level languages (C,Assembler) in the same way as the low-level units in real-time and in parallel. A sketch of an open drive architecture isshown in Fig. 5 50.6. Concept of self-healing in machinesSelf-healing is an important feature required in the new generation of machine-tools. This will go beyond faults monitor-ing and scheduling maintenance to achieve extremely high reliability. The aim is to heal a component from software andFig. 4. Hybrid network application.AlteraAPEXEncoder Evaluation ModulePWM ModuleFPGACPUFIFOFilterPLCSensor Driver3rdLayer: FreelyProgrammableCPUs/DSPsDiagnosticsCurrentControl2ndLayer: FPGA1st Layer: HardwareCPUSlotsVHDLC / ASM Fig. 5. Open drive architecture.S. Mekid et al./Mechanism and Machine Theory 44 (2009) 466476473environmental errors. A worst case would be to replace a defect component by either automatic maintenance scheduling, or,engage a new mode of functioning among others in the machine but this would need prediction of scenarios at the initialstage of the machine design. Once this is possible, it is assumed that the system would never fail, hence and great increasein life time and economic outcomes.The concept of self-healing in software based systems will intervene after perceiving faults and attempt to solving bugsand conflicts, make the necessary adjustments and restore a working order required for the particular on-going application.Human intervention could be required; otherwise agents could be programmed to assist the self-healing. While writing thispaper an interesting survey has been published to cover self-healing software based systems 42.Many active research developments are working in this direction and could support machine design aspects like newmaterials such as composite materials that can heal themselves. Fibres break under relatively low impact loads releasingrepair agents that seep into the cracks and harden, repairing the damage 43. Nervous materials could also be key materialsfor machines as the can feel pain and attempt to recover from it, hence bringing the machine dynamic and thermal char-acteristics back to requirements.7. Up-coming intelligent multi or hybrid agent systemsRecent agents have been developed to address a number of obstacles and ease the use both communication and param-eter monitoring in manufacturing. Sensor clustering becomes a very attractive application particularly in manufacturingwhere various types of phenomena are monitored and information should be exchanged between internal sensors (i.e. drivesensors to measure current and positions), external sensors (such as vibration sensors) and the CNC control that supervisesthe machine performance.It is clear that agents have to either work alone or cooperate to achieve a task. The question could be whether a singleagent could perform all the tasks or the concept of multi-agent has to be introduced. Communication between agents isimportant to transfer information between agents with a capability of prioritization. With multi-agent systems could par-allel computation be used to speed up the system. Robustness, scalability and the programming become easier 44.Multi agent systems would not probably be of systematic use if the system is not suitable or if it is applied it may intro-duce delays or will be an expensive solution. Further multi-agents are not suitable when used only to decentralise a systemnormally modelled as a centralised system. One should not try to provide multi-agent solutions to the non-suitable prob-lems, it is foremost important to focus on the problems the multi-agents are meant to solve and not on the possible benefits45.Today the focus of agent research is more on multi-agent systems than on single agent systems, since agents that co-oper-ate and/or communicate can solve much more complex tasks than just one single agent is capable of 46. Verification andvalidation of multi agents has already been addressed in 47. Learning and autonomous capabilities should be part of themulti-agents strategy. Nahm and Ishikawa 48 have proposed a hybrid network of agents as shown in Fig. 4, they employa lightweight middle agent, called interface agent” for continuous or discrete interactions between local agents (type 1),between a collection of local agents and a collection of remote agents (type 2), and between a local agent and a remote agent(type 3). Therefore, agent interactions are made only via the interface agent.Concerning networked machines to a central process knowledge server, process information data can be forwarded to acentralised agent for expert analysis and decision making 3, sharing knowledge to thirds in the net. Synergistic union ofnetworked machines could perform as process knowledge generation nodes.8. Concluding remarksAlthough strong research efforts have been conducted over the last decades in machining process monitoring and controlfield, there has been little transfer of such technologies into industry. The main lacks to overcome the challenges in order toincrease the impact and to bring all the potential benefits provided by such automation and optimisation systems into ma-chine tool industry could be summarised as follows:(a) Development of robust sensing and signal processing techniques, implementing monitoring and control techniquesproposed in the literature into usage requirements of real life applications (e.g. aggressive environment, fluids, noiseand chips), both for direct and indirect measurement techniques. Miniaturisation and embedding of sensors and actu-ators into machine tool components is an on going exciting research trend.(b) Development of reliable and process knowledge-based diagnosis with control strategies, so that systems could beautonomously self-adapted with zero set-up time for the end user, operating under a wide range of machining con-ditions and part requirements. As a result, without the need of skilled operators, flexible application of process auto-mation and optimisation systems will become possible under changing market requirements.(c) Adoption of OAC systems including integrated and co-ordinated open process controllers, towards the industrial stan-dardisation of machining process monitoring and control systems, enabling the integration of user-defined, flexible,self-learning and multipurpose supervisory systems.474S. Mekid et al./Mechanism and Machine Theory 44 (2009) 466476(d) Synergistic and co-ordinated research and development efforts between machine tool builders, control manufacturers,research institutions and machine end-users, avoiding resource overlapping, and enabling high-risk and long-termstudies for ground-breaking results.(e) Development of new adaptronics for modular machines with mechatronic aspect to ease reconfiguration of the nextgeneration of machine tools.Intelligent process control should address both workpiece quality (dimensional and material integrity with surface finishquality) and the related cost in terms of tooling and time. This can be best accomplished by using precise process models andsensory information in an open-architecture control environment. To achieve these objectives it is required to use preciseprocess models with compliant cluster sensors within an open architecture control environment. In addition, it is also re-quired to develop and integrate a variety of support technologies as mentioned previously.References1 H. Mizumoto, S. Arii, Y. Kami, M.Yabuya, A single-point diamond turning machine with micro cutting mechanism using active aerostatic guideway, in:MATADOR Conference, Manchester, 2004.2 W. Gao, Construction and testing of a nano-machining instrument, Precision Engineering 24 (2000) 320328.3 S. Liang, R. Hecker, R. Landers, Machining process monitoring and control: the state-of-the-art, Journal of Manufacturing Science and Engineering 126(2004) 297310.4 H.K. Tnshoff, T. Friemuth, J.C. Becker, Process monitoring in grinding, Annals of the CIRP 51 (2) (2002) 121. Keynote papers.5 H.K. Tnshoff, I. Inasaki, Sensors in manufacturing, Sensors Applications, vol. I, Wiley & Sons, 2001, ISBN 3-527-26538-4.6 S.E. Oraby, D.R. 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