普通车床的数字化改造设计【用GSK980T数控系统】
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普通车床的数字化改造设计【用GSK980T数控系统】,普通,车床,数字化,改造,设计,GSK980T,数控系统
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Advanced CNC system with in-process feed-rate optimisationFirman Ridwana,b, Xun Xua,naDepartment of Mechanical Engineering, University of Auckland, Auckland 1142, New ZealandbFaculty of Mechanical Engineering, Andalas University, Padang, 17163, Indonesiaa r t i c l e i n f oArticle history:Received 8 December 2011Received in revised form31 March 2012Accepted 29 April 2012Available online 17 June 2012Keywords:Computer numerical control (CNC)STEP-NCFeed-rate optimisationMonitoringFuzzy controla b s t r a c tTight quality requirements and stringent customer demands are the main thrust behind the develop-ment of new generation machine tool controllers that are more universal, adaptable and interoperable.The development of some international standards such as STEP and STEP-NC presents a vision forintelligent CNC machining. Implementation of STEP-NC enabled Machine Condition Monitoring (MCM)is presented in this paper. The system allows optimisation during machining in order to shortenmachining time and increase product quality. In the system, an optiSTEP-NC, an AECopt controller and aKnowledge-Based Evaluation (KBE) module have been developed. The aim of the optiSTEP-NC system isto perform initial feed-rate optimisation based on STEP-NC data to assist process planners in assigningappropriate machining parameters. AECopt acts as a connector between the process planner andmachining environment with the intention to provide adaptive and automatic in-process machiningoptimisation. KBE based-MTConnect is responsible for obtaining machining know-how. Optimisation isperformed before, during or after machining operations, based on the data collected and monitoredsuch as machining vibration, acceleration and jerk, cutting power and feed-rate.& 2012 Elsevier Ltd. All rights reserved.1. IntroductionOver the years, computer numerical control (CNC) machinetools have been developed, with the ability to machine high-precision products. One of the technologies applied in support ofCNC development is by incorporating machine condition monitor-ing (MCM). In doing so, machine tools are supervised by means ofsensing elements, signal conditioning devices, signal processingalgorithms and signal interpretation. For real-time supervision of aCNC machine, various intelligent functions such as adaptivecontrol, re-generation of optimised data sets and advanced opti-misation models have been developed and implemented. In thisway, various machining process anomalies can be detected at anearly stage, assuring a safer machining environment.Utilisation of MCM for machine tools reduces the need forhuman intervention during machining and allowed automaticsupervision of the machine tool. However, challenges still exist incoping with frequent design revisions, stringent demand onproduct quality and shorter times to market. Moreover, machin-ing activities have been customer-centric rather than manufac-turer-driven. To enable active quality control during machining,machining parameters are best monitored and controlled, so thatmachine tool behaviour is analysed in time and appropriateactions taken in due course. The main concern of monitoringand control of on-going processes is to record relevant sensorydata so that machine tool characteristics can be understood andfed back for a real-time reaction. For example, under the machin-ing domain, maintaining optimal machining parameters to avoidover-loading of a spindle, excessive cutting force, chatter, toolwear and other constraints needs the proper combination ofappropriate machining parameters and on-going performance ofmachine tools. Understanding these characteristics demands atrade-off between precise empirical models and systematic con-trol of machine tools.To cope with this, MCM can be automated by integratingmonitoring technology with decision-making procedures. The aimis to produce self-adjusting intelligent systems that are capableof adapting to the ever-changing machining environment 1.In addition, as the technology grows, there are demands andnew prospects to empower current CNC with more advancedfeatures such as adaptability, agility, reconfigurability and inter-operability 2. In realising an agile and autonomous manufactur-ing environment, open CNC architecture is also envisaged 3.There are multiple impediments in realising this vision. First, inspite of great technological achievements, contemporary CNCprogrammes are still being executed based on a sequential setof NC programming language, aka G-codes. These codes weredeveloped more than 50 years ago with little, if any, intelligence.The initial design of the codes was to hold a set of low-level datathat are mostly step-by-step instructions to drive the earliestContents lists available at SciVerse ScienceDirectjournal homepage: /locate/rcimRobotics and Computer-Integrated Manufacturing0736-5845/$-see front matter & 2012 Elsevier Ltd. All rights reserved./10.1016/j.rcim.2012.04.008nCorresponding author. Tel.: 64 9 373 7599X84527, fax: 64 9 373 7479.E-mail address: x.xuauckland.ac.nz (X. Xu).Robotics and Computer-Integrated Manufacturing 29 (2013) 1220models of machine tools. Outdated yet still widely used, G-codesonly hold a subset of information, which becomes an obstacle toachieving a complete, intelligent and optimised machining envir-onment. For instance, although various work has been devoted toenhancing optimisation models, a range of features cannot beutilised and incorporated within the codes.Second, only limited control of the programme execution isallowed during machining, which makes it difficult to change theprogramme on the shop-floor. Last minute changes are notpermitted. The machining operations are fully dominated by thepredetermined NC codes and in most cases, the machine toolsare not able to change any cutting conditions and machiningsequences during machining operations. In addition, since it onlysupports one-way information flow from design to manufactur-ing, any drastic changes to the manufacturing process cannot bereadily preserved and directly fed back to the designer 4.Finally, information flow in G-codes was designed unidirec-tionally, i.e., from CAD to the shop-floor, and does not enablefeedback of know-how from the shop-floor to the designer 5.As a result, this conventional way of NC programming is considereda bottleneck for achieving an intelligent machining environment.The ISO TC 184/SC 1/WG7 envisions a gradual evolution fromISO 6983 to portable feature-based programming formally knownas ISO 14649. TC 184 is the technical committee for Industrialautomation systems and integration 6. Its scope is standardisa-tion in the field of industrial automation and integration con-cerningdiscretepartmanufacturing andencompassingtheapplication of multiple technologies, that is information systems,machines and equipment, and telecommunications. ISO 14649,also known as STEP-NC (Standard for the Exchange of Productdata for Numerical Control), provides an opportunity to overcomethe abovementioned obstacles especially in realising intelligentmachining operations. The main characteristic of STEP-NC is itshigh-level and object-oriented data structure. Unlike G-codewhere a part program is written to describe simple tool move-ments and functions, the STEP-NC interface is able to work withrich information such as manufacturing features, multiple opera-tions such as finishing and roughing processes, machine toolcapability, motor drive power, mechanical efficiency, machiningstrategy, cutting tool information and workpiece properties. SinceSTEP-NC data model describes rich information, quality knowl-edge and data can be utilised on the shop-floor, which enablesadvanced optimisation analysis to be conducted. Modifications onthe shop-floor are possible and machining know-how can bepreserved for designers and process planners, thus improving thecommunication link between design and manufacturing depart-ments. By providing a complete and structured data model, noinformation is lost. Post-processors for machine-specific adapta-tions of NC programs are no longer needed. In addition, this richinformation content results in higher flexibility enabling last-minute changes or the correction of technological values withinthe part program. This research has a focus on adaptive control forintelligent machining in a universal and interoperable manner.Adaptive execution of STEP-NC data and feed-rate optimisationhas been realised.2. STEP-NC enabled MCM frameworkG-codes deprive machining processes of much needed infor-mation such as workpiece characteristics, tool properties andoptimised cutting parameters that is often provided by experi-enced operators. The functional requirements of the developedSTEP-NC enabled MCM system include (i) an offline optimisationmodule, (ii) a data model in support of process optimisation, and(iii) process monitoring and control. These functional require-ments are explained below.?Offline optimisationpreliminary determination of optimummachining parameters.?To start off, it is necessary to assign appropriate machiningparameters for any machining operation. A tool for simulatingoptimum machining parameters can be used to determineoptimum machining parameters.?Data model in support of process optimisation.?Intelligent machining requires a comprehensive data model insupport of adaptive control and monitoring of in-processmachining as well as autonomous supervision of optimisedmachining operations. In this regard, STEP-NC data model isextendedtocaterfordatamodelingforon-machineoptimization.?Continuous monitoring and optimization of machining processes.Machining process involves complex interactions betweentool-workpiece motions, machining parameters and machine toolcapabilities. Continuously monitoring these activities is an impor-tant method in tracking any occurrence of machining abnorm-ality. The processed data can be fed to optimisation algorithm foradaptive control.3. Development of the systemThe system architecture has been developed to support anintelligent, interoperable, informative and innovative manufac-turing platform. Under the machining domain, it is widely knownthat over-loading of a spindle, excessive cutting force, chatter,tool wear and other constraints may lead to major problems suchas tool breakage, product quality deterioration and even worsemachine breakdown. As such, continuous monitoring of machinebehaviour, real-time optimisation and the systematic retention ofmachining knowledge were integrated, giving rise to a compre-hensive architecture called STEP-NC Enabled MCM framework(Fig. 1).The system supports three levels of information flow: high-level data for process planning, machine control data for control-ling the machine movements and knowledge data evaluation forsubsequent machining operations. These information flows takeMonitoring/Visualisation/Analysis Software(MTConnect Client)STEP-NC Based ControllerKBEFig. 1. STEP-NC enabled MCM system architecture.F. Ridwan, X. Xu / Robotics and Computer-Integrated Manufacturing 29 (2013) 122013place in three separate sub-systems: the optiSTEP-NC sub-system,AECopt controller and Knowledge-based evaluation sub-system.These sub-systems are discussed in the following sections.3.1. optiSTEP-NCThe aim of optiSTEP-NC is to perform initial feed-rate optimi-sation, assisting process planners to assign appropriate machiningparameters for producing an NC part program. It is based on twocriteria, minimum machining time and optimal surface quality.There are four tasks involved in developing optiSTEP-NC.3.1.1. Process planningThe aim of process planning is to enrich machining featuresrepresented in AP-224 with the necessary syntax information toform entities defined by ISO 14649. Such entities are thosecontaining additional generic information of machining para-meters, cutting tools and workplans. Furthermore, additionalinformation such as material properties and surface conditionrequirements can be used to support the desired final part. Theavailable information under this format will maintain its genericnature until the moment when a CAM system populates theprocess plan with native manufacturing information in order togenerate a specific or native process plan 2,7,. Development of the off-line optimiserTheOptimisationmoduleisresponsibleforoptimisingmachiningparameters,inparticularfeed-ratesforspecificmachining features, which are calculated based on the informa-tion about machine tool capability and etc. In this module, cuttingpower obtained from a cutting force is simulated to obtainappropriate cutting parameters such as feed-rate, spindle speedand depth of cut. This module can also use the cutting forceinformation from the KBE to calculate the machining parameters.Both time-critical (TC) and quality-critical (QC) optimisationalgorithms have been developed, corresponding to the criteria ofminimum machining time and optimal surface quality, respec-tively. TC machining operations are often for roughing purposeswhereby increasing the material removal rate is one of the maingoals with cutting power as the main constraint 9. On the otherhand, QC machining operations are often used for finishingpurposes where surface quality is of the main concern.In developing the optimisation algorithm, fuzzy logic is uti-lised to process imprecise data. The output is the optimisedmachining parameters for achieving either time-critical or qual-ity-critical goals. The optimisation results are presented in agraphical user interface. The simulator was developed usingLabWindows/CVI(CforVisualInstrument)softwareunderNational Instrument (Fig. 2). In order to validate the systemperformance and algorithms, a test case is performed to showthe behaviour of machining parameters. In order to simulate thecutting force fluctuation as in a real situation, a random noise of acertain range is added to the theoretical cutting forces and asurface roughness predictive model has also been developed.Apparently, the cutting force values obtained from actual machin-ing can also be used as an input to the simulator. This can be doneto verify the actual value of cutting force during machining. Thegoverning equations of the parameters are incorporated in devel-oping optiSTEP-NC.The interface has four panes and a plot area. The input datapane contains information about the process such as differenttypes of milling operations, properties of the workpiece and toolmaterial, flute number, mechanical efficiency and chip-load. Theuser has the option to set the required value for these data. Inorder to calculate the power and cutting force, information suchas allowable depth of cut based on machining capability and themain machine power are pre-set. The machine tool data panedisplays information about machine tool capabilities such asmachine motor power and maximum depth of cut. This pane alsoprovides two switches, ON/OFF and TC/QC. The TC Propertiespane for example shows the predicted power consumption,predicted cutting force, current feed per tooth, current feed-rateand material removal rate. It also includes the power limitwarning indicating the safe limit and over limits of powerconsumption.Plots are shown for feed-rate, cutting force and materialremoval rate, all on the time domain. This is done by calculatingthe input data of mechanical efficiency, different types of millingprocess, tool material, workpiece material, tool geometry, max-imum feed per tooth depth of cut and machine power. The resultfrom the calculation gives an optimised feed-rate that changesaccording to the cutting force. For example, if the calculatedcutting power is larger than the machine power, the feed will bereduced until the calculated cutting power reaches an allowablevalue, i.e., less than the machine power. In doing this, excessiveFig. 2. optiSTEP-NC simulator.F. Ridwan, X. Xu / Robotics and Computer-Integrated Manufacturing 29 (2013) 122014cutting forces can be avoided. The QC Properties pane has twomodes, i.e., feed calculation (Feed Calc) and surface roughnesscalculation (Ra Calc). The Feed Calc option is used to determinethe optimised value of feed-rate depending on the given rough-ness values (N1 to N12) . Development of interpreterThis interpreter (as shown in Fig. 3) converts STEP-NC datainto machining commands. The STEP-NC data is defined by Parts10, 11 and 111 of ISO 14649, as well as the newly developedoptimisation data model. This newly developed data structureserves as an interface between STEP-NC data and the actualmachining optimisation process. The previous interpreter wascapable of translating basic milling functions 11. Therefore, anadditional function is needed in handling the optimisation datafor machine execution.The interpreter has three main data functions: input file (*.stp),tool file name (*.tlt) and error file (*.txt). Once processing starts,the object-oriented data of a STEP file is translated into a group ofmachining features and workingsteps for execution in the form ofCanonical Machining Command (CMC)12,13. This CMC outputhas been further enhanced to allow in-process optimisation to becarried during machining.3.1.4. Tool-path interpretation for machining executionA set of CMC codes is executed by the CNC controller namedAECopt. In this way, the link between process planner, optimisa-tion strategy and machine tool capability is integrated.3.2. AECoptThe machine tool controller has been re-designed to supportprocess optimisation, continuous monitoring and control. Thisresearch demonstrates how CMC is utilised to enable adaptiveexecution of STEP-NC data. The system to realise this is calledAECopt. AECopt is essentially an open and adaptive CNC systemthat provides three functions: (i) understanding of machine toolbehaviour and capabilities through MCM, (ii) adaptive control ofoptimised machine parameters and (iii) execution of a CMC partprogram. A Fuzzy-Inference System (FIS) was developed andintegrated into the CMC part program. Fig. 4 shows the data flowof the feed-rate optimisation process. An optimal feed-rate isdefined as a feed-rate for a short period of machining time thatdoes not exceed the milling machines rated maximum power anddoes not cause excess vibration. Typically, each machine tool hasits own maximum power rating. This can be used as a baseline forsettingthemachinetoolcapabilityslimit.Byconsideringmachine tools nominal power, operating cutting power is keptbelow the main motor power in order to maintain a safety zoneduring the machining operation. In this way, problems such asspindle over-loading, excessive cutting force, chatter, tool wear,product quality deterioration and even machine tool breakage canbe avoided.To achieve an optimal feed-rate, the reference cutting power(Nref) is set to a value just below the maximum power (Nmax), withconsideration given to possible overshoot of cutting power abovethe reference cutting power. The optimisation procedure is brieflyexplained as follows, making use of the corresponding numbers inFig. 4. The roughing process starts with a maximum depth of cut.Feed-rate optimisation begins with an initial maximum allowablefeed-rate value obtained from previously calculated data. Thevalue is assigned to SET_FEED_RATE commandA. The aim is toachieve a shorter machining time. During machining, the toolmay require linear or circular interpolations. This is achievedusing the STRAIGHT_FEED, ARC_FEED and ELLIPSE_FEED com-mandsB. The cutting force sensor detects cutting forces based onwhich cutting power is calculated. Using motor power as thereference, the cutting power error (ENc) and cutting power change(CNc) are obtainedC. Mathematically, the two errors are expressedas:ENci Ncref?Ncni1CNi Ncni?Ncni?12These two errors are used as input for fuzzy control. The FuzzyInference System consists of a basic fuzzifier of inputs, a fuzzyinference engine, a fuzzy rule base, membership functions and adefuzzifierD. The control signal is the feed-rate. Fuzzy rules areused to optimise the feed-rate assigned to the axis actuatorsE.For roughing operations, the feed-rate optimisation expression isdescribed by Eqs. (3) and (4).fopts1 Maxfzf Z8rtRa1=2,amax,xt3where x(t)(Nm,n,ks,Vc,t). Nmis the main drive motor power (kW),fopts1the optimum feed-rate (mm/min), Rathe arithmetic surfaceroughness (mm), amaxthe maximum depth of cut(mm), rtthe toolnose radius (mm)topts1 Mintmfopts1,amax,dsi?4where, topts1the optimum machining time (min), dsithe differenttypes of face-milling where i1, 2, and 3. Thus, ds1is defined asfull immersion milling type, ds2is unidirectional immersion type,and ds3is bilateral immersion type.In the case of finishing operations, feed-rate optimisation isexpressed by Eq. (5). In this case, the system switches to normalCMCs.fopts2 Minfzf r8rtRa1=2,amin5wherefopts2is the Optimum feed-rate (mm/min)This algorithm is implemented for every tool movement alongthe X, Y and Z axis. This procedure applies to all machine functionsthat contain the FEED command, such as ARC_FEED and ELLIP-SE_FEED. This results in tool movement with optimised feed-ratesvarying in smooth transitions, which is not possible with G-codebased execution. For finishing operations, feed-rate is optimisedin order to achieve the required surface quality.The program utilises data acquisition cards to convert voltageinput and output control signals into values that are interpretableby a computer and vice versa. The National Instruments Compu-ter (PXI-1031) is used as it has on-board data acquisition (DAQ)cards and an available software development programmingenvironment such as LabWindows/CVI 9.0. LabWindows/CVIprovides data acquisition libraries that contain functions forsignal reading and transmitting. The machine tool used is theFig. 3. ISO 14649 interpreter.F. Ridwan, X. Xu / Robotics and Computer-Integrated Manufacturing 29 (2013) 122015Sherline 2010 CNC milling machine. The interface of the AECoptcontroller system is shown in Fig. 5.The interface provides two types of controls: Manual and (Auto)Control. The Manual functions provide Feed Override for X, Y, and Zaxis, Speed Override for clockwise (CW) and counter clockwise (CCW)rotations, Spindle On and Coolant. The Control functions provideLOAD, RUN and LINE RUN options. The LOAD option loads a CMCprogram that has been interpreted from a STEP-NC file. The RUNoption executes the CMC file, with command line displayed. Finally,LINE RUN provides an option for displaying the CMCs output for aspecific command chosen by the user. A group of visual displays isutilised by both control functions. The START/STOP button is used toexecute optiCMCs and CMC, respectively. The START option is alsoused to start acquiring data from cutting force, which is used as theinput for optiCMC. At the same time, an accelerometer sensor signalis acquired for offline data analysis.Fig. 4. Fuzzy logic based feed-rate optimisation algorithm.F. Ridwan, X. Xu / Robotics and Computer-Integrated Manufacturing 29 (2013) 1220163.3. Knowledge-based evaluationProvisionofoptimal andupdatedparametersbasedonmachine conditions is the key to an efficient and productivemachining performance. One way of achieving this is to empowerthe controller with intelligent knowledge throughout the productdevelopment process. This is achieved through the KnowledgeBased Evaluation system that records and evaluates updated datainformation on the shop-floor. This can be done through directrecording or networked recording using protocols such as MTCon-nect. The direct recording approach during machining is a simpledata-saving method. The networked recording needs an openarchitecture of network protocols. The recording process mayinclude machining parameters such as actual feed-rate, accelera-tion, jerk, machining time, actual cutting force and vibration,which are then evaluated to make sure that the allowable cuttingpower of the machine tool is not exceeded. This information isused for updating the data in the STEP-NC data model. The lastaction in the system is to record the actual feed-rate for knowl-edge-based evaluation.The recorded information is then evaluated in order to updatethe STEP file with the up-to-date characteristics of the machinecondition. Thus, adjustment of machining parameters can bemade at a later time.3.3.1. MTConnectIntegration of STEP-NC with MTConnect enables an interoper-able approach for accessing and handling machining data acrossdifferent locations. MTConnect is an open protocol and XML-based standard for data integration which can act as an enablerfor higher level standards 14. Its architecture can be easilydeployed and retrofitted to the existing machines, hence provid-ing flexibility and portability functions for various types ofmachining environments.MTConnect has four components: Device, Adapter, Agent andClient; they collectively act as the backbone of the communica-tion standard. The device is referred to components such ascontroller, sensors and machine tool that are responsible forproviding the monitored data. These data are acquired by dataacquisition system and gathered by an Adapter. The Adapter isresponsible for communicating and streaming it to the Agent in astandard format. The data acquisition process acts as the devicesApplication Programming Interface (API), with which the Adapterwould communicate. The Agent then accepts the data requestsfrom a Client application, which then returns the data in XMLformat. The client can then extract the data from the documentand display it to the user. These data can be evaluated for moremeaningful output by taking the current condition of the machinetool.3.3.2. Data acquisition and analysisSince STEP-NC provides a rich data modelling method fordescribing machining data, compared with a conventional NCcode structure, the machining know-how under the STEP-NCsystem can thus be preserved for the entire product developmentcycle. STEP-NC is a high-level data model and its execution alsorequires more specific machining data.The KBE system is responsible for three tasks: data recording,visualisation and evaluation. First, the data streamed throughMTConnect is recorded in a database which can be accessed at1. Adaptive and Manual Switch button2. Feed & Speed Overrides Knob button3. Manual Milling Machine Axes Control4. Spindle On button5. Coolant button6. CMC file Display7. LOAD, RUN and LINE RUN Buttons for CMC file8. Current workpiece X, Y, Z position coordinate display9. Vibration in Time and Frequency Domain Display Plot10. Cutting Force Display Plot11. 3D Simulation Window12. Emergency Stop button13. START/STOP button14. Quit button1011121314123456789Fig. 5. AECopt controller GUI.F. Ridwan, X. Xu / Robotics and Computer-Integrated Manufacturing 29 (2013) 122017different locations. The dynamic machining parameters that arerecorded include actual feed-rate, acceleration, jerk, cuttingpower and maximum vibration amplitude. Second, the systemprovides a user interface for visualisation purposes. The interfaceconsists of a tree-view, table and graphical representation of theacquired dynamic machining parameters. The snapshot of theuser interface is shown in Fig. 6. Third, machining parameters areevaluated with the aim of obtaining another set of optimumparameters for subsequent machining operations. These include:(1) real cutting power values used to calculate optimum feed-rates,(2) acceleration and jerk values that are evaluated to obtainsmooth motion,(3) chatteranalysisobtainedbyobservingvibrationsignalthrough the Short Time Fourier Transform (STFT) to avoidexcessive chatter during cutting.All of these evaluated parameters help provide appropriatefeed-rates for safer machining operations. These feed-rates arethen assigned for updating the STEP-NC data stored in a STEP-NCfile. In this way, the knowledge can be utilised in performingsuperior machining operations.3.3.3. Data evaluationThe data streamed via MTConnect is continuously recordedinto a know-how database. A portion of the recorded data isshown in Table 1. It can be seen in the table that for everyincrementoftime,changesofmachinebehaviourcanbeobserved. Clearly visible is the gradual change of feed-rates forevery single increment of time. The dynamic behaviour of thesefeed-rates can be further differentiated to obtain acceleration andjerk. During machining, excitations of vibrations in machineelements can result from excessive jerk, which can lead toaccelerated tool wear, increasing machining noise and largecontouring errors 15. Thus, jerk values can act as an indicatorfor smooth machining operation.The data from the time domain needs to be recorded sepa-rately, due to the large amount of time domain data (at asampling rate of 10,000 Hz). The time domain vibration signal isfurther processed using the STFT technique. Fig. 7 is an exampleof the STFT view obtained from part of the recorded data at aninterval of 8 s. STFT can perform the frequency variation over thetime duration. From this variation, any significant chatter can bedetected, which will determine the feed-rate value at that time.For example, significant amplitude at chatter frequency of185.5 Hz occurred at 3.8 s. The recorded data show that thecontroller generated a feed-rate of 127 mm/min at around 3.8 sof machining. As a result, the feed-rate of 127 mm/min can berecognised as over-speed of the machine tool table movement. Itshould be avoided for subsequent machining operations byFig. 6. Interface of the KBE system.Table 1Recorded data via MTConnect.TCPFRAJMVA6.1940.06194.285?0.934?1.8442920.0206.2950.05991.443?0.4690.4653973.3096.3560.06284.417?1.920?1.4513254.8246.4970.05870.085?1.6940.2263086.4136.5440.05454.155?5.649?3.9555063.8366.6530.05741.827?1.8853.7642966.8436.7470.05534.188?1.3540.5312470.1526.8560.05332.203?0.3031.0513287.1386.950.05844.1342.1152.4192956.0067.0440.05656.6342.2160.1013369.8957.1530.05458.5950.300?1.9164043.4777.2470.05855.622?0.527?0.8273091.0487.3560.05550.522?0.780?0.2534358.8997.5440.05637.438?1.0730.1744047.1137.6530.05749.9381.9112.9844594.567TTime (s).CPCutting power (kW).FRFeed-rate (mm/min).AAcceleration (mm/sec2).JJerk (mm/sec3).MVAMax vibration amplitude (1000?1).F. Ridwan, X. Xu / Robotics and Computer-Integrated Manufacturing 29 (2013) 122018updating the STEP file. This real feed-rate value can be controlled,to not exceed the value of the allowable amplitude of chatterfrequency, by setting the upper limit of feed-rate in the tuningsystem. Hence, the improved feed-rate can be assigned to thecontroller.4. ConclusionsUse of the STEP-NC data model provides a promising platformfor various applications consolidated under the same data struc-ture. It brings design data such as geometry, tolerances andmaterials into process control and monitoring of machiningoperations, allowing a robust control mechanism. Motivated bythis benefit, the newly developed EXPRESS schema for optimisa-tion purposes augments the existing STEP-NC data models. This isnecessary for an integrated environment in which high-levelmachine condition monitoring can be exercised for optimisingmachining processes. The developed EXPRESS data model pro-vides the necessary data for machining optimisation.The STEP-NC enabled machine condition monitoring systemconsists of three sub-systems. The first subsystem, optiSTEP-NC,is responsible of early phase optimisation. The purpose is to assistprocess planners in generating optimum machining parametersfor a STEP-NC file. This is carried out for two different scenarios:(a) maximizing feed-rate and depth of cut for time-criticalmachiningoperations(e.g.,roughingoperations)and(b) maximizing machining quality for quality-critical machiningoperations (e.g., finishing operations). A simulator has beendeveloped to verify the optimisation algorithms, the real-timeprocess control and the monitoring algorithm.An adaptive execution of a CMC program with feed-rateoptimisation (AECopt) controller is the second sub-system ofthe framework. The controller allows canonical machine com-mands to be executed with a fuzzy feed-rate optimisationmodule. The key feature of the proposed NC program executoris the ability to perform adaptive feed-rate optimisation bykeeping a constant load within machine tools capability. Further-more, the optimisation algorithm can also help reduce chatteramplitude. Hence, occurrence of excessive chatter can be avoided.This leads to a much healthier machining operation environment.The experimental results approved the effectiveness of theproposed feed-rate optimisation module.The third subsystem (known as a knowledge-based evaluationsystem) was developed. Accurate, informative and updated machin-ing know-how is utilised for achieving automated and intelligentmachining operations. By effectively monitoring and recordingmachining processes in the standardized environment of STEP-NCand MTConnect, a complete utilization of machining know-how canbe applied at any point in time. The KBE system demonstrated thatvaluable machining know-how helps identify optimal feed-rates sothat the onset of chatter
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