FA Application PackageiQ Monozukuri Tool Wear Diagnosisfor Machine Tools

Global Player

e-F@ctory

iQ Monozukur i　2-3

e-F@ctory is a concept for a further step on "Monozukuri", which reduces the total cost for development, production, and maintenance, and continuously supports improvement activities of the customer by utilizing the FA technology and IT technology.

In the increasingly complex manufacturing sites, coordination between "Man" and "Machine" through the best use of information from the production site is a key concept.

Productivity and quality can be improved not only with the information obtained from the devices at the production site, but the improvement triggered by on-site notice and flexible human actions. Similarly, automatic adjustment of equipment based on the information recognized by human is indispensable for the promotion of automation.

We have realized the "Next-generation manufacturing" through the use of the "e-F@ctory" information proposed by Mitsubishi Electric, the effective and flexible manufacturing realized through the coordination between man and machine, and the optimization of the production site, and the entire supply chain and engineering chain.

Coordination between man and machine through the

use of information

Information

Machine Man

Many issues exist with the varying-type/varying-volume production of machine tools.

Feedback expressing concern from the shop floor includes “I focus so much on quality,

I do not know the appropriate the time of tool change,”

“I can’t prevent quality defects caused by sudden tool abnormalities,” and “It’s difficult

to collect data from a wide-variety of machine tools, and I don’t know how to analyze it.”

With this package, IoT data are collected and analyzed using Mitsubishi Electric’s

independent technology to optimize tool operation control and support

the easy detection of quality defects.

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Five Use Cases SolvingTool Wear Issues

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Use Case

1

Use Case

2

Use Case

3

Use Case

4

Use Case

5

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In the past, TBM (tool usage count) was the basis for tool change,however it became apparent that tools were being changed prior to lifeexpiration despite the potential to be used close to the maximum loadfor tool change results.

Machining count (tool usage count)

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Tool life time for eachmachining condition

Predicts the number of timesa tool can be used beforereaching the set thresholdbased on past data results.Estimates appropriate tool life.

Tool change every 50 uses

Difference indeterioration riseangle due to varyingtype/varying-volumeproduction

Machining count (tool usage count) Machining order

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We change tools based on tool usage time/count, but I am unsure of the appropriate tool change timing in the case ofvarying-type/varying-volume production.

Predict optimal tool change timing even in the case of varying-type/varying-volume production.Reduce tool change count as well as tool cost and labor!

Simultaneous collection of IoT machining data and machining conditions from machine tools to visualize changesin trends with identical machining conditions.

Reduction in Annual Tool Costs and Labor Requiredfor Tool Change Work By Reducing the Frequency of Tool Change

ConventionalAnnual tool cost2.33 mill yen/tool

1.38 mill/tool

New tool price Re-grinding price

Post-introduction

● Annual tool cost by tool optimal tool change (example)

1.29 mill yen (15,000 yen ×51 tools） 1.04 mill yen（6,000 yen ×102 tools）

612,000 yen（6，000 yen ×174 tools）

765,000 yen（15,000 yen × 86 tools）

Cut by950,000 yen

● Trends with regular tool change ● Trends when tools are replaced at usage limit (wear)

The optimal tool life in varying-type/varying-volume production was determinedand tool maintenance was improved by switching from TBM (tool usage count)to condition-based maintenance CBM (wear state). As a result, tool usage count increased by 170%!

Assume the same tool is used to machine Product A and Product B. When a high volume of Product A is being manufactured, there were no product defects when tool change was carried out as it had been until now. However, when the productionpercentage of new Product B was increased, product defects began occurring, therefore the operator had no choice but to revisethe setting for the regular tool change timing for a shorter period referring to the count when defects occurred.

Have you ever experienced this?

Conventional Post-introduction

1420

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4420

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4300

4240

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4120

4060

Machining order

Tool deterioration condition

Previous maximumdeterioration condition for the relevantmachining

Use Case

1

Quality defects occur due to sudden tool abnormalities or manufacturing abnormalities in the upstream process.

Immediately after machining, detects abnormalities by identifying things that “Differ to the norm!” based on change from machining feature value in normal times.　　

● Detection of tool breakage (example) ● Detection of machining abnormalities due to mold　deformation (example)

Machining orderMachining abnormality detection

Machining orderBlade breakage detection

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Capture changes with machining feature value during normal machining, to support extraction ofdiagnosis thresholds for judging abnormal machining.

Reducing Loss Cost by Preventing Leakage of Productswith Quality Defects Due to Machining Faults

Detects sudden increases in machining feature value causedby machining faults.

Detects sudden reductions in machining feature value causedby blade breakage.

Sudden tool defects create a large volume of defective products up until quality inspection. A large volume of defective products is produced due to mold deformation in the upstream process (casting).

Have you ever experienced this?

Detects signs ofmachining

abnormalities

Detects bladebreakage

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Use Case

2

I want to eliminate tool breakage detection (breakage detection) time, which is a waste of operating time.

● Average load/workload trend ● Occurring alarm

Detect tool breakage in real-time When a tool breakage is detected, an alarm messageis outputted and the signal tower *1 illuminates!*1: If external abnormality input terminal has been preparedon the machine tools

11/29 11:55:5611/29 11:55:56

Threshold

Program1

Program2

Program3

Program28

Program29

Program30

With breakage detection

Achievement of sensor-less tool breakage detection

Sensor-free tool breakage diagnosis Sensor-free tool breakage diagnosis

● Cycle time improvement with tool diagnosis (example)

・・・

By leveraging IoT machining data, cycle time was significantly improved!

Program1

Program2

Program3

Program3

Program3

Program3

・・・

Able to detect tool breakages using IoT machining data only, making sensor-less tool breakage possible.

Have you ever experienced this?

It takes breakage detection time for each machining, each affecting the cycle time.

Productivity Increase by 10% or Higher Due to ShorterBreakage Detection Time

Conventional

Post-introduction

Total machining time12 minutes

10 min 30 sec

Reduced by90 seconds

Use Case

3

Achieve better traceability based oncentrally-managed IoT machiningdata/Product serial number/machiningprogram (model type), and machiningstart/finish timing. Also enables simultaneous collection of datapertaining to machining, such as cutting oiltemperature and cuttingoil discharge pressure.

Quality values are out of spec but thereason is unknown.

Supporting the CNC communication protocolof various companies, it is possible to collectmachining data for up to 10 machines,covering all process from rough machiningto finishing.This enables standardized tool changeoperation across various machine tools!

For details on connectable CNC models, please contact your local branch or dealer.

Data collection is difficult as the productionline contains both new and old machinemodels by various machine toolsmanufacturers.

Machine tools

Mitsubishi CNC(old)

Company A’s CNC(old)

Company B’s CNC(old)

Company C’s CNC(old)

Mitsubishi CNC(new)

Protocolconverter

Protocolconverter

Company A’s CNC(new)

● Clarify abnormal machining by superimposing　waveform data of identical machining! 　(Identify cause of excessive cutting in　upstream process (rough machining))

・・・Normal・・・Abnormal

Rough machining Finishing Inspection

Machine toolsMachining dimensioninspection device

Diagnosisresults display

Datacollection/diagnosis

・IoT machining data・Product serial number・Machining program (model type)・Machining start/finish times GOT2000 MELSEC iQ-R

Centralized managementof machining data

Sending of collected data

GOT2000 MELSEC iQ-R

Supports the CNC communicationprotocol of various companies!

Connects with up to 10 machines!

Centralized Management of Machining DataContributing to Traceability

Capable of Connection with Various MachineTools – Both New and Old

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Can identify that “abnormality exists onupstream process”

Protocolconverter

Protocolconverter

Protocolconverter

Protocolconverter

Protocolconverter

Protocolconverter

Protocolconverter

Protocolconverter

Use Case

4Use Case

5

Wide-array of Analysis Technology LeveragingData to Achieve Reliable Tool Diagnosis

Automatic Detection of Machining Load

Real-time diagnosis of tools and machining quality in various machining types, such as rough machining and finishing. Various forms of analog and digital data are collected, and data relating to cutting load based on collection waveform is automatically extracted (data cleansing). Furthermore, machining feature value is automatically calculated from the extracted waveform, a statistical population (learning subject) for diagnosis is generated, and extraction of the diagnosis threshold not relying on experience is supported. High-accuracy diagnosis is achieved, as the adequacy of settings such as data collection conditions, can be confirmed using statistical methods.

Based on machining feature value (equivalent to cutting load) trends at time of tool change based on the conventional tool counter, it is possible to determine tool life by individual models with accumulated patterns on cutting performance by tool and wear deterioration. Through determining the tool l ife by individual model, the number of times the tool can be used until i t reaches l i fe can be predicted from post-tool change deterioration trends, making it possible to use the tool right up until the end of its life in line with wear status (CBM).

By making “models” from machining program number and tool number combinations, tool life can be diagnosed in relation to various machining conditions incorporated in the model, such as machined material, workpiece shape, spindle speed, cutting depth, and feed. As such, even if one type of tool is used for production under various machining conditions, tool life for individual models can be stipulated, and tool diagnosis in varying-type/varying-volume production is possible by predicting deterioration to suit the progress of tool wear.

Optimization of Tool Change Timing

Tool Load Pattern Learning

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Machining order［TBM（tool usage count）］

［CBM（wear status）］Machining order

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Machining order

Slow tool wearWear differsdepending on tool Fast tool wear

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Machining order Machining order

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・・・Identical tool usage time・・・Tool change

Continuous collection of machine tools data

11：23 11：37 11：39 11：53 15：55 16：09 16：11 16：25 （Time）

・・・Unnecessary data

Serial Amachining

Data cleansing Data cleansing Data cleansing Data cleansing

Serial Bmachining

Serial Cmachining

Serial Dmachining

Mach

ining

load

curre

nt

Toollife

Optimization ofusage time

Conventionalusage time

Machining abnormalities can beinstantly detectedby comparingdifferences betweenvarious data!

Extract only the currentmachining data excludingunnecessary data

Tool is replaced based on the number of times ithas been used, regardless of its condition, thereforethe height of the peaks varies → tool isn’t beingused until the end of its life

Diagnose optimal tool life to suit various tool wear!

Now possible to use tools untilthe end of their life

・・・Identical tool usage time・・・Tool change

Serial DSerial C

Serial BSerial A

Mach

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load

curre

nt MachiningFaults

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Diagnoses short-term changes of collected machining data

Statistically learns machining load/no-load based on past results from identical models for normal machining and air-cutting, and supports extraction of diagnosis threshold for determining abnormal machining. This makes it possible to detect things that differ to the norm, including changes in upstream processes (base treatment), equipment changes, machined materials (different workpiece), and output alarms.

By assessing tool and machining abnormalities based on short-term trends of the collected data feature value, then statistically analyzing long-term trends, it is possible to perform predictive diagnosis on machine tools. If abnormalities exist on the machine tools spindle or feed drive system, rotational control will become unstable, therefore the collected waveform would not stabilize, and there would be variance in feature value. As such, by finding the standard deviation for feature value by a set number of machining operations, and looking at deviation value change trends, it is possible to provide data which the user can assess to confirm which axis has the greatest variance.

Detection of Machining Quality Abnormalities

Machining Data Utilization

*1 If external abnormality input terminal has been prepared on the machine tools

Present tool life with the available usage count

Based on post- tool change di fferences in tool cutt ing performance and the status of varying-type/varying-volume production, displays predicted remaining count as available usage count to show how many more times a tool can perform machining until it reaches its life. Able to set abnormality output in the two stages of “caution” and “warning” based on predicted remaining count to enhance user-friendliness. If an abnormality occurs, an abnormality output can be sent externally also, enabling abnormality display on the machine tools, etc.*1

（times）

-σ 　μ　 σ-σ 　μ　 σ-σ　μ　σ

σ σ σ

Histogram forthe600 th workpiece Histogram for the 1200 th workpiece Histogram for the 1800 th workpiece

18001200600Deviation gradually increases due to mechanical “play”

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600

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Feat

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Machining order Machining order

Suddenload

increases

Suddenload

decreases

Workpiece mountingdefect and workpiece

quality defect

toolbreakage

Display tool life withpredicted remaining count! Manage each tool’s usage status in one list!

Learns “load upper/lower limit exceeded” based on past results of identical models

Spindle deterioration trend

・・・Identical tool usage time・・・Tool change

"Visualization, Analyzation, Optimization" that accurately graspsthe tool status and support efficient cycle time improvement.

Supports tool change operation where tools are used for full life

Visualization of machining data waveform collection, machine condition/diagnosis resultsVisualization

Analyzation

Optimization

Collect machining data of each machine tools in real-time for storage or comparison purposes. （compare differences between deteriorated toolsand new tools）

Swiftly confirm machining status of machine tools for diagnosis on a machine status screen.

Set tool change condition and confirm tool usage status for each machine.（notification of tool change timing using alarms）

Electronic conversion of diagnosis alarms and tool change history, as well as support of timely tool change operation.

Diagnosing tool status from changes in trend data

Predicts tool life from wear status and notifies user of the predicted remaining count for each tool

Automatically calculate feature value based on machining data and diagnose tool status from trend data.

Immediately detects tool abnormalities and prevents machining defects.

Automatically calculates each feature value using statistical analysis to enable display and diagnosis of trend data.

Predictedremaining

count display

Predictsdeterioration Detects

bladebreakage

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Improvement of cycle time and tool life through optimization of machining conditions

By comparing machining condition for the same tool between machining programs, optimizes machining conditions such as cutting speed, feed amount,cutting depth, etc. to support improvement of cycle time.

Optimal machining conditions can be confirmed by comparison of changes in time load is placed on tool.

Communication means with machine tools and data cleansing conditions can be set for each individual machine to enable accurate collection of machining condition data.

Set models (machining conditions combining tools and machining programs), and select feature value to be targeted by diagnosis.

Tool information can be set for each machine.

Threshold of feature value to be targeted by diagnosis can be set for each model.

Improvement

Various settings for various needsSettings

System Specifications

*1：Limitations exist depending on diagnosis conditions

PLC CPUHigh speed data logger moduleCC-Link IE Field Networkmaster/local module

HUBHUB for CC-Link IEField Network

Protocolconverter

Analog-digitalconverter module

Extension analog-digitalconverter module

RS-232C communication cable I/O module output cable

Alarmexternaloutput

Analog output cable

I/O moduleTo FTP server

① ② ③

①②③

GOT

Collectioninterface

Drive units（Servo/Inverter）

Remote I/O module（Machine tool contact I/O）

Control module※

（CNC）

System Configuration

※If connecting to another company’s CNC, please contact a Mitsubishi Electric branch.

Ethernet Analog output cableI/O module output cableCC-Link IE Field Network

RS-232C communication cable

Machinetools

Software

*1：Please contact a Mitsubishi Electric branch.*2：Necessary for the CNC machine individually.*3：As optional, when connecting with external I/O devices, please select unit type and quantity for I/O points to be used. *4：please select module type and quantity for I/O points to be used.

※Software used for startup.

Device

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Contents of Package

FA Application Package

Refer to the “License Key Appl icat ion Procedures” enclosed with the product.

Enter the “Product ID” enclosed with the product and the Ser ia l Number of the PLC you wi l l use.

This wi l l be emai led to you in approximately one business day.

From the “License Key Registrat ion” window in GOT, register l icense key.

The issued l icense key can only be used with the hardware belonging tothe ser ia l number entered at the t ime of appl icat ion. (Please note i t cannot be used with other hardware)

＊１：Maximum no. of connections supported by license

License Key Registration Process

Partner Products (protocol converter for CNC connection)

iQ Monozukur i　16-17

FANUC CNC compatible gateway for overseas Mitsubishi Electric CNC compatible gateway

● Instal l , wire up equipment ● Set device parameters (communicat ion means, data col lect ion condi t ions, etc.) , register diagnosis model● Conduct t r ia l operat ion check for data col lect ion preparat ion ● Data col lect ion to determine diagnosis threshold (data col lect ion including 5 to 10 tool exchanges: Approx. 1 month)

● Select the device, machining type, tool for d iagnosis● Determine system conf igurat ion, secure instal lat ion environment

● Conf i rm adequacy of set t ings f rom col lect ion data● Calculate diagnosis threshold f rom trend data ● Set calculat ion threshold

● Commence operat ion (check machine condi t ion) ● Tool wear diagnosis, tool breakage diagnosis● Tool change in l ine wi th diagnosis resul ts/alarms ● Revise thresholds● Opt imizat ion of machining programs using a cycle t ime improvement support funct ion

Pre-introduction Flow

e-F@ctory, iQ Monozukur i , MELSEC, MELSOFT, GOT, and CC-Link IE are t rademarksand/or registered trademarks of Mitsubishi Electr ic Corporat ion in Japan and overseas. Ethernet is the registered trademark of Fuj i Xerox Co., Ltd.The company names, system names, product names, etc. appear ing in th is document are general lytrademarks and/or registered trademarks of indiv idual companies.There are cases in th is document where t rademark symbols（™, ®）are not speci f ied.

Trademarks

iQ Monozukur i　18-19

Explanation of Terminology

L（NA）16071ENG-A 2003（IP）

HEAD OFFICE: TOKYO BLDG., 2-7-3, MARUNOUCHI, CHIYODA-KU, TOKYO 100-8310, JAPANwww.MitsubishiElectric.com

Sales officeCountry/Region Tel/FaxMITSUBISHI ELECTRIC AUTOMATION, INC.500 Corporate Woods Parkway, Vernon Hills, IL 60061, U.S.A.

USA Tel : +1-847-478-2100Fax : +1-847-478-2253

MITSUBISHI ELECTRIC DO BRASIL COMERCIO E SERVICOS LTDA.Avenida Adelino Cardana, 293, 21 andar, Bethaville, Barueri SP, Brasil

Brazil Tel : +55-11-4689-3000Fax : +55-11-4689-3016

MITSUBISHI ELECTRIC EUROPE B.V. German BranchMitsubishi-Electric-Platz 1, 40882 Ratingen, Germany

Germany Tel : +49-2102-486-0Fax : +49-2102-486-7780

MITSUBISHI ELECTRIC EUROPE B.V. UK BranchTravellers Lane, UK-Hatfield, Hertfordshire, AL10 8XB, U.K.

UK Tel : +44-1707-28-8780Fax : +44-1707-27-8695

MITSUBISHI ELECTRIC EUROPE B.V. Irish BranchWestgate Business Park, Ballymount, Dublin 24, Ireland

Ireland Tel : +353-1-4198800Fax : +353-1-4198890

MITSUBISHI ELECTRIC EUROPE B.V. Italian BranchCentro Direzionale Colleoni - Palazzo Sirio, Viale Colleoni 7, 20864 Agrate Brianza (MB), Italy

Italy Tel : +39-039-60531Fax : +39-039-6053-312

MITSUBISHI ELECTRIC EUROPE, B.V. Spanish BranchCarretera de Rubi, 76-80-Apdo. 420, E-08190 Sant Cugat del Valles (Barcelona), Spain

Spain Tel : +34-935-65-3131Fax : +34-935-89-1579

MITSUBISHI ELECTRIC EUROPE B.V. French Branch25, Boulevard des Bouvets, 92741 Nanterre Cedex, France

France Tel : +33-1-55-68-55-68Fax : +33-1-55-68-57-57

MITSUBISHI ELECTRIC EUROPE B.V. (Scandinavia)Hedvig Mollersgata 6, 223 55 Lund, Sweden

Sweden Tel : +46-8-625-10-00Fax : +46-46-39-70-18

MITSUBISHI ELECTRIC (RUSSIA) LLC St. Petersburg BranchPiskarevsky pr. 2, bld 2, lit “Sch”, BC “Benua”, office 720; 195027 St. Petersburg, Russia

Russia Tel : +7-812-633-3497Fax : +7-812-633-3499

MITSUBISHI ELECTRIC TURKEY A.S Umraniye BranchSerifali Mahallesi Nutuk Sokak No:5, TR-34775 Umraniye/Istanbul, Turkey

Turkey Tel : +90-216-526-3990Fax : +90-216-526-3995

MITSUBISHI ELECTRIC EUROPE B.V. Dubai BranchDubai Silicon Oasis, P.O.BOX 341241, Dubai, U.A.E.

UAE Tel : +971-4-3724716Fax : +971-4-3724721

ADROIT TECHNOLOGIES20 Waterford Office Park, 189 Witkoppen Road, Fourways, South Africa

South Africa Tel : +27-11-658-8100Fax : +27-11-658-8101

MITSUBISHI ELECTRIC AUTOMATION (CHINA) LTD.Mitsubishi Electric Automation Center, No.1386 Hongqiao Road, Shanghai, China

China Tel : +86-21-2322-3030Fax : +86-21-2322-3000

SETSUYO ENTERPRISE CO., LTD.6F, No.105, Wugong 3rd Road, Wugu District, New Taipei City 24889, Taiwan

Taiwan Tel : +886-2-2299-2499Fax : +886-2-2299-2509

MITSUBISHI ELECTRIC AUTOMATION KOREA CO., LTD.7F to 9F, Gangseo Hangang Xi-tower A, 401, Yangcheon-ro, Gangseo-Gu, Seoul 07528, Korea

Korea Tel : +82-2-3660-9569Fax : +82-2-3664-8372

MITSUBISHI ELECTRIC ASIA PTE. LTD.307 Alexandra Road, Mitsubishi Electric Building, Singapore 159943

Singapore Tel : +65-6473-2308Fax : +65-6476-7439

PT. MITSUBISHI ELECTRIC INDONESIAGedung Jaya 8th Floor, JL. MH. Thamrin No.12, Jakarta Pusat 10340, Indonesia

Indonesia Tel : +62-21-31926461Fax : +62-21-31923942

MITSUBISHI ELECTRIC INDIA PVT. LTD. Pune BranchEmerald House, EL-3, J Block, M.I.D.C., Bhosari, Pune-411026, Maharashtra, India

India Tel : +91-20-2710-2000Fax : +91-20-2710-2100

MITSUBISHI ELECTRIC AUSTRALIA PTY. LTD.348 Victoria Road, P.O. Box 11, Rydalmere, N.S.W 2116, Australia

Australia Tel : +61-2-9684-7777Fax : +61-2-9684-7245

MITSUBISHI ELECTRIC FACTORY AUTOMATION (THAILAND) CO., LTD.12th Floor, SV.City Building, Office Tower 1, No. 896/19 and 20 Rama 3 Road,Kwaeng Bangpongpang, Khet Yannawa, Bangkok 10120, Thailand

Thailand Tel : +66-2682-6522Fax : +66-2682-6020

MITSUBISHI ELECTRIC VIETNAM COMPANY LIMITEDUnit 01-04, 10th Floor, Vincom Center, 72 Le Thanh Ton Street, District 1, Ho Chi Minh City, Vietnam

Vietnam Tel : +84-28-3910-5945Fax : +84-28-3910-5947

MITSUBISHI ELECTRIC EUROPE B.V. Polish Branchul. Krakowska 48, 32-083 Balice, Poland

Poland Tel : +48-12-347-65-00

MITSUBISHI ELECTRIC EUROPE B.V. Czech Branch, Prague OfficePekarska 621/7, 155 00 Praha 5, Czech Republic

Czech Republic Tel : +420-255-719-200

MITSUBISHI ELECTRIC AUTOMATION, INC. Mexico BranchBoulevard Miguel de Cervantes Saavedra 301, Torre Norte Piso 5, Ampliacion Granada,Miguel Hidalgo, Ciudad de Mexico, Mexico, C.P.115200

Mexico Tel : +52-55-3067-7512

New publication, effective Mar. 2020.Specifications are subject to change without notice.

Mitsubishi Electric Corporation Nagoya Works is a factory certified for ISO 14001 (standards for environmental management systems) and ISO 9001 (standards for quality assurance management systems).