소프트웨어 기술을 융합한 금형가공용 스마트머신 -...

한국정밀공학회지 제 35권 제 2호 pp. 121-128 February 2018 / 121

J. Korean Soc. Precis. Eng., Vol. 35, No. 2, pp. 121-128 https://doi.org/10.7736/KSPE.2018.35.2.121

ISSN 1225-9071 (Print) / 2287-8769 (Online)

• 특집 • 공작기계의 스마트화 기술

소프트웨어 기술을 융합한 금형가공용 스마트머신 개발

Software Technology Integrated Smart Machine Tool Development forMold Machining

박대유1, 엄규용1, 조현용2, 김두진2, 박재근3, 김수진4,#

De-Yu Park1, Kyu-Yeong Yum1, Hyun-Yeong Cho2, Du-Jin Kim2, Jae-Keun Park3, and Su-Jin Kim4,#

1 ㈜화천기공 기술연구소 (Research Center, Hwachoen Machinery Co., Ltd.)

2 ㈜엔씨비 기술연구소 (Research Center, NCB Co., Ltd.)

3 나이스솔루션 (Nice Solution Co., Ltd.)

4 경상대학교 기계항공공학부 (School of Mechanical and Aerospace Engineering, Gyeongsang National University)

# Corresponding Author / E-mail: [email protected], TEL: +82-55-772-1636

KEYWORDS: Computer aided manufacturing (CAD/CAM), Machining simulation (가공 시뮬레이션), Mold machining (금형 가공),

Smart machine tools (스마트 장비), Process planning (공정 설계), Graphite electrode (흑연 전극)

The mold manufacturing is one batch production that the same process does not repeat. The digital model in software is

processed with a real mold fabricated in high performance without error. In this study process planning, and machining

simulation software are integrated with a smart machine tool for the mold industry. It reduces the operational complexity to

four button clicks after dragging and dropping of 3d model data to fabricate multiple-numbers of graphite electrodes. The

smart machine tool fabricated 27 graphite electrodes with minimum interference of humans in 35 hours.

Manuscript received: November 24, 2017 / Revised: January 18, 2018 / Accepted: January 22, 2018

1. Introduction

Die and mold is a special tool used for the mass production of

same parts repeatedly. Mold manufacturing includes just about all

aspects of manufacturing: part design, mold design, process

planning, prototype production, advanced mechanical electrical

machining methods, and quality control.1 The mold machining is

single batch production that the same process does not repeated

again. The machine tools for mold industry should be smart

enough to fabricate the part of first and last in high performance

without error.

Experts with different skills are working for each of the mold

design, process planning, tool path generation, machine tool

operation and tool management. The separated process in which

the operator manually determines the machining process, tool and

machining pattern produce a long period of time and different

quality depending on their personal skill. The separated process

steps and interference of human are the reasons of fabrication

errors and process delays.

Therefore, there is a need for more researches on CNC machine

tools having an automatic machining function capable of

improving the quality of production process by minimizing the

frequency of manual selection and its effects on machining time.

A lot of process planning, tool path generation, machining

simulation, computer numerical control, and process control have

been researched separately or coupled. The process planning

system coupled with machining simulation was proposed consists

of geometry feature recognition, cutting mode and tool selection,

Copyright © The Korean Society for Precision Engineering

This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/

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122 / February 2018 한국정밀공학회지 제 35권 제 2호

toolpath generation.2 The virtual machining process simulated

cutting mechanics along tool path and optimized NC data by

respecting the physical limits of the machine tool and cutting

operation.3 In order to enable process monitoring for single batch

production without a learning phase, a simulation based approach

should be researched for generating reference data to set process

limits.4 The tool wear and breakage monitoring for single

production of mold was possible based on the machining

simulation.5

Some researchers are trying to integrate computer aided

machining and simulation technology into machine tools. The

procedures to cut letters and patterns using the four-axis lettering

machine were implemented using a personal computer numerical

control system.6 Commercial CAD/CAM software was installed in

open architecture motion controller.7

A large number of EDM (Electric discharge machining)

electrodes are used in plastic injection mold manufacturing. Each

electrode, holder and working coordinate system are designed in

electrode boundaries identified by sharp corner uncut which can be

detected by calculating the surface angles at their common edges.8

Graphite has good thermal conductivity and machinability, is a

widely used tool in EDM electrode materials. Graphite machinability

tests were carried out, followed by an analysis of tool wear and

surface quality generated in down- and up-milling.9 The feed rate is

the most important machining factors affecting on the groove

width precision and the surface roughness average for the end-

milling of high-purity graphite under dry machining conditions.10

During the machining multiple graphite electrodes on a machine

table, a lot of human mistakes occur during stock positioning, work

coordinate setting, NC data handling, and tool setting. But, there is

no research on solving these problems with intelligent machining

process or machine tool.

In this research a smart machine tool for electrode machining in

mold industry is introduced. The process planning, tool path

generation, machining simulation, automatic graphite stock setting,

machining and tool management are integrated in windows

operation system of the open architecture controller of the machine

tool. When 3d models input in a CNC controller, the machining

sequence and tool are automatically selected and the tool path is

created. Afterward the workpiece will be machined based on the

data checked in machining simulation. During machining, the tool

length and spindle current are measured and the correction is made

when the value exceeds the control limit. Multiple numbers of 3d

models dragged and drooped form network folder to smart

machine tool are fabricated automatically to graphite electrodes

without interrupt of operators. The research did not stop at the

laboratory level experiment but commercialized to smart machine

tool in mold industry.

Three companies with a large share of the Korean market in

machine tool, simulation software and process planning for mold

processing started to develop smart machines that combined

equipment and software technology in 2010. The first smart

machine tool named Smart-UaX for graphite electrode machining

processing was launched in 2012 Seoul international machine tool

show. The machining center automatically fabricated dozens of

graphite electrodes together without interference of person after

input 3d models. It has been successfully sold into the market even

at the twice price of the general machining center. However, due to

the used of foreign commercial CNC controller and CAM

software, the problem of technology dependency still remain.

2. Software and Machine Tool for Mold Industry

A smart machine tool was developed using the software that the

authors have developed and used in the mold industry. The first

software is the machining process planning software N-CASS, the

second is the NC machining simulation and optimization software

NCBrain, and the third is the interface software running inside the

CNC controller.

2.1 CAPP and CAM

NC data are produced by a high-level technician manually

specifying the area, method, tool, and condition suitable for the 3d

model, so that there is a large difference in productivity and quality

depending on the person. It is necessary for CAPP (Computer aided

process planning) software to make the machining process. The

feature-based, knowledge-based, STEP-compliant, generic algorithm,

and neural network methods had been used in the majority of

computer aided process planning researches during the 2002-2013

period.11 The feature-based method extracts algorithmically

manufacturing features from 3d model.2,12,13

The feature recognition and knowledge based process planning

for automatic tool path generation system named N-CASS was

developed and had been used in the mold industry.14 The process

planning software controls existing functionality or customized

routines of commercial CAM software by applying OLE (object

linking and embedding) library with the Visual Basic programming

language. The system analyzes the 3d model and automatically

selects the appropriate process and generates the NC data, which

eliminates the difference caused by the skill of the person.

2.2 Simulation and Optimization

Stable and economic tool path is important in die and mold

한국정밀공학회지 제 35권 제 2호 February 2018 / 123

manufacturing because the first machining is the final opportunity

to increase productivity. NCBrain is a machining simulation and

optimization software stabilizes tool path and controls cutting

condition, liking the practical condition data proved in die and

mold industry.15 The geometric model, used to simulate material

removal process, is z-buffer which is the simplest and fastest

approach.3 The feed rate is regulated to control the instantaneous

maximum cutting forces computed by specific cutting energy and

the intersection of tool and workpiece.16-21 The simulation software

has been used by thousands die and mold manufacturing

companies to stabilize tool path and improve productivity.

2.3 Machine Tools for Mold

Machining is the main process of mold manufacturing and the

machine tool maker Hwachoen has the large customers in mold

industry.22 The process planning and machining simulation

companies suggested the machine tool maker to integrate their

software technology in the machine tool to make smart machine.

The developed process planning and machining simulation are

able to be installed in the Windows operating system of Fanuc 30i

CNC. The HMI (Human machine interface) is a dedicated personal

computer to easily customize into smart CNC.

3. Integration into a Smart Machine Tool

The commercial process planning and machining simulation

software developed by the authors of this paper were integrated

into the CNC controller to simplify the mold machining process.

The stock positioning method of several parts and HMI integrating

upper software is newly developed in this research.

3.1 Process Flow and HMI

The smart machine tool is consisting of workpiece setting,

process planning, tool path generation, machining simulation, real

machining, and process control as shown in Fig. 1. When the

power of the machine tool is turned on, the machining unit and the

delegating unit are ready, and the HMI, which is stored in the basic

database of the control unit, is executed and displayed on the

display unit of the interface apparatus.

The HMI inputs 3d models and positions stocks. When several

3d models are input, HMI shows the layout to place stocks on the

table and minimize the movement of tools. The N-CASS and

CAM generate tool path by analyzing the input modeling data and

automatically selecting the process of machining the workpiece

and the tool to be used from the database stored in the control

device. The NCBrain verifies and optimizes tool path. The

automatically generated tool path is verified by machining

simulation to eliminate the error and optimize it to the machining

condition database.

The CNC machine automatically measures the size and

coordinates of the workpiece and then the real machining

processes is started. It minimizes the manual selection frequency

and the quality error of the workpiece during the machining

process. The tool wear monitoring system measures tool length

before and after machining. If a tool breakage error detected during

the machining process, it would be replaced with same size one in

the automatic tool changer and the machining continues without

stopping.

3.2 Stock Positioning

Small workpieces such as electrodes are processed together by

placing several pieces on one table. There was a novel two-

dimensional nesting strategy suitable for sheet metal industries

employing laser cutting and profile blanking processes.23 But it is

different to the nesting that should be considered height and

interference in machining process.

In this research, stock positioning software is developed to place

many workpieces on single table. When several 3d models are

input, it analyzes the bounding box of each model to select a

suitable size of the workpiece, and shows the layout to place many

stocks on single table.

Fig. 1 Process flow chart of smart machine tool


It places the workpieces on a grid-divided table according to the

stock size and the radius of the holder as shown in Fig. 2. The

material is arranged on the grid of the table from wide to small and

from high to low. The spacing of the workpieces should be at least

the distance between the holder radius and the tool radius as

written in Eq. (1), so that interference between neighboring

workpieces and tool does not occur during machining.

sw > rh + rt (1)

sw : space of workpieces

rh : holder radius

rt : tool radius

If the height difference between two neighboring workpieces is

larger than the space, the distance gap of them is enlarged as Eq.

(2).

sw > Δz (2)

Δz: height difference of workpieces

The completed batch status is displayed on the HMI as shown in

Fig. 2. An operator places the real stocks on a table based on the

stock position displayed on HMI. The OMM (On machine

measuring) measures the stock position and sets the working

coordinates in the memory of the CNC automatically. An alarm

message will be displayed when the measured size and position of

stock is different to the input model.

3.3 Process Planning and Tool Path Generation

The computer aided process planning is required for smart

machining. In this research the feature recognition and knowledge-

based methods were used for machining process planning.24 The

feature recognition step analyzes the 3d model to detect the size

and the special geometry. The features are used to select

automatically the machining pattern, cutting conditions and the

required tools prepared in the knowledge database. The recognized

features are the upper geometry, thickness of rib, the width of the

groove, concave fillet radius, and lower setting box.

The upper free geometry is finished with the ball end mill and

the lower setting box is finished with a flat end mill after the

roughing process. The diameter of the tool is selected from the size

of the bounding box, the width of the groove shape, and the

concave fillet radius as expressed in Eq. (3). The general condition

used to select the tool diameter is the volume and height of the

bounding box. The residual finishing and grooving tool diameter is

smaller than the width of the groove features.

dt = fk (vh, wg, rf) (3)

dt : Tool diameter

vh : Volume times height of bounding box

wg : Grove width

rf : Concave fillet radius

Fig. 3 and Table 1 show the machining process planning and

tool suggestion examples in case of (a) groove and (b) rib

Fig. 2 Automatic generation of initial stock position on HMI

Fig. 3 Process planning of N-CASS

Table 1 Process planning and tools for (a) groove and (b) rib

Process (a) Tool D(mm) Process (b) Tool D(mm)

Roughing Round D8 Roughing Round D10

Re-Rough Round D3 Re-Rough Ball D4

Finish Ball D3 Finish Ball D4

Re-Finish Ball D1 - -

Groove Flat D1 - -

Set box Flat D8 Set box Flat D8


geometry. The basic machining process is the constant z-level

roughing and finishing of the upper geometry, and the flat end

milling of the lower setting box. The roughing, re-roughing and

finishing tool diameters of (b) are bigger than (a) because the

geometry is higher.

The thickness of the rib is calculated as the distance between

two parallel steep slopes.25 The roughing offset allowance is

increased and finishing z-step interval is decreased based on the

height per thickness ratio of rib feature to increase the bending

strength of the rib while finish machining.

The machining method, cutting tools, and cutting conditions

planned by CAPP is transferred to commercial CAM software to

generate tool paths without interference of an operator. The

software was installed in windows operation system of CNC and

run in the background automatically. Drag and drop of 3d models

into HMI is everything that a worker should do for tool path

generation.

3.4 Machining Simulation

The tool path generated in automatic process planning and

CAM software typically takes longer machining time than that of

high level engineer selecting the best process manually. The tool

paths automatically generated rarely includes error which includes

collision accident.

A machining simulation software NCBrain was used to verify

the collision error and optimize machining conditions to increase

productivity as shown in Fig. 4. It controlled in the background of

the controller by HMI to remove the error of NC data, delete

useless tool path, and optimize feed rates based on the knowledge

database.26 The optimized data saved in the directory of the

controller which is used by CNC machine tool for graphite

electrode machining.

3.5 Monitoring and Tool Replacement

The common collision accident happens because of the tool

length compensation value input error of operators. Automatic tool

setter measures each cutting tool before machining to compensate

tool length. The tool length is measured again after machining to

check the difference compared to the original tool length. If the

difference is large because the tool was broken during the

machining process the same tool will be searched in tool magazine.

The broken tool is replaced to the same one and the NC data is

automatically reloaded so that the machining continues again

automatically. The tool usage time is also calculated. If usage time

is longer than tool life, HMI will notice worker to change it to a

new one.

4. Smart Machining Experiment

4.1 Experiment Environments

The developed smart machine tool Smart-UaX27 shown in Fig. 5

was tested to fabricate graphite electrodes in a mold making

company.28 The machining time of conventional method calculated

by experts’ experience was compared with it of the smart machine

tool.

Table 2 is the features of the Smart-UaX. The controller H-

SMART is a dedicated operating system for smart machine tools

that allows anyone to complete easily the entire process; analysis

of machining shape, creation of machining data, setting of tool and

workpiece, and machining. The maximum travel distance is 1,300

mm in the X direction and 750 mm in the Y direction so that many

workpieces can be placed together on one table. The rapid traverse

Fig. 4 Machining simulation and optimization of NCBrain

Fig. 5 Smart machine tool named Smart-UaX

Table 2 Features of Smart-UaX

Features Unit Smart-UaX

Controller - H-SMART

Table size mm 1,200/720

Travel(X/Y/Z) mm 1,300/750/420

Rapid feedrate mm/min 20,000

Max. spindle rpm 12,000

ATC storage ea 50


speed is 20,000 mm/min and the maximum spindle speed is 12000

rpm to meet the high speed machining conditions of graphite. With

50 tools in the tool storage magazine and the tool management

system of the controller, the operator only needs to replace the

worn tool.

The workpieces are 27 graphite electrodes of a commercial

mold maker. The actual electrode designs to be used for electric

discharge machining in the mold company are fabricated in the

smart machine tool without intervention of processing experts. In

the results, all graphite electrodes are fabricated in the smart

machine tool successfully as shown in Fig. 6.

4.2 Process Time

The conventional method analyzes the shape of each part before

machining, selects machining conditions and tools, outputs a large

number of NC files with CAM software, assigns the work

coordinate of the parts in the files, sorts the machining sequence,

edits NC file into one. It transfers the file to CNC controller, fixes

the workpieces in the table, sets the workpiece coordinate system,

and sets the cutting tools. If one part takes 10 min for CAM and

3 min for workpiece positioning and setting based on the expert’s

experience, it took more than 5 hours 51 min to prepare before

machining in the conventional method as shown in Table 3. If

machining time is same, the total fabrication time will be 39 hours

48 min in the conventional method.

The smart machine tool was possible to finish the preparation in

20 min with four clicks after input 27 3d design files and to run

machining process simultaneously with CAM operation as shown

in Fig. 6. The CAM and VM time which is run in background

simultaneously with stock positioning and machining process is

not included to total machining time in case of smart machine tool.

So the 4 hours 51 min preparation time is saved compared to

experts’ conventional method. An operator fixed electrodes on the

table based on the stock position report displayed on the HMI after

designs were input. The sizes and positions are measured with

OMM in the machine, and working coordinate is automatically set

in CNC. The roughing NC data were prepared while the operator

was setting stocks, and the machining started without waiting time.

Because of limited space of the table, stock positioning and

machining process were repeated 3 times. The total fabrication

time, including stock fixing, process planning, tool path generation,

simulation, and machining was 34 hours 57 min as shown in Table 3.

4.3 Operation Complexity

The automatic machining using a smart machine tool is easy to

operate and saves time for machining preparation comparing to

conventional machining method of graphite electrode. A trained

CAM engineer creates the machining path and the NC operator

prepares tools, workpieces, and organizes the order of execution

sequence of the numerous NC files to execute the machining. The

operation complexity of the experts’ conventional method is about

344 steps as shown in Table 4. Both experienced engineers have a

long preparation time and can make mistakes in complex

processes.

The smart machine tool reduced the operational complexity to 4

button clicks in HMI after drag and drop of 3d model data. 1st

AUTO button starts the smart process, 2nd OK button confirms

your models, 3rd JIG Ready button confirms after stocks are set on

Fig. 6 27 graphite electrodes fabricated by smart machine tool

Table 3 Comparison of process time

ProcessTime (hour:min)

Experts Smart-UaX

CAM Sim 4:30 (2:27)

Stock position 1:21 1:00

Machining 33:57 33:57

Total time 39:48 34:57

Table 4 Comparison of operation complexity

Experts Complexity Smart-UaX Complexity

Process plan 27 AUTO 1

CAM 27 × 5 OK 1

Stock set 27 JIG Ready 1

Simulation 27 × 5 Auto RUN 1

Tool set 20

Total 344 Total 4 click


the smart jig, and 4th Auto RUN button starts machining if NC

data of first model is generated as shown in Fig. 1 and Table 4. All

software processes are run in background to prepare machining

during an operator setups workpieces. It is able to automatically

find and replace alternate tools without human operation when the

tool is broken during the machining process. Thereby, the

productivity and quality are only depending on the knowledge of

the smart machine tool without considering the skill of the operator.

4.4 Quality

Fig. 6 shows 27 graphite electrodes fabricated automatically by

the knowledge of smart machine tool. The quality is related to tool

path pattern, tool geometry and cutting condition. The tool path

pattern, step interval and tool diameter are selected at CAPP step

and the spindle speed and federate condition are regulated in

virtual machining step. Experts in the experimented mold company

checked the quality of 27 electrodes and decided the quality is

same to the parts fabricated by their conventional method except a

thin long rib shape.

A lack of knowledge of the smart machine tool can lead to

defects in unconsidered geometry. Smart machining for thin and

long rib shapes caused poor surface roughness due to tool shaking.

In order to improve the machining completeness of the thin and

long rib shape, knowledge data were improved to recognize thin

and long rib features and to apply different machining processes

and machining conditions.

5. Conclusion

As the virtual machining of the digital world is synchronized

with the actual machining, the machine tool will become smart to

simplify and reduce human mistakes in the complex processes.

A smart machine tool that fabricates graphite electrodes with

only 3d model input was developed by the cooperation of process

planning, machining simulation, and machine tool making

companies. The stock positioning method and HMI integrating

software technology is developed in this research.

It reduces the operational complexity to 4 button click after drag

and drop of 3d model data to fabricate multiple-number of graphite

electrodes. The smart machine tool fabricated 27 graphite

electrodes with minimum interference of human in 35 hours.

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