The principal aim of this project is to develop a methodology and

its associated algorithm to prepare the component for repair and

to automatically identify the welded part of the repaired geome-

try to enable adaptive machining for creating a smooth surface

finish for the geometry.

The objectives of this project are to:

1.1.Review and analyse the state of the state of the art of re-

manufacturing to understand the concept.

1.2. Develop a methodology for the generation of customised

tool steps by creating a programming algorithm for smooth sur-

face and the preparation for testing using MATLAB.

1.3. Demonstrate and verification of the proposed methodology

by using a 3D printed part.

Summary Remanufacturing is comprehensive and challenging industrial

procedure to bring defective part which have failed due to fatigue

back to use. The process is currently done manually, this is time

consuming, hence the need for adaptive repair. A good surface

finish should have a theoretical surface between finish 1.6 and

3.2 µm

The 3 mains Methodology for adaptive repair

Preparation of the surface of an unknown defective part ge-

ometry for repair

Comparison of geometry with a defect with the original ge-

ometry

Generation of G-code for welding

Fill up material with weld

Creating a smooth surface after welding

Develop algorithm to create tool path

Generate G-code which is used for CNC machining process

3. CYLINDRIC VS PRISMATIC

SHAPE Most rolling stock components are cylindrical in shape e.g.

crankshaft /drive shaft.

A turning operation is needed to improve the surface finish on

shafts

The typical machining or cutting parameters for shafts are

Depth of cut, Cutting feed and Feed rate

Rolling stock components are usually prismatic shaped

A milling operation is needed to improve the surface finish

An endmill or ball nose cutter is often used

The machining parameter include spindle speed, cutting

speed, feed rate, number of tooth.

1. AIMS AND OBJECTIVES

2. BACKGROUND

4.2. COMMON ROLLING STOCK MATERIALS

Material End mill cutter (6mm diameter)

Turning tool

Cutting speed (m/min)

Feed per tooth (mm)

Cutting speed (m/min)

Feed rate for fine machining

Mild steel 30 – 40 Roughing cut

= 0.020

Finishing cut

= 0.039

120 - 200 0.03 – 0.1

Cast iron 18 – 25 80 – 140 0.05 – 0.2

Aluminium 50 – 110 80 – 1200 0.05 – 0.5

Stainless steel

10 - 15 140 – 190 0.02 – 0.6

Brass 30 – 50 300 - 1000 0.01 – 0.2

TABLE 1: Displaying the cutting parameter

4.1. CUTTING PARAMETERS FOR MACHINING

Designation Abbreviation Unit formula

Spindle speed n RPM n=( vc ×1000)/

(d × π)

Cutting speed Vc m/min Vc =(d ××n)/

1000

Feed rate Fr mm/min Milling

Fr=fr × Z× n

Turning

Fr=fr × n

Theoretical Surface finish

Ra µm Ra=(fr^2)/8R

Where Z = number of tooth/flute can be from 1, 2 or more Fz = feed per tooth (mm) R = radius of cutter (mm) d = diameter of work piece for turning and tool cutter diameter for milling

π = 3.14

A mild steel block of size 75mm x 60 x 30mm

A hole was cut out in the middle of the block.

The defective part was cleaned with an electronic flap disc.

A MIG (Metal Inert Gas) was used to weld the surface to about two

2mm high.

The block was taken to the CNC machine laboratory.

The block was modelled on Solidworks 2017.

The CAD model was transferred to SolidCAM software.

The software was setup for face milling. An 6 mm diameter end mill cut-

ter was used with the calculated feed rate of 248.28mm/min and the

spindle speed of 1591.55RPM

A simulation was run to see the tool path and GCode

The GCode was fed into the CNC machine which had milled off the

welded part off the block to create a smooth surface

5. METHODOLOGY

Turning operation

Material = aluminium

Diameter of shaft = 80mm

Spindle speed = (130 ×1000)/(80 × π) = 517.25 rpm

Feed rate = 0.1 x 517.25 = 51.73 mm/min

Milling operation

Material = mild steel

Diameter of endmill cutter = 6mm

Spindle speed = (30 ×1000)/(6 × π) = 1591.55 rpm

Feed rate = 0.039 x 4 x 1591.55 = 248.28 mm/min

Feed rate per revolution = 0.039 x 4 = 0.156 mm/rev

Ra = 〖0.156〗^2/(8 ×3)=1.014×〖10〗^(-3) mm

Unit conversion: 1mm = 1000 µm

Ra = 1.46 ×〖10〗^(-3) ×1000=1.46 µm

5.1 STRATEGY FOR G-CODE

1.Create a text file

2.Identify the coordinate of the geometry

3.Determine the start as finish location based on the area of the re-

paired surface.

4.Calculate the cutting parameters such as feed rate and spindle

speed.

5.Manually write the necessary M and G codes.

6.Develop an algorithm on MATLAB.

7.Set variables as codes and then Generate G-code.

9.The G-Code should generate automatically in the text file.

5.2. STRATEGY FOR TOOL PATH

6. VERIFICATION

7. CONCLUSION

The process of developing an algorithm for the adaptive repair for

smooth surface has been successful.

However, the verification process

The theoretical roughness for the milling process is below the threshold

of 1.6 and 3.2µm

The factors that affect the smooth include the feed rate, chip load, spin-

dle speed and number of cutter tooth.

For this case the number of tooth Z can be 5, therefore the recalculated

Ra would be 1.6µm

8. FURTHER WORK

Another verification is to be carried out with a 3D printer.

Due to time and the volume of work involved in this project, more

work needs to be done on the preparation of the surface for mate-

rial deposition.

9. REFERENCES

•Table 1 was sourced from WNT Mastertool “Total Tooling” catalogue

•https://smithy.com/machining-reference/lathe-turning/page/2

18/04/18

ADAPTIVE REPAIR FOR REMANUFACTURING

BY OSATO OSEMWENGIE

13419381

4. THEORY

Figure 2: mild

steel with defect

Figure 3: welded

surface

Supervisor: Dr Wang

Internal Examiner: Mr Milne

Identify the boundary: since the geometry

for the repaired (welded) surface is known,

identify the start and finish point of the ar-

ea.

Create an area on the matlab as Xmax,

Xmin, Ymax , Ymin, Zmin and Zmax

Create a point cloud with the coordinates

and another point cloud with the a varia-

ble.

Determine the tool path width, number of

tool steps set this as variables on MATLAB

Generate the tool path automatically

Figure 1: Framework of methodology, the parts highlighted in green

where this project started from and ends in yellow.