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Framework of a computer-aided short-run SPC planning system

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Abstract

Statistical process control (SPC) is recognized as a technique to achieve cost-effective quality control through continuous manufacturing process improvement. But with growing demand for small-batch and high-variety products in the current dynamic market, the involved manufacturing processes are becoming more complex, variable, and flexible, which are not suitable for implementing SPC in the traditional way. Hence, short-run SPC is applied instead. Planning is a critical phase in the implementation of short-run SPC, which includes the formation of part families and the determination of corresponding data collection. To ensure homogeneity of the family members, this paper addresses preliminary analysis on the characteristics and applications of pertinent factors, and statistical analysis for SPC-based part family formation. To improve the efficiency of SPC planning and the adaptation for computer-integrated manufacturing, a framework for a computer-aided short-run SPC planning system is proposed using group technology classification and coding concepts. This invokes a 29-digit hybrid code appended to the Opitz coding scheme. Further, a supportive database is also proposed to facilitate coding information retrieval and system updating. A case study is shown with data collected from injection-mold manufacturing, which typically involves small-batch processes.

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Correspondence to Y. S. Wong.

Appendices

Appendix 1: abstracted processing information of injection mold 4525

Steps

Feature name

Operation type

Machine type

Machine used

Cutter type and diameter

Step 3

Face 5, step 3

End milling

CNC_Finishing

Moki Seiki SV-500

Flat end mill ϕ10

Step 7

Face 1, 3

End milling

CNC_Finishing

Moki Seiki SV-500

Flat end mill ϕ6

Step 11

Face 2

End milling

CNC_Finishing

Moki Seiki SV-500

Flat end mill ϕ12

Step 13

Face 4

End milling

CNC_Finishing

Moki Seiki SV-500

Flat end mill ϕ12

Step 21

Step 1

End milling

CNC_Finishing

Moki Seiki SV-500

Flat end mill ϕ12

Step 23

Step 2

End milling

CNC_Finishing

Moki Seiki SV-500

Flat end mill ϕ12

Step 29

Face 6

End milling

CNC_Finishing

Moki Seiki SV-500

Flat end mill ϕ 10

Appendix 2: code of each feature

Feature name

D7_D10_D11_D12D13D14_D15D16_D17D18D19

D20D21D22D23_D24D25D26_D27D28D29

Normal value

Face 5

A_1_A_C01_01_A02

4525_203_003

200.26

Step 3

A_1_A_C01_01_A04

4525_203_004

−20.53

Face 1

A_1_A_C01_01_A01

4525_203_008

−157.93

Face 3

A_1_A_C01_01_A01

4525_203_009

119.42

Face 2

A_1_A_C01_01_A01

4525_203_015

−2.92

Face 4

A_1_A_C01_01_A01

4525_203_018

−12.20

Step 1

A_1_A_C01_01_ A01

4525_203_027

−112.00

Step 2

A_1_A_C01_01_ A01

4525_203_029

−110.00

Face 6

A_1_A_C01_01_ A02

4525_203_033

25.04

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Zhu, Y.D., Wong, Y.S. & Lee, K.S. Framework of a computer-aided short-run SPC planning system. Int J Adv Manuf Technol 34, 362–377 (2007). https://doi.org/10.1007/s00170-006-0610-7

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  • DOI: https://doi.org/10.1007/s00170-006-0610-7

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