Data Governance to Improve Data Quality for Statistical Process Control (SPC): A Case Study PT. XYZ

Mulyani Pratiwi; Yova Ruldeviyani

doi:10.1145/3451471.3451488

Data Governance to Improve Data Quality for Statistical Process Control (SPC): A Case Study PT. XYZ

Mulyani Pratiwi, Yova Ruldeviyani

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

PT XYZ is having difficulty to implement a continuous monitoring system to be able to quickly identify problems in the process and be able to fix them immediately. The monitoring system is carried out by the Statistical Process Control (SPC) especially the Six Sigma method. However, SPC should be in every process that is important and carried out continuously, so that detection can be done quickly and no one is missed during abnormal events. However, there are obstacles faced in implementing SPC through continuous monitoring, namely the quality of data to present SPC from conventional to real time monitoring. DAMA International said that data quality programs will be more effective when they are part of a data governance program. Therefore, the data governance framework is the focus for developing data quality for SPC at PT. XYZ This study was confirmed by Nonlinear Iterative Partial Least Square (NIPALS) and validated by SPC expert interviews. NIPALS Regression was used because their factors can be verified. Strategic Planning impact to data quality management, the simulation result the accuracy has better 0.89% and standard deviation is better 442% than As-Is condition. This also impacts to early detection which saves cost 22USD per running one product.

Original language	English
Title of host publication	ICSIM 2021 - Proceedings of the 2021 4th International Conference on Software Engineering and Information Management
Publisher	Association for Computing Machinery
Pages	99-105
Number of pages	7
ISBN (Electronic)	9781450388955
DOIs	https://doi.org/10.1145/3451471.3451488
Publication status	Published - 16 Jan 2021
Event	4th International Conference on Software Engineering and Information Management, ICSIM 2021 - Virtual, Online, Japan Duration: 16 Jan 2021 → 18 Jan 2021

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	4th International Conference on Software Engineering and Information Management, ICSIM 2021
Country/Territory	Japan
City	Virtual, Online
Period	16/01/21 → 18/01/21

Keywords

Data Governance
Data Quality
NIPALS
Six Sigma
SPC

Access to Document

10.1145/3451471.3451488

Cite this

Pratiwi, M., & Ruldeviyani, Y. (2021). Data Governance to Improve Data Quality for Statistical Process Control (SPC): A Case Study PT. XYZ. In ICSIM 2021 - Proceedings of the 2021 4th International Conference on Software Engineering and Information Management (pp. 99-105). Article 3451488 (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3451471.3451488

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title = "Data Governance to Improve Data Quality for Statistical Process Control (SPC): A Case Study PT. XYZ",

abstract = "PT XYZ is having difficulty to implement a continuous monitoring system to be able to quickly identify problems in the process and be able to fix them immediately. The monitoring system is carried out by the Statistical Process Control (SPC) especially the Six Sigma method. However, SPC should be in every process that is important and carried out continuously, so that detection can be done quickly and no one is missed during abnormal events. However, there are obstacles faced in implementing SPC through continuous monitoring, namely the quality of data to present SPC from conventional to real time monitoring. DAMA International said that data quality programs will be more effective when they are part of a data governance program. Therefore, the data governance framework is the focus for developing data quality for SPC at PT. XYZ This study was confirmed by Nonlinear Iterative Partial Least Square (NIPALS) and validated by SPC expert interviews. NIPALS Regression was used because their factors can be verified. Strategic Planning impact to data quality management, the simulation result the accuracy has better 0.89% and standard deviation is better 442% than As-Is condition. This also impacts to early detection which saves cost 22USD per running one product.",

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Pratiwi, M & Ruldeviyani, Y 2021, Data Governance to Improve Data Quality for Statistical Process Control (SPC): A Case Study PT. XYZ. in ICSIM 2021 - Proceedings of the 2021 4th International Conference on Software Engineering and Information Management., 3451488, ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 99-105, 4th International Conference on Software Engineering and Information Management, ICSIM 2021, Virtual, Online, Japan, 16/01/21. https://doi.org/10.1145/3451471.3451488

Data Governance to Improve Data Quality for Statistical Process Control (SPC): A Case Study PT. XYZ. / Pratiwi, Mulyani; Ruldeviyani, Yova.
ICSIM 2021 - Proceedings of the 2021 4th International Conference on Software Engineering and Information Management. Association for Computing Machinery, 2021. p. 99-105 3451488 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2021/1/16

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N2 - PT XYZ is having difficulty to implement a continuous monitoring system to be able to quickly identify problems in the process and be able to fix them immediately. The monitoring system is carried out by the Statistical Process Control (SPC) especially the Six Sigma method. However, SPC should be in every process that is important and carried out continuously, so that detection can be done quickly and no one is missed during abnormal events. However, there are obstacles faced in implementing SPC through continuous monitoring, namely the quality of data to present SPC from conventional to real time monitoring. DAMA International said that data quality programs will be more effective when they are part of a data governance program. Therefore, the data governance framework is the focus for developing data quality for SPC at PT. XYZ This study was confirmed by Nonlinear Iterative Partial Least Square (NIPALS) and validated by SPC expert interviews. NIPALS Regression was used because their factors can be verified. Strategic Planning impact to data quality management, the simulation result the accuracy has better 0.89% and standard deviation is better 442% than As-Is condition. This also impacts to early detection which saves cost 22USD per running one product.

AB - PT XYZ is having difficulty to implement a continuous monitoring system to be able to quickly identify problems in the process and be able to fix them immediately. The monitoring system is carried out by the Statistical Process Control (SPC) especially the Six Sigma method. However, SPC should be in every process that is important and carried out continuously, so that detection can be done quickly and no one is missed during abnormal events. However, there are obstacles faced in implementing SPC through continuous monitoring, namely the quality of data to present SPC from conventional to real time monitoring. DAMA International said that data quality programs will be more effective when they are part of a data governance program. Therefore, the data governance framework is the focus for developing data quality for SPC at PT. XYZ This study was confirmed by Nonlinear Iterative Partial Least Square (NIPALS) and validated by SPC expert interviews. NIPALS Regression was used because their factors can be verified. Strategic Planning impact to data quality management, the simulation result the accuracy has better 0.89% and standard deviation is better 442% than As-Is condition. This also impacts to early detection which saves cost 22USD per running one product.

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Pratiwi M, Ruldeviyani Y. Data Governance to Improve Data Quality for Statistical Process Control (SPC): A Case Study PT. XYZ. In ICSIM 2021 - Proceedings of the 2021 4th International Conference on Software Engineering and Information Management. Association for Computing Machinery. 2021. p. 99-105. 3451488. (ACM International Conference Proceeding Series). doi: 10.1145/3451471.3451488

Data Governance to Improve Data Quality for Statistical Process Control (SPC): A Case Study PT. XYZ

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