Applying dashboards for manufacturing by comparing programs used between Google Data Studio and Microsoft Power BI

Authors

  • Warakorn Thaiprecha Student in Department of Industrial Engineering and Management, Faculty of Engineering and Industrial Technology, Silpakorn University
  • Kanate Puntusavase Lecturer in Department of Industrial Engineering and Management, Faculty of Engineering and Industrial Technology, Silpakorn University

Keywords:

Power BI, Power Query, Normalization, Dashboard

Abstract

The purposes of this research were 1) to apply the dashboard to solve various problems, 2) to manage database systems that can be used in Power BI programs and Google Data Studio. The industrial model factory is a brake pad factory. The researcher analyzed the problems from all 3 departments, the planning department, the production department and the quality control department. The researcher analyzed problems, databases and selected indicators to use. The databases are managed before being used in Microsoft Power BI to analyze, examine, identify trends in problems and expected to happen. The researcher has applied indicators and control charts for display. Information is collected and managed by normalization. From the analysis of problems from 3 departments, it was found that the planning department found problems in delivery on time because the status of production is unknown. The production department encountered the problem of delayed surveillance because the problem is not summarized from the database. The quality control department encountered the tendency problem of the product's test results. This affects the product's performance because the test hardness (hardness) and specific gravity (specific gravity) tend to be low, but the test results are within the specified criteria. Making it not vigilant about the trend of the test results. After dashboard creation compares Microsoft Power BI and Google Data Studio. The research results found that the result of using the dashboard to detect problems that arise can be. The planning department can solve the problem of overdue deliveries. The production department can help reduce production problems in terms of productivity and waste monitoring. Quality control department to control problems arising from test values, see trends in product properties to monitor problems that arise can analyze waste to track problems. Compare the usage of Microsoft Power BI and Google Data Studio. Google Data Studio is appropriate to start operations because it is easy-to-use report that can be forwarded. Signing up is not difficult because it is a public email and importing data is not complicated. Microsoft Power BI can be further developed. Easy-to-manage data source. No duplicate preparing data is required.

References

ทนง ประสานพานิช พ.บ. (2555) แผนภูมิควบคุม (Control Chart) กับงานประจำ. วารสารศูนย์การศึกษาแพทยศาสตร์คลินิก โรงพยาบาลพระปกเกล้า. 29(3), 236 – 244

ศิระ เอกบุตร (2562). ก้าวสู่การเตรียมข้อมูลยุคใหม่ด้วย Power Query [ออนไลน์]. ค้นเมื่อ 25 มิถุนายน 2565, จาก : https://www.thepexcel.com/excel-power-up-power-query-ep02/

Google One. (ม.ม.ป.). พื้นที่เก็บข้อมูล [ออนไลน์]. ค้นเมื่อ 25 มิถุนายน 2565, จาก : https://blog.skooldio.com/power-bi-vs-data-studio/

Microsoft Power BI. (ม.ม.ป.). ราคา Power BI [ออนไลน์]. ค้นเมื่อ 25 มิถุนายน 2565, จาก : https://powerbi.microsoft.com/th-th/pricing/

Multitech. (2563). Power BI Architecture ? [ออนไลน์]. ค้นเมื่อ 25 มิถุนายน 2565, จาก : https://informationit27.medium.com/power-bi-architecture-5cd425c8b103

Panchart Mitrakul. (2564). อยากทำ Business Intelligence ใช้โปรแกรมอะไรดี? [ออนไลน์]. ค้นเมื่อ 25 มิถุนายน 2565, จาก : https://blog.skooldio.com/power-bi-vs-data-studio/

Ferreira, L., Putnik, G., Cunha, M., Putnik, Z., Castro, H., Alves, C., Shah, V., & Varela, M. L. R. (2013). Cloudlet Architecture for Dashboard in Cloud and Ubiquitous Manufacturing. Procedia CIRP, 12, 366-371.

Galiveedu Shoaib, S. N. (2022). Power Bi Dashboard for Data Analysis. International Research Journal of Engineering and Technology, 09, 2881-2885.

Gröger, C., Hillmann, M., Hahn, F., Mitschang, B., & Westkämper, E. (2013). The Operational Process Dashboard for Manufacturing. Procedia CIRP, 7, 205-210.

M. M. Yusof, E., S. Othman, M., & M. Yusof, R. (2018). Operational dashboard: Accelerator for shop floor workers. International Journal of Engineering & Technology, 7(2.29).

Mazumdar, S., Varga, A., Lanfranchi, V., Petrelli, D., & Ciravegna, F. (2011). A Knowledge Dashboard for Manufacturing Industries. in The Semantic Web: ESWC 2011 Workshops - ESWC 2011 Workshops, 29th- 30th May 2011. 112-124. Germany : Springer-Verlag Berlin Heidelberg.

Vilarinho, S., Lopes, I., & Sousa, S. (2017). Design Procedure to Develop Dashboards Aimed at Improving the Performance of Productive Equipment and Processes. Procedia Manufacturing, 11, 1634-1641.

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Published

2023-12-29