Analysis of Production Transition Loss Ratio as Production Planning Performance Indicator in PT Mandom Indonesia Tbk
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As one of the famous cosmetic manufacturers in Indonesia, and also as part of Mandom Group that support global demand, PT Mandom Indonesia Tbk has up to 2.500 product variants adapting domestic and international regulations with an average of 500 variants were being produced in a month. Because there are differences between each variant, adjustment setting between each transition is mandatory. This condition is worsened due to previous policy which made a product could be produced up to three times a month. With no clear controlling method, the production planning division creates a production schedule without considering thoroughly the time loss caused by transition activities and so the loss caused by the stop of production due to transition is also tripled up to 1.800 transitions in a month. Within this paper, author would like to describe a solution that has already been tested within the company which is one-phase production planning. One-phase production planning is a method developed by author to design a production schedule based on transition priority level in order to reduce transition activities as much as possible. The method is adopting the basic principle of OEE and is improved based on the company condition so it could be implemented easily and gave a positive impact on the company. Transition activities were divided into three categories which are washing transition, part changing transition, and small setting transition. Those transitions were tested by using SPC method and analyzed to determine which transition should be prioritized. To maintain the objectivity of the project result, a new monitoring tool for production planning performance has been created which is the transition loss ratio. Transition loss ratio is a simplified calculation method customized for PT Mandom Indonesia Tbk that visualizes the amount of loss by presenting it in the percentage of the total scheduled value. One-phase production policy has been tested for two months with the result of reducing transition loss from 9.5% to 7.5% which equals to 14,2 Billion Indonesian Rupiah (±>$984,000) in a year.
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References
-
Arieska, Permadina Kanah. Herdiani, Novera. 2018. Margin of Error Between Simple Random Sampling and Stratified Sampling. International Conference on Technopreneurship and Education (ICTE), pp 4.
Google Scholar
1
-
Greenberg, Betsy. 2008. Excel Manual for Introduction to the Practice of Statistics Sixth Edition. University of Texas. pp. 68.
Google Scholar
2
-
Groebner, David F. Shannon, Patrick W. Fry, Phillip C. Smith, Kent D. 2010. Business Statistics: A Decision-Making Approach, 8th Edition, Pearson. Chapter 19, pp.19-6.
Google Scholar
3
-
Jacobs, F. Robert. Chase, Richard B. 2018. Operations and Supply Chain Management: Fifteenth Edition. McGraw-Hill Education, pp 325.
Google Scholar
4
-
McNeese, Bill. 2016. How Much Data Do I Need to Calculate, BPI Consulting. Viewed at 28 September 2021 from https://www.spcforexcel.com/Downloads/pdf/How-Much-Data-Do-I-Need-to-Calculate-Control-Limits.pdf.
Google Scholar
5
-
PT Mandom Indonesia Tbk. Master Production Schedule 2019. Unpublished Manuscript.
Google Scholar
6
-
PT Mandom Indonesia Tbk. Master Production Schedule 2020. Unpublished Manuscript.
Google Scholar
7
-
PT Mandom Indonesia Tbk. Master Production Schedule 2021. Unpublished Manuscript.
Google Scholar
8
-
PT Mandom Indonesia Tbk. Kanri Genka: Production Loss Report 2019 – 2021. Unpublished Manuscript.
Google Scholar
9
-
PT Mandom Indonesia Tbk. Product Master Data 2019 – 2021. Unpublished Manuscript.
Google Scholar
10
-
PT Mandom Indonesia Tbk. Monthly Actual Cost 2019 – 2021. Unpublished Manuscript.
Google Scholar
11
-
Rao, Suhasini Subba. 2021. Data Analysis and Statistical Methods: Lecture 13. Texas A&M University. Viewed at 29th September 2021 from https://web.stat.tamu.edu/~suhasini/teaching651/lecture13MWF.pdf.
Google Scholar
12
-
Republik Indonesia. 2021. Pemberlakuan Pembatasan Kegiatan Masyarakat Level 4, Level 3, Dan Level 2 Corona Virus Disease 2019 di Wilayah Jawa dan Bali, Instruksi Menteri Dalam Negeri Nomor 27 Tahun 2021, Jakarta. Viewed at 30th September 2021 from https://ditjenbinaadwil.kemendagri.go.id/download/file/Inmendagri_No_27_Tahun_2021.pdf.
Google Scholar
13
-
Republik Indonesia. 2021. Pemberlakuan Pembatasan Kegiatan Masyarakat Darurat Corona Virus Disease 2019 Di Wilayah Jawa Dan Bali, Instruksi Menteri Dalam Negeri Nomor 15 Tahun 2021, Jakarta. Viewed at 30th September 2021 from https://covid19.go.id/storage/app/media/Regulasi/2021/Juli/INMENDAGRI%20NO%2015%20TAHUN%202021%20TENTANG%20PPKM%20DARURAT.pdf.
Google Scholar
14
-
Ron, A.J. De. Rooda, J.E. 2006. OEE and Equipment Effectiveness; an Evaluation. International Journal of Production Research Vol. 44 No. 23. pp 1.
Google Scholar
15
-
Scodanibbio, Carlo. 2008. World Class TPM: How to Calculate Overall Equipment Effectiveness (OEE). Viewed at 24th November 2021 from www.scodanibbio.com.
Google Scholar
16
-
Taherdoost, Hamed. 2017. Determining Sample Size; Hot to Calculate Survey Sample Size. Viewed at 24th November 2021 from https://www.researchgate.net/profile/Hamed-Taherdoost/publication/322887480_Determining_Sample_Size_How_to_Calculate_Survey_Sample_Size/links/5a7419b80f7e9b20d490577c/Determining-Sample-Size-How-to-Calculate-Survey-Sample-Size.pdf.
Google Scholar
17
-
Tsarouhas, Panagiotis H. (2020). Overall Equipment Effectiveness (OEE) Evaluation for an Automated Ice Cream Production Line. International Journal of Productivity and Performance Management Vol. 69 No. 5, page 7.
Google Scholar
18
-
Veroya, Felix C. 2014. Introduction to Statistical Process Control: A Problem Solving Process Approach, Bookboon.com. pp 47-58.
Google Scholar
19