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Production Scheduling Improvement of Nut Manufacturing Process Using Production Time Forecasting

EasyChair Preprint no. 9639

6 pagesDate: January 30, 2023


This research aims to study the optimization of the auto part manufacturing process to increase efficiency and ensure the punctuality of product delivery. The study found that the problems were that the setup for each manufacturing engine model was slow; spare parts for the engine was not enough for the manufacturing process; and the engine did not work to its full potential. This made the manufacturing process take more time than expected. To compensate for the unexpected additional time, spontaneous overtime was necessarily implemented. Therefore, by gathering the previous manufacturing plan, manufacturing details and delivery records, as well as the manufacturing process examination records. The data were then analyzed using the MINITAB program to forecast the production time. The data received from the forecast were used to create a new manufacturing plan which led to more accurate manufacturing results. After the forecast had been made, it could be concluded that this forecasting method can be applied to help increase overall manufacturing output, ensure timely product delivery, and reduce additional costs from unexpected problems such as overtime expenses and shipping fees for delayed delivery. And reduce the delay in the process, and even prevent late delivery.

Keyphrases: Manufacture Regression Analysis, Manufacturing Management Optimization, regression analysis

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Pavee Siriruk and Kalyarat Phukchum},
  title = {Production Scheduling Improvement of Nut Manufacturing Process Using Production Time Forecasting},
  howpublished = {EasyChair Preprint no. 9639},

  year = {EasyChair, 2023}}
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